INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89099, 2018, 'plos', 'xcfx86-evo: A program to evolve phenotypic models of biological networks', 'Henry, Adrien|Hemery, Mathieu|Franxc3xa7ois, Paul', 'Physics Department, McGill University, Montreal, Quxc3xa9bec, Canada.|Physics Department, McGill University, Montreal, Quxc3xa9bec, Canada.|Physics Department, McGill University, Montreal, Quxc3xa9bec, Canada.', 'Canada|Canada|Canada', 5, 'Algorithms|Animals|Computational Biology|Embryonic Development|Gene Regulatory Networks|Genetic Fitness|Mice|Models, Biological|Phenotype|Software', 'Journal Article', '10.1371/journal.pcbi.1006244', '29889886', 'Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present xcfx86-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of xcfx86-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. xcfx86-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.'),
(89100, 2018, 'plos', '3D morphology-based clustering and simulation of human pyramidal cell dendritic spines', 'Luengo-Sanchez, Sergio|Fernaud-Espinosa, Isabel|Bielza, Concha|Benavides-Piccione, Ruth|Larrañaga, Pedro|DeFelipe, Javier', 'Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.|Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.|Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.|Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.|Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.|Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo, Madrid, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 4, 'Cerebral Cortex|Cluster Analysis|Computer Simulation|Dendrites|Dendritic Spines|Humans|Imaging, Three-Dimensional|Pyramidal Cells|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006221', '29897896', 'The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.'),
(89101, 2018, 'plos', 'Identifying functional groups among the diverse, recombining antigenic var genes of the malaria parasite Plasmodium falciparum from a local community in Ghana', 'Rorick, Mary M|Baskerville, Edward B|Rask, Thomas S|Day, Karen P|Pascual, Mercedes', 'Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States of America.|Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States of America.|School of Biosciences, Bio21 Institute, The University of Melbourne, Melbourne, AU.|School of Biosciences, Bio21 Institute, The University of Melbourne, Melbourne, AU.|Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States of America.', 'United States|United States|-|-|United States', 1, 'Animals|Antigenic Variation|Antigens, Protozoan|Computational Biology|Conserved Sequence|Female|Genetic Variation|Ghana|Humans|Malaria, Falciparum|Male|Parasites|Plasmodium falciparum|Protozoan Proteins|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1006174', '29897905', 'A challenge in studying diverse multi-copy gene families is deciphering distinct functional types within immense sequence variation. Functional changes can in some cases be tracked through the evolutionary history of a gene family, however phylogenetic approaches are not possible in cases where gene families diversify primarily by recombination. We take a network theoretical approach to functionally classify the highly recombining var antigenic gene family of the malaria parasite Plasmodium falciparum. We sample var DBLxcexb1 sequence types from a local population in Ghana, and classify 9,276 of these variants into just 48 functional types. Our approach is to first decompose each sequence type into its constituent, recombining parts, we then use a stochastic block model to identify functional groups among the parts, finally, we classify the sequence types based on which functional groups they contain. This method for functional classification does not rely on an inferred phylogenetic history, nor does it rely on inferring function based on conserved sequence features. Instead, it infers functional similarity among recombining parts based on the sharing of similar co-occurrence interactions with other parts. This method can therefore group sequences that have undetectable sequence homology or even distinct origination. Describing these 48 var functional types allows us to simplify the antigenic diversity within our dataset by over two orders of magnitude. We consider how the var functional types are distributed in isolates, and find a nonrandom pattern reflecting that common var functional types are non-randomly distinct from one another in terms of their functional composition. The coarse-graining of var gene diversity into biologically meaningful functional groups has important implications for understanding the disease ecology and evolution of this system, as well as for designing effective epidemiological monitoring and intervention.'),
(89102, 2018, 'plos', 'A biophysical mechanism for preferred direction enhancement in fly motion vision', 'Borst, Alexander', 'Max-Planck-Institute of Neurobiology, Martinsried, Germany.', 'Germany', 8, 'Animals|Biophysical Phenomena|Biophysics|Dendrites|Diptera|Motion|Motion Perception|Neurons|Photic Stimulation|Signal Transduction|Vision, Ocular|Visual Acuity|Visual Cortex|Visual Fields', 'Journal Article', '10.1371/journal.pcbi.1006240', '29897917', 'Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond to visual stimuli moving in one but not in the opposite direction, so-called direction-selective neurons, are found abundantly. In general, direction selectivity can arise by either signal amplification for stimuli moving in the cells preferred direction (preferred direction enhancement), signal suppression for stimuli moving along the opposite direction (null direction suppression), or a combination of both. While signal suppression can be readily implemented in biophysical terms by a hyperpolarization followed by a rectification corresponding to the nonlinear voltage-dependence of the Calcium channel, the biophysical mechanism for signal amplification has remained unclear so far. Taking inspiration from the fly, I analyze a neural circuit where a direction-selective ON-cell receives inhibitory input from an OFF cell on the preferred side of the dendrite, while excitatory ON-cells contact the dendrite centrally. This way, an ON edge moving along the cells preferred direction suppresses the inhibitory input, leading to a release from inhibition in the postsynaptic cell. The benefit of such a two-fold signal inversion lies in the resulting increase of the postsynaptic cells input resistance, amplifying its response to a subsequent excitatory input signal even with a passive dendrite, i.e. without voltage-gated ion channels. A motion detector implementing this mechanism together with null direction suppression shows a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio.'),
(89103, 2018, 'plos', 'Cloud computing applications for biomedical science: A perspective', 'Navale, Vivek|Bourne, Philip E', 'Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States', 13, 'Biomedical Research|Cloud Computing|Computational Biology|Humans', 'Journal Article', '10.1371/journal.pcbi.1006144', '29902176', 'Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.'),
(89104, 2018, 'plos', 'Hybrid stochastic framework predicts efficacy of prophylaxis against HIV: An example with different dolutegravir prophylaxis schemes', 'Duwal, Sulav|Dickinson, Laura|Khoo, Saye|von Kleist, Max', 'Department of Mathematics & Computer Science, Freie Universität Berlin, Berlin, Germany.|Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.|Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.|Department of Mathematics & Computer Science, Freie Universität Berlin, Berlin, Germany.', 'Germany|United Kingdom|United Kingdom|Germany', 0, 'Adult|Aged|Anti-HIV Agents|Computer Simulation|Female|HIV Infections|HIV-1|Heterocyclic Compounds, 3-Ring|Humans|Male|Middle Aged|Models, Statistical|Pre-Exposure Prophylaxis|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006155', '29902179', 'To achieve the 90-90-90 goals set by UNAIDS, the number of new HIV infections needs to decrease to approximately 500,000 by 2020. One of the five pillars to achieve this goal is pre-exposure prophylaxis (PrEP). Truvada (emtricitabine-tenofovir) is currently the only medication approved for PrEP. Despite its advantages, Truvada is costly and requires individuals to adhere to the once-daily regimen. To improve PrEP, many next-generation regimen, including long-acting formulations, are currently investigated. However, pre-clinical testing may not guide candidate selection, since it often fails to translate into clinical efficacy. On the other hand, quantifying prophylactic efficacy in the clinic is ethically problematic and requires to conduct long (years) and large (N>1000 individuals) trials, precluding systematic evaluation of candidates and deployment strategies. To prioritize- and help design PrEP regimen, tools are urgently needed that integrate pharmacological-, viral- and host factors determining prophylactic efficacy. Integrating the aforementioned factors, we developed an efficient and exact stochastic simulation approach to predict prophylactic efficacy, as an example for dolutegravir (DTG). Combining the population pharmacokinetics of DTG with the stochastic framework, we predicted that plasma concentrations of 145.18 and 722.23nM prevent 50- and 90% sexual transmissions respectively. We then predicted the reduction in HIV infection when DTG was used in PrEP, PrEP on demand and post-exposure prophylaxis (PEP) before/after virus exposure. Once daily PrEP with 50mg oral DTG prevented 99-100% infections, and 85% of infections when 50% of dosing events were missed. PrEP on demand prevented 79-84% infections and PEP >80% when initiated within 6 hours after virus exposure and continued for as long as possible. While the simulation framework can easily be adapted to other PrEP candidates, our simulations indicated that oral 50mg DTG is non-inferior to Truvada. Moreover, the predicted 90% preventive concentrations can guide release kinetics of currently developed DTG nano-formulations.'),
(89105, 2018, 'plos', 'Mechanical evolution of DNA double-strand breaks in the nucleosome', 'Cleri, Fabrizio|Landuzzi, Fabio|Blossey, Ralf', 'Institut dElectronique, Microélectronique et Nanotechnologie (IEMN, UMR Cnrs 8520), 59652 Villeneuve dAscq, France.|Institut dElectronique, Microélectronique et Nanotechnologie (IEMN, UMR Cnrs 8520), 59652 Villeneuve dAscq, France.|Unité de Glycobiologie Structurelle et Fonctionnelle (UGSF, UMR Cnrs 8576), 59000 Lille, France.', 'France|France|France', 3, 'Cell Nucleus|Computer Simulation|DNA|DNA Breaks, Double-Stranded|DNA Damage|DNA Repair|Histones|Hydrogen Bonding|Molecular Dynamics Simulation|Nucleosomes', 'Journal Article', '10.1371/journal.pcbi.1006224', '29902181', 'Double strand breaks (DSB) in the DNA backbone are the most lethal type of defect induced in the cell nucleus by chemical and radiation treatments of cancer. However, little is known about the outcomes of damage in nucleosomal DNA, and on its effects on damage repair. We performed microsecond-long molecular dynamics computer simulations of nucleosomes including a DSB at various sites, to characterize the early stages of the evolution of this DNA lesion. The damaged structures are studied by the essential dynamics of DNA and histones, and compared to the intact nucleosome, thus exposing key features of the interactions. All DSB configurations tend to remain compact, with only the terminal bases interacting with histone proteins. Umbrella sampling calculations show that broken DNA ends at the DSB must overcome a free-energy barrier to detach from the nucleosome core. Finally, by calculating the covariant mechanical stress, we demonstrate that the coupled bending and torsional stress can force the DSB free ends to open up straight, thus making it accessible to damage signalling proteins.'),
(89106, 2018, 'plos', 'Classification of red blood cell shapes in flow using outlier tolerant machine learning', 'Kihm, Alexander|Kaestner, Lars|Wagner, Christian|Quint, Stephan', 'Department of Experimental Physics, Saarland University, Campus E2 6, Saarbrücken, Germany.|Department of Experimental Physics, Saarland University, Campus E2 6, Saarbrücken, Germany.|Department of Experimental Physics, Saarland University, Campus E2 6, Saarbrücken, Germany.|Department of Experimental Physics, Saarland University, Campus E2 6, Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany', 17, 'Blood Flow Velocity|Cell Shape|Computational Biology|Erythrocytes|Humans|Hydrodynamics|Machine Learning|Models, Theoretical|Neural Networks (Computer)', 'Journal Article', '10.1371/journal.pcbi.1006278', '29906283', 'The manual evaluation, classification and counting of biological objects demands for an enormous expenditure of time and subjective human input may be a source of error. Investigating the shape of red blood cells (RBCs) in microcapillary Poiseuille flow, we overcome this drawback by introducing a convolutional neural regression network for an automatic, outlier tolerant shape classification. From our experiments we expect two stable geometries: the so-called slipper and croissant shapes depending on the prevailing flow conditions and the cell-intrinsic parameters. Whereas croissants mostly occur at low shear rates, slippers evolve at higher flow velocities. With our method, we are able to find the transition point between both phases of stable shapes which is of high interest to ensuing theoretical studies and numerical simulations. Using statistically based thresholds, from our data, we obtain so-called phase diagrams which are compared to manual evaluations. Prospectively, our concept allows us to perform objective analyses of measurements for a variety of flow conditions and to receive comparable results. Moreover, the proposed procedure enables unbiased studies on the influence of drugs on flow properties of single RBCs and the resulting macroscopic change of the flow behavior of whole blood.'),
(89107, 2018, 'plos', 'Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions', 'Brooks, Logan C|Farrow, David C|Hyun, Sangwon|Tibshirani, Ryan J|Rosenfeld, Roni', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 17, 'Centers for Disease Control and Prevention (U.S.)|Communicable Diseases|Epidemics|Forecasting|Humans|Influenza, Human|Models, Biological|Models, Statistical|Public Health|Retrospective Studies|Seasons|United States', 'Journal Article', '10.1371/journal.pcbi.1006134', '29906286', 'Accurate and reliable forecasts of seasonal epidemics of infectious disease can assist in the design of countermeasures and increase public awareness and preparedness. This article describes two main contributions we made recently toward this goal: a novel approach to probabilistic modeling of surveillance time series based on delta densities, and an optimization scheme for combining output from multiple forecasting methods into an adaptively weighted ensemble. Delta densities describe the probability distribution of the change between one observation and the next, conditioned on available data, chaining together nonparametric estimates of these distributions yields a model for an entire trajectory. Corresponding distributional forecasts cover more observed events than alternatives that treat the whole season as a unit, and improve upon multiple evaluation metrics when extracting key targets of interest to public health officials. Adaptively weighted ensembles integrate the results of multiple forecasting methods, such as delta density, using weights that can change from situation to situation. We treat selection of optimal weightings across forecasting methods as a separate estimation task, and describe an estimation procedure based on optimizing cross-validation performance. We consider some details of the data generation process, including data revisions and holiday effects, both in the construction of these forecasting methods and when performing retrospective evaluation. The delta density method and an adaptively weighted ensemble of other forecasting methods each improve significantly on the next best ensemble component when applied separately, and achieve even better cross-validated performance when used in conjunction. We submitted real-time forecasts based on these contributions as part of CDCs 2015/2016 FluSight Collaborative Comparison. Among the fourteen submissions that season, this system was ranked by CDC as the most accurate.'),
(89108, 2018, 'plos', 'Tellurium notebooks-An environment for reproducible dynamical modeling in systems biology', 'Medley, J Kyle|Choi, Kiri|König, Matthias|Smith, Lucian|Gu, Stanley|Hellerstein, Joseph|Sealfon, Stuart C|Sauro, Herbert M', 'Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Institute for Theoretical Biology, Humboldt University of Berlin, Berlin, Germany.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|eScience Institute, University of Washington, Seattle, Washington, United States of America.|Department of Neurology and Center for Advanced Research on Diagnostic Assays Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|Germany|United States|United States|United States|United States|United S', 10, 'Computer Simulation|Humans|Models, Biological|Reproducibility of Results|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006220', '29906293', 'The considerable difficulty encountered in reproducing the results of published dynamical models limits validation, exploration and reuse of this increasingly large biomedical research resource. To address this problem, we have developed Tellurium Notebook, a software system for model authoring, simulation, and teaching that facilitates building reproducible dynamical models and reusing models by 1) providing a notebook environment which allows models, Python code, and narrative to be intermixed, 2) supporting the COMBINE archive format during model development for capturing model information in an exchangeable format and 3) enabling users to easily simulate and edit public COMBINE-compliant models from public repositories to facilitate studying model dynamics, variants and test cases. Tellurium Notebook, a Python-based Jupyter-like environment, is designed to seamlessly inter-operate with these community standards by automating conversion between COMBINE standards formulations and corresponding in-line, human-readable representations. Thus, Tellurium brings to systems biology the strategy used by other literate notebook systems such as Mathematica. These capabilities allow users to edit every aspect of the standards-compliant models and simulations, run the simulations in-line, and re-export to standard formats. We provide several use cases illustrating the advantages of our approach and how it allows development and reuse of models without requiring technical knowledge of standards. Adoption of Tellurium should accelerate model development, reproducibility and reuse.'),
(89109, 2018, 'plos', 'Stochastic shielding and edge importance for Markov chains with timescale separation', 'Schmidt, Deena R|Galán, Roberto F|Thomas, Peter J', 'Department of Mathematics and Statistics, University of Nevada, Reno, Reno, Nevada, United States of America.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, Ohio, United States of America.', 'United States|United States|United States', 2, 'Action Potentials|Algorithms|Computer Simulation|Ion Channel Gating|Kinetics|Markov Chains|Membrane Potentials|Models, Biological|Models, Neurological|Neurons|Normal Distribution|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006206', '29912862', 'Nerve cells produce electrical impulses (spikes) through the coordinated opening and closing of ion channels. Markov processes with voltage-dependent transition rates capture the stochasticity of spike generation at the cost of complex, time-consuming simulations. Schmandt and Galán introduced a novel method, based on the stochastic shielding approximation, as a fast, accurate method for generating approximate sample paths with excellent first and second moment agreement to exact stochastic simulations. We previously analyzed the mathematical basis for the methods remarkable accuracy, and showed that for models with a Gaussian noise approximation, the stationary variance of the occupancy at each vertex in the ion channel state graph could be written as a sum of distinct contributions from each edge in the graph. We extend this analysis to arbitrary discrete population models with first-order kinetics. The resulting decomposition allows us to rank the importance of each edges contribution to the variance of the current under stationary conditions. In most cases, transitions between open (conducting) and closed (non-conducting) states make the greatest contributions to the variance, but there are exceptions. In a 5-state model of the nicotinic acetylcholine receptor, at low agonist concentration, a pair of hidden transitions (between two closed states) makes a greater contribution to the variance than any of the open-closed transitions. We exhaustively investigate this edge importance reversal phenomenon in simplified 3-state models, and obtain an exact formula for the contribution of each edge to the variance of the open state. Two conditions contribute to reversals: the opening rate should be faster than all other rates in the system, and the closed state leading to the opening rate should be sparsely occupied. When edge importance reversal occurs, current fluctuations are dominated by a slow noise component arising from the hidden transitions.'),
(89110, 2018, 'plos', 'Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response', 'Tee, Wei-Ven|Guarnera, Enrico|Berezovsky, Igor N', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.', 'Singapore|Singapore|Singapore', 15, 'Allosteric Regulation|Allosteric Site|Binding Sites|Ligands|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1006228', '29912863', 'The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for traditional orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the reverse perturbation hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the sites structure to an available effector molecule and by the design or selection of an appropriate ligand.'),
(89111, 2018, 'plos', 'Evolutionary dynamics of paroxysmal nocturnal hemoglobinuria', 'Mon Père, Nathaniel|Lenaerts, Tom|Pacheco, Jorge M|Dingli, David', 'Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium.|Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium.|Centro de Biologia Molecular e Ambiental, Universidade do Minho, Braga, Portugal.|Division of Hematology and Department of Molecular Medicine, Mayo Clinic, Rochester, MN, United States of America.', 'Belgium|Belgium|Portugal|United States', 1, 'Clone Cells|Evolution, Molecular|Hematopoiesis|Hematopoietic Stem Cells|Hemoglobinuria|Hemoglobinuria, Paroxysmal|Humans|Membrane Proteins|Models, Biological|Mutation', 'Journal Article', '10.1371/journal.pcbi.1006133', '29912864', 'Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder characterized by hemolysis and a high risk of thrombosis, that is due to a deficiency in several cell surface proteins that prevent complement activation. Its origin has been traced to a somatic mutation in the PIG-A gene within hematopoietic stem cells (HSC). However, to date the question of how this mutant clone expands in size to contribute significantly to hematopoiesis remains under debate. One hypothesis posits the existence of a selective advantage of PIG-A mutated cells due to an immune mediated attack on normal HSC, but the evidence supporting this hypothesis is inconclusive. An alternative (and simpler) explanation attributes clonal expansion to neutral drift, in which case selection neither favours nor inhibits expansion of PIG-A mutated HSC. Here we examine the implications of the neutral drift model by numerically evolving a Markov chain for the probabilities of all possible outcomes, and investigate the possible occurrence and evolution, within this framework, of multiple independently arising clones within the HSC pool. Predictions of the model agree well with the known incidence of the disease and average age at diagnosis. Notwithstanding the slight difference in clonal expansion rates between our results and those reported in the literature, our model results lead to a relative stability of clone size when averaging multiple cases, in accord with what has been observed in human trials. The probability of a patient harbouring a second clone in the HSC pool was found to be extremely low ([Formula: see text]). Thus our results suggest that in clinical cases of PNH where two independent clones of mutant cells are observed, only one of those is likely to have originated in the HSC pool.'),
(89112, 2018, 'plos', 'Evolution of chemokine receptors is driven by mutations in the sodium binding site', 'Taddese, Bruck|Deniaud, Madeline|Garnier, Antoine|Tiss, Asma|Guissouma, Hajer|Abdi, Hervé|Henrion, Daniel|Chabbert, Marie', 'Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.|Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.|Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.|Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.|Laboratoire de Génétique, Immunologie et Pathologies Humaines, Faculté des Sciences de Tunis, Université de Tunis El Manar, Tunis, Tunisie.|The University of Texas at Dallas, School of Behavioral and Brain Sciences, Dallas, Texas, United States of America.|Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.|Laboratoire MITOVASC, UMR CNRS 6015 - INSERM 1083, Université dAngers, Angers, France.', 'France|France|France|France|-|United States|France|France', 7, 'Allosteric Site|Amino Acid Sequence|Binding Sites|Biological Evolution|Chemokines|Computer Simulation|Evolution, Molecular|Humans|Molecular Dynamics Simulation|Mutation|Phylogeny|Principal Component Analysis|Protein Binding|Protein Conformation|Receptors, CCR5|Receptors, CXCR4|Receptors, Chemokine|Signal Transduction|Sodium', 'Journal Article', '10.1371/journal.pcbi.1006209', '29912865', 'Chemokines and their receptors (members of the GPCR super-family) are involved in a wide variety of physiological processes and diseases, thus, understanding the specificity of the chemokine receptor family could help develop new receptor specific drugs. Here, we explore the evolutionary mechanisms that led to the emergence of the chemokine receptors. Based on GPCR hierarchical classification, we analyzed nested GPCR sets with an eigen decomposition approach of the sequence covariation matrix and determined three key residues whose mutation was crucial for the emergence of the chemokine receptors and their subsequent divergence into homeostatic and inflammatory receptors. These residues are part of the allosteric sodium binding site. Their structural and functional roles were investigated by molecular dynamics simulations of CXCR4 and CCR5 as prototypes of homeostatic and inflammatory chemokine receptors, respectively. This study indicates that the three mutations crucial for the evolution of the chemokine receptors dramatically altered the sodium binding mode. In CXCR4, the sodium ion is tightly bound by four protein atoms and one water molecule. In CCR5, the sodium ion is mobile within the binding pocket and moves between different sites involving from one to three protein atoms and two to five water molecules. Analysis of chemokine receptor evolution reveals that a highly constrained sodium binding site characterized most ancient receptors, and that the constraints were subsequently loosened during the divergence of this receptor family. We discuss the implications of these findings for the evolution of the chemokine receptor functions and mechanisms of action.'),
(89113, 2018, 'plos', 'Modeling the functions of condensin in chromosome shaping and segregation', 'Sakai, Yuji|Mochizuki, Atsushi|Kinoshita, Kazuhisa|Hirano, Tatsuya|Tachikawa, Masashi', 'iTHES Research Group, RIKEN, Wako, Japan.|iTHES Research Group, RIKEN, Wako, Japan.|Chromosome Dynamics Laboratory, RIKEN, Wako, Japan.|Chromosome Dynamics Laboratory, RIKEN, Wako, Japan.|iTHES Research Group, RIKEN, Wako, Japan.', 'Japan|Japan|Japan|Japan|Japan', 6, 'Adenosine Triphosphatases|Chromosome Segregation|Chromosomes|Computational Biology|DNA-Binding Proteins|Humans|Models, Genetic|Molecular Dynamics Simulation|Multiprotein Complexes', 'Journal Article', '10.1371/journal.pcbi.1006152', '29912867', 'The mechanistic details underlying the assembly of rod-shaped chromosomes during mitosis and how they segregate from each other to act as individually mobile units remain largely unknown. Here, we construct a coarse-grained physical model of chromosomal DNA and condensins, a class of large protein complexes that plays key roles in these processes. We assume that condensins have two molecular activities: consecutive loop formation in DNA and inter-condensin attractions. Our simulation demonstrates that both of these activities and their balancing acts are essential for the efficient shaping and segregation of mitotic chromosomes. Our results also demonstrate that the shaping and segregation processes are strongly correlated, implying their mechanistic coupling during mitotic chromosome assembly. Our results highlight the functional importance of inter-condensin attractions in chromosome shaping and segregation.'),
(89114, 2018, 'plos', 'Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer', 'Shin, Sung-Young|Müller, Anna-Katharina|Verma, Nandini|Lev, Sima|Nguyen, Lan K', 'Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.|Molecular Cell Biology Department, Weizmann Institute of Science, Rehovot, Israel.|Molecular Cell Biology Department, Weizmann Institute of Science, Rehovot, Israel.|Molecular Cell Biology Department, Weizmann Institute of Science, Rehovot, Israel.|Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.', 'Australia|Israel|Israel|Israel|Australia', 5, 'Antineoplastic Agents|Computational Biology|Databases, Genetic|Drug Synergism|ErbB Receptors|Female|Focal Adhesion Kinase 2|Gene Expression Profiling|Humans|Proto-Oncogene Proteins c-met|Signal Transduction|Triple Negative Breast Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1006192', '29920512', 'Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic values. We have previously showed that the non-receptor tyrosine kinase PYK2 is a downstream effector of EGFR and c-Met and demonstrated their crosstalk signalling in basal-like TNBC. Here we applied a systems modelling approach and developed a mechanistic model of the integrated EGFR-PYK2-c-Met signalling network to identify and prioritize potent drug combinations for TNBC. Model predictions validated by experimental data revealed that among six potential combinations of drug pairs targeting the central nodes of the network, including EGFR, c-Met, PYK2 and STAT3, co-targeting of EGFR and PYK2 and to a lesser extent of EGFR and c-Met yielded strongest synergistic effect. Importantly, the synergy in co-targeting EGFR and PYK2 was linked to switch-like cell proliferation-associated responses. Moreover, simulations of patient-specific models using public gene expression data of TNBC patients led to predictive stratification of patients into subgroups displaying distinct susceptibility to specific drug combinations. These results suggest that mechanistic systems modelling is a powerful approach for the rational design, prediction and prioritization of potent combination therapies for individual patients, thus providing a concrete step towards personalized treatment for TNBC and other tumour types.'),
(89115, 2018, 'plos', 'Community interactions and spatial structure shape selection on antibiotic resistant lineages', 'Estrela, Sylvie|Brown, Sam P', 'Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America.|School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'United States|Georgia', 21, 'Anti-Bacterial Agents|Bacteria|Bacterial Infections|Biofilms|Computational Biology|Drug Resistance, Bacterial|Humans|Microbial Interactions|Models, Biological|Symbiosis', 'Journal Article', '10.1371/journal.pcbi.1006179', '29927925', 'Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.'),
(89116, 2018, 'plos', 'Solving the RNA design problem with reinforcement learning', 'Eastman, Peter|Shi, Jade|Ramsundar, Bharath|Pande, Vijay S', 'Department of Bioengineering, Stanford University, Stanford, CA, United States of America.|Department of Chemistry, Stanford University, Stanford, CA, United States of America.|Department of Computer Science, Stanford University, Stanford, CA, United States of America.|Department of Bioengineering, Stanford University, Stanford, CA, United States of America.', 'United States|United States|United States|United States', 5, 'Algorithms|Computer Simulation|Computer-Aided Design|Learning|Machine Learning|Nucleic Acid Conformation|Problem Solving|RNA|RNA Folding', 'Journal Article', '10.1371/journal.pcbi.1006176', '29927936', 'We use reinforcement learning to train an agent for computational RNA design: given a target secondary structure, design a sequence that folds to that structure in silico. Our agent uses a novel graph convolutional architecture allowing a single model to be applied to arbitrary target structures of any length. After training it on randomly generated targets, we test it on the Eterna100 benchmark and find it outperforms all previous algorithms. Analysis of its solutions shows it has successfully learned some advanced strategies identified by players of the game Eterna, allowing it to solve some very difficult structures. On the other hand, it has failed to learn other strategies, possibly because they were not required for the targets in the training set. This suggests the possibility that future improvements to the training protocol may yield further gains in performance.'),
(89117, 2018, 'plos', 'Control of neurite growth and guidance by an inhibitory cell-body signal', 'Bicknell, Brendan A|Pujic, Zac|Dayan, Peter|Goodhill, Geoffrey J', 'Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.|Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.', 'Australia|Australia|United Kingdom|Australia', 2, 'Computational Biology|Models, Biological|Neurites|Neurogenesis|Neurons|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1006218', '29927943', 'The development of a functional nervous system requires tight control of neurite growth and guidance by extracellular chemical cues. Neurite growth is astonishingly sensitive to shallow concentration gradients, but a widely observed feature of both growth and guidance regulation, with important consequences for development and regeneration, is that both are only elicited over the same relatively narrow range of concentrations. Here we show that all these phenomena can be explained within one theoretical framework. We first test long-standing explanations for the suppression of the trophic effects of nerve growth factor at high concentrations, and find they are contradicted by experiment. Instead we propose a new hypothesis involving inhibitory signalling among the cell bodies, and then extend this hypothesis to show how both growth and guidance can be understood in terms of a common underlying signalling mechanism. This new model for the first time unifies several key features of neurite growth regulation, quantitatively explains many aspects of experimental data, and makes new predictions about unknown details of developmental signalling.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89118, 2018, 'plos', 'Lipidated apolipoprotein E4 structure and its receptor binding mechanism determined by a combined cross-linking coupled to mass spectrometry and molecular dynamics approach', 'Henry, Nicolas|Krammer, Eva-Maria|Stengel, Florian|Adams, Quentin|Van Liefferinge, François|Hubin, Ellen|Chaves, Rui|Efremov, Rouslan|Aebersold, Ruedi|Vandenbussche, Guy|Prévost, Martine|Raussens, Vincent|Deroo, Stéphanie', 'Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Structural Biology Research Center, VIB, Brussels, Belgium.|Structural Biology Research Center, VIB, Brussels, Belgium.|Structural Biology Research Center, VIB, Brussels, Belgium.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.|Center for Structural Biology and Bioinformatics, Structure and Function of Biological Membranes, Faculté des Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium.', 'Belgium|Belgium|Switzerland|Belgium|Belgium|Belgium|Belgium|Belgium|Switzerland|Belgium|Belgium|Belg', 4, 'Apolipoprotein E4|Apolipoproteins E|Humans|Ligands|Lipid Metabolism|Lipids|Mass Spectrometry|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Isoforms', 'Journal Article', '10.1371/journal.pcbi.1006165', '29933361', 'Apolipoprotein E (apoE) is a forefront actor in the transport of lipids and the maintenance of cholesterol homeostasis, and is also strongly implicated in Alzheimers disease. Upon lipid-binding apoE adopts a conformational state that mediates the receptor-induced internalization of lipoproteins. Due to its inherent structural dynamics and the presence of lipids, the structure of the biologically active apoE remains so far poorly described. To address this issue, we developed an innovative hybrid method combining experimental data with molecular modeling and dynamics to generate comprehensive models of the lipidated apoE4 isoform. Chemical cross-linking combined with mass spectrometry provided distance restraints, characterizing the three-dimensional organization of apoE4 molecules at the surface of lipidic nanoparticles. The ensemble of spatial restraints was then rationalized in an original molecular modeling approach to generate monomeric models of apoE4 that advocated the existence of two alternative conformations. These two models point towards an activation mechanism of apoE4 relying on a regulation of the accessibility of its receptor binding region. Further, molecular dynamics simulations of the dimerized and lipidated apoE4 monomeric conformations revealed an elongation of the apoE N-terminal domain, whereby helix 4 is rearranged, together with Arg172, into a proper orientation essential for lipoprotein receptor association. Overall, our results show how apoE4 adapts its conformation for the recognition of the low density lipoprotein receptor and we propose a novel mechanism of activation for apoE4 that is based on accessibility and remodeling of the receptor binding region.'),
(89119, 2018, 'plos', 'Transmission of temporally correlated spike trains through synapses with short-term depression', 'Bird, Alex D|Richardson, Magnus J E', 'Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.|Warwick Mathematics Institute, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom', 2, 'Action Potentials|Animals|Computer Simulation|Humans|Models, Neurological|Neuronal Plasticity|Neurons|Neurotransmitter Agents|Presynaptic Terminals|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1006232', '29933363', 'Short-term synaptic depression, caused by depletion of releasable neurotransmitter, modulates the strength of neuronal connections in a history-dependent manner. Quantifying the statistics of synaptic transmission requires stochastic models that link probabilistic neurotransmitter release with presynaptic spike-train statistics. Common approaches are to model the presynaptic spike train as either regular or a memory-less Poisson process: few analytical results are available that describe depressing synapses when the afferent spike train has more complex, temporally correlated statistics such as bursts. Here we present a series of analytical results-from vesicle release-site occupancy statistics, via neurotransmitter release, to the post-synaptic voltage mean and variance-for depressing synapses driven by correlated presynaptic spike trains. The class of presynaptic drive considered is that fully characterised by the inter-spike-interval distribution and encompasses a broad range of models used for neuronal circuit and network analyses, such as integrate-and-fire models with a complete post-spike reset and receiving sufficiently short-time correlated drive. We further demonstrate that the derived post-synaptic voltage mean and variance allow for a simple and accurate approximation of the firing rate of the post-synaptic neuron, using the exponential integrate-and-fire model as an example. These results extend the level of biological detail included in models of synaptic transmission and will allow for the incorporation of more complex and physiologically relevant firing patterns into future studies of neuronal networks.'),
(89120, 2018, 'plos', 'Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database', 'Zappia, Luke|Phipson, Belinda|Oshlack, Alicia', 'Bioinformatics, Murdoch Childrens Research Institute, Melbourne, Victoria, Australia.|Bioinformatics, Murdoch Childrens Research Institute, Melbourne, Victoria, Australia.|Bioinformatics, Murdoch Childrens Research Institute, Melbourne, Victoria, Australia.', 'Australia|Australia|Australia', 48, 'Base Sequence|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|RNA|RNA, Small Cytoplasmic|Sequence Analysis, RNA|Single-Cell Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1006245', '29939984', 'As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for researchers. In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database (www.scRNA-tools.org) to catalogue and curate analysis tools as they become available. Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform. Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data. We see that many tools perform tasks specific to scRNA-seq analysis, particularly clustering and ordering of cells. We also find that the scRNA-seq community embraces an open-source and open-science approach, with most tools available under open-source licenses and preprints being extensively used as a means to describe methods. The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records the growth of the field over time.'),
(89121, 2018, 'plos', 'Removing contaminants from databases of draft genomes', 'Lu, Jennifer|Salzberg, Steven L', 'Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America.|Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America.', 'United States|United States', 14, 'Bacteria|Computational Biology|DNA Contamination|Databases, Genetic|Genomics|Humans|Metagenome|Metagenomics|Reproducibility of Results|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1006277', '29939994', 'Metagenomic sequencing of patient samples is a very promising method for the diagnosis of human infections. Sequencing has the ability to capture all the DNA or RNA from pathogenic organisms in a human sample. However, complete and accurate characterization of the sequence, including identification of any pathogens, depends on the availability and quality of genomes for comparison. Thousands of genomes are now available, and as these numbers grow, the power of metagenomic sequencing for diagnosis should increase. However, recent studies have exposed the presence of contamination in published genomes, which when used for diagnosis increases the risk of falsely identifying the wrong pathogen. To address this problem, we have developed a bioinformatics system for eliminating contamination as well as low-complexity genomic sequences in the draft genomes of eukaryotic pathogens. We applied this software to identify and remove human, bacterial, archaeal, and viral sequences present in a comprehensive database of all sequenced eukaryotic pathogen genomes. We also removed low-complexity genomic sequences, another source of false positives. Using this pipeline, we have produced a database of clean eukaryotic pathogen genomes for use with bioinformatics classification and analysis tools. We demonstrate that when attempting to find eukaryotic pathogens in metagenomic samples, the new database provides better sensitivity than one using the original genomes while offering a dramatic reduction in false positives.'),
(89122, 2018, 'plos', 'The impact of temporal sampling resolution on parameter inference for biological transport models', 'Harrison, Jonathan U|Baker, Ruth E', 'Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 2, 'Algorithms|Bayes Theorem|Biological Transport|Computer Simulation|Image Processing, Computer-Assisted|Models, Biological|Models, Theoretical|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1006235', '29939995', 'Imaging data has become an essential tool to explore key biological questions at various scales, for example the motile behaviour of bacteria or the transport of mRNA, and it has the potential to transform our understanding of important transport mechanisms. Often these imaging studies require us to compare biological species or mutants, and to do this we need to quantitatively characterise their behaviour. Mathematical models offer a quantitative description of a system that enables us to perform this comparison, but to relate mechanistic mathematical models to imaging data, we need to estimate their parameters. In this work we study how collecting data at different temporal resolutions impacts our ability to infer parameters of biological transport models by performing exact inference for simple velocity jump process models in a Bayesian framework. The question of how best to choose the frequency with which data is collected is prominent in a host of studies because the majority of imaging technologies place constraints on the frequency with which images can be taken, and the discrete nature of observations can introduce errors into parameter estimates. In this work, we mitigate such errors by formulating the velocity jump process model within a hidden states framework. This allows us to obtain estimates of the reorientation rate and noise amplitude for noisy observations of a simple velocity jump process. We demonstrate the sensitivity of these estimates to temporal variations in the sampling resolution and extent of measurement noise. We use our methodology to provide experimental guidelines for researchers aiming to characterise motile behaviour that can be described by a velocity jump process. In particular, we consider how experimental constraints resulting in a trade-off between temporal sampling resolution and observation noise may affect parameter estimates. Finally, we demonstrate the robustness of our methodology to model misspecification, and then apply our inference framework to a dataset that was generated with the aim of understanding the localization of RNA-protein complexes.'),
(89123, 2018, 'plos', 'Age density patterns in patients medical conditions: A clustering approach', 'Alhasoun, Fahad|Aleissa, Faisal|Alhazzani, May|Moyano, Luis G|Pinhanez, Claudio|González, Marta C', 'Center for Computational Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Center for Complex Engineering Systems at KACST and MIT, Cambridge, Massachusetts, United States of America.|Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|IBM Research Labs, Rio de Janeiro, Brazil.|IBM Research Labs, Rio de Janeiro, Brazil.|Center for Computational Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|Brazil|Brazil|United States', 0, 'Age Factors|Algorithms|Brazil|Cluster Analysis|Disease|Epidemiologic Methods|Epidemiology|Female|Humans|International Classification of Diseases|Male|Sex Factors', 'Journal Article', '10.1371/journal.pcbi.1006115', '29944648', 'This paper presents a data analysis framework to uncover relationships between health conditions, age and sex for a large population of patients. We study a massive heterogeneous sample of 1.7 million patients in Brazil, containing 47 million of health records with detailed medical conditions for visits to medical facilities for a period of 17 months. The findings suggest that medical conditions can be grouped into clusters that share very distinctive densities in the ages of the patients. For each cluster, we further present the ICD-10 chapters within it. Finally, we relate the findings to comorbidity networks, uncovering the relation of the discovered clusters of age densities to comorbidity networks literature.'),
(89124, 2018, 'plos', 'Correction: A Mixture of Delta-Rules Approximation to Bayesian Inference in Change-Point Problems', 'Wilson, Robert C|Nassar, Matthew R|Tavoni, Gaia|Gold, Joshua I', 'Department of Psychology and Cognitive Science Program, University of Arizona, Tucson, Arizona, United States of America.|Department of Psychology, Brown University, Providence, Rhode Island, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006210', '29944654', '[This corrects the article DOI: 10.1371/journal.pcbi.1003150.].'),
(89125, 2018, 'plos', 'Thalamocortical and intracortical laminar connectivity determines sleep spindle properties', 'Krishnan, Giri P|Rosen, Burke Q|Chen, Jen-Yung|Muller, Lyle|Sejnowski, Terrence J|Cash, Sydney S|Halgren, Eric|Bazhenov, Maxim', 'Department of Medicine, University of California, San Diego, La Jolla, CA, United States of America.|Departments of Radiology and Neurosciences, UCSD, San Diego, CA, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, CA, United States of America.|Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, San Diego, CA, United States of America.|Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, San Diego, CA, United States of America.|Dept. of Neurology, Massachusetts General Hospital and Harvard University, Boston, MA, United States of America.|Departments of Radiology and Neurosciences, UCSD, San Diego, CA, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, CA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 2, 'Adult|Cerebral Cortex|Computer Simulation|Connectome|Electroencephalography|Female|Healthy Volunteers|Humans|Magnetoencephalography|Male|Memory Consolidation|Neurons|Sleep|Sleep Stages|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1006171', '29949575', 'Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.'),
(89126, 2018, 'plos', 'Two critical positions in zinc finger domains are heavily mutated in three human cancer types', 'Munro, Daniel|Ghersi, Dario|Singh, Mona', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.', 'United States|United States|United States', 7, 'Adenomatous Polyposis Coli|Amino Acid Sequence|Binding Sites|CYS2-HIS2 Zinc Fingers|DNA|DNA-Binding Proteins|Female|Humans|Male|Neoplasms|Repressor Proteins|Sequence Homology, Amino Acid|Skin Neoplasms|Transcription Factors|Uterine Neoplasms|Zinc Fingers', 'Journal Article', '10.1371/journal.pcbi.1006290', '29953437', 'A major goal of cancer genomics is to identify somatic mutations that play a role in tumor initiation or progression. Somatic mutations within transcription factors are of particular interest, as gene expression dysregulation is widespread in cancers. The substantial gene expression variation evident across tumors suggests that numerous regulatory factors are likely to be involved and that somatic mutations within them may not occur at high frequencies across patient cohorts, thereby complicating efforts to uncover which ones are cancer-relevant. Here we analyze somatic mutations within the largest family of human transcription factors, namely those that bind DNA via Cys2His2 zinc finger domains. Specifically, to hone in on important mutations within these genes, we aggregated somatic mutations across all of them by their positions within Cys2His2 zinc finger domains. Remarkably, we found that for three classes of cancers profiled by The Cancer Genome Atlas (TCGA)-Uterine Corpus Endometrial Carcinoma, Colon and Rectal Adenocarcinomas, and Skin Cutaneous Melanoma-two specific, functionally important positions within zinc finger domains are mutated significantly more often than expected by chance, with alterations in 18%, 10% and 43% of tumors, respectively. Numerous zinc finger genes are affected, with those containing Krüppel-associated box (KRAB) repressor domains preferentially targeted by these mutations. Further, the genes with these mutations also have high overall missense mutation rates, are expressed at levels comparable to those of known cancer genes, and together have biological process annotations that are consistent with roles in cancers. Altogether, we introduce evidence broadly implicating mutations within a diverse set of zinc finger proteins as relevant for cancer, and propose that they contribute to the widespread transcriptional dysregulation observed in cancer cells.'),
(89127, 2018, 'plos', 'Computation predicts rapidly adapting mechanotransduction currents cannot account for tactile encoding in Merkel cell-neurite complexes', 'Gerling, Gregory J|Wan, Lingtian|Hoffman, Benjamin U|Wang, Yuxiang|Lumpkin, Ellen A', 'Department of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Medical Scientist Training Program, Columbia University College of Physicians & Surgeons, New York, New York, United States of America.|Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Physiology & Cellular Biophysics, Columbia University College of Physicians & Surgeons, New York, New York, United States of America.', 'United States|United States|United States|United States|United States', 1, 'Action Potentials|Computational Biology|Computer Simulation|Mechanoreceptors|Mechanotransduction, Cellular|Merkel Cells|Neurites|Neurons, Afferent|Sensory Receptor Cells|Skin|Touch', 'Journal Article', '10.1371/journal.pcbi.1006264', '29958280', 'Distinct firing properties among touch receptors are influenced by multiple, interworking anatomical structures. Our understanding of the functions and crosstalk of Merkel cells and their associated neurites-the end organs of slowly adapting type I (SAI) afferents-remains incomplete. Piezo2 mechanically activated channels are required both in Merkel cells and in sensory neurons for canonical SAI responses in rodents, however, a central unanswered question is how rapidly inactivating currents give rise to sustained action potential volleys in SAI afferents. The computational model herein synthesizes mechanotransduction currents originating from Merkel cells and neurites, in context of skin mechanics and neural dynamics. Its goal is to mimic distinct spike firing patterns from wildtype animals, as well as Atoh1 knockout animals that completely lack Merkel cells. The developed generator function includes a Merkel cell mechanism that represents its mechanotransduction currents and downstream voltage-activated conductances (slower decay of current) and a neurite mechanism that represents its mechanotransduction currents (faster decay of current). To mimic sustained firing in wildtype animals, a longer time constant was needed than the 200 ms observed for mechanically activated membrane depolarizations in rodent Merkel cells. One mechanism that suffices is to introduce an ultra-slowly inactivating current, with a time constant on the order of 1.7 s. This mechanism may drive the slow adaptation of the sustained response, for which the skins viscoelastic relaxation cannot account. Positioned within the sensory neuron, this source of current reconciles the physiology and anatomical characteristics of Atoh1 knockout animals.'),
(89128, 2018, 'plos', 'A dual regulation mechanism of histidine kinase CheA identified by combining network-dynamics modeling and system-level input-output data', 'Mello, Bernardo A|Pan, Wenlin|Hazelbauer, Gerald L|Tu, Yuhai', 'IBM T. J. Watson Research Center, Yorktown Heights, New York, United States of America.|Department of Biochemistry, University of Missouri, Columbia, Missouri, United States of America.|Department of Biochemistry, University of Missouri, Columbia, Missouri, United States of America.|IBM T. J. Watson Research Center, Yorktown Heights, New York, United States of America.', 'United States|United States|United States|United States', 7, 'Adenosine Triphosphate|Biochemical Phenomena|Chemotaxis|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Histidine Kinase|Kinetics|Methyl-Accepting Chemotaxis Proteins|Models, Biological|Protein Binding|Signal Transduction|Substrate Specificity|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006305', '29965962', 'It is challenging to decipher molecular mechanisms in biological systems from system-level input-output data, especially for complex processes that involve interactions among multiple components. We addressed this general problem for the bacterial histidine kinase CheA, the activity of which is regulated in chemotaxis signaling complexes by bacterial chemoreceptors. We developed a general network model to describe the dynamics of the system, treating the receptor complex with coupling protein CheW and the P3P4P5 domains of kinase CheA as a regulated enzyme with two substrates, ATP and P1, the phosphoryl-accepting domain of CheA. Our simple network model allowed us to search hypothesis space systematically. For different and progressively more complex regulation schemes, we fit our models to a large set of input-output data with the aim of identifying the simplest possible regulation mechanisms consistent with the data. Our modeling and analysis revealed novel dual regulation mechanisms in which receptor activity regulated ATP binding plus one other process, either P1 binding or phosphoryl transfer between P1 and ATP. Strikingly, in our models receptor control affected the kinetic rate constants of substrate association and dissociation equally and thus did not alter the respective equilibrium constants. We suggest experiments that could distinguish between the two dual-regulation mechanisms. This systems-biology approach of combining modeling and a large input-output dataset should be applicable for studying other complex biological processes.'),
(89129, 2018, 'plos', 'Post-Turing tissue pattern formation: Advent of mechanochemistry', 'Brinkmann, Felix|Mercker, Moritz|Richter, Thomas|Marciniak-Czochra, Anna', 'Institute of Applied Mathematics, BioQuant and Interdisciplinary Center of Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.|Institute of Applied Mathematics, BioQuant and Interdisciplinary Center of Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.|Magdeburg University, Institute for Analysis and Numerics, Magdeburg, Germany.|Institute of Applied Mathematics, BioQuant and Interdisciplinary Center of Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany', 10, 'Animals|Biomechanical Phenomena|Body Patterning|Chemical Phenomena|Computer Simulation|Embryonic Development|Feedback, Physiological|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006259', '29969460', 'Chemical and mechanical pattern formation is fundamental during embryogenesis and tissue development. Yet, the underlying molecular and cellular mechanisms are still elusive in many cases. Most current theories assume that tissue development is driven by chemical processes: either as a sequence of chemical patterns each depending on the previous one, or by patterns spontaneously arising from specific chemical interactions (such as Turing-patterns). Within both theories, mechanical patterns are usually regarded as passive by-products of chemical pre-patters. However, several experiments question these theories, and an increasing number of studies shows that tissue mechanics can actively influence chemical patterns during development. In this study, we thus focus on the interplay between chemical and mechanical processes during tissue development. On one hand, based on recent experimental data, we develop new mechanochemical simulation models of evolving tissues, in which the full 3D representation of the tissue appears to be critical for obtaining a realistic mechanochemical behaviour. The presented modelling approach is flexible and numerically studied using state of the art finite element methods. Thus, it may serve as a basis to combine simulations with new experimental methods in tissue development. On the other hand, we apply the developed approach and demonstrate that even simple interactions between tissue mechanics and chemistry spontaneously lead to robust and complex mechanochemical patterns. Especially, we demonstrate that the main contradictions arising in the framework of purely chemical theories are naturally and automatically resolved using the mechanochemical patterning theory.'),
(89130, 2018, 'plos', 'COBRAme: A computational framework for genome-scale models of metabolism and gene expression', 'Lloyd, Colton J|Ebrahim, Ali|Yang, Laurence|King, Zachary A|Catoiu, Edward|OBrien, Edward J|Liu, Joanne K|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, United States of America.|Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 11, 'Algorithms|Computer Simulation|Gene Expression|Genome|Metabolism|Models, Genetic|Software Design', 'Journal Article', '10.1371/journal.pcbi.1006302', '29975681', 'Genome-scale models of metabolism and macromolecular expression (ME-models) explicitly compute the optimal proteome composition of a growing cell. ME-models expand upon the well-established genome-scale models of metabolism (M-models), and they enable a new fundamental understanding of cellular growth. ME-models have increased predictive capabilities and accuracy due to their inclusion of the biosynthetic costs for the machinery of life, but they come with a significant increase in model size and complexity. This challenge results in models which are both difficult to compute and challenging to understand conceptually. As a result, ME-models exist for only two organisms (Escherichia coli and Thermotoga maritima) and are still used by relatively few researchers. To address these challenges, we have developed a new software framework called COBRAme for building and simulating ME-models. It is coded in Python and built on COBRApy, a popular platform for using M-models. COBRAme streamlines computation and analysis of ME-models. It provides tools to simplify constructing and editing ME-models to enable ME-model reconstructions for new organisms. We used COBRAme to reconstruct a condensed E. coli ME-model called iJL1678b-ME. This reformulated model gives functionally identical solutions to previous E. coli ME-models while using 1/6 the number of free variables and solving in less than 10 minutes, a marked improvement over the 6 hour solve time of previous ME-model formulations. Errors in previous ME-models were also corrected leading to 52 additional genes that must be expressed in iJL1678b-ME to grow aerobically in glucose minimal in silico media. This manuscript outlines the architecture of COBRAme and demonstrates how ME-models can be created, modified, and shared most efficiently using the new software framework.'),
(89131, 2018, 'plos', 'Paxillin phosphorylation at serine 273 and its effects on Rac, Rho and adhesion dynamics', 'Tang, Kaixi|Boudreau, Colton G|Brown, Claire M|Khadra, Anmar', 'Department of Physiology, McGill University, Montreal, Quxc3xa9bec, Canada.|Department of Physiology, McGill University, Montreal, Quxc3xa9bec, Canada.|Department of Physiology, McGill University, Montreal, Quxc3xa9bec, Canada.|Department of Physiology, McGill University, Montreal, Quxc3xa9bec, Canada.', 'Canada|Canada|Canada|Canada', 2, 'Animals|CHO Cells|Cell Movement|Cell Polarity|Cricetulus|Cytoskeletal Proteins|Enzyme Activation|Enzyme Inhibitors|Focal Adhesions|Models, Biological|Okadaic Acid|Paxillin|Phosphorylation|Serine|Signal Transduction|p21-Activated Kinases|rac GTP-Binding Proteins|rho GTP-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1006303', '29975690', 'Focal adhesions are protein complexes that anchor cells to the extracellular matrix. During migration, the growth and disassembly of these structures are spatiotemporally regulated, with new adhesions forming at the leading edge of the cell and mature adhesions disassembling at the rear. Signalling proteins and structural cytoskeletal components tightly regulate adhesion dynamics. Paxillin, an adaptor protein within adhesions, is one of these proteins. Its phosphorylation at serine 273 (S273) is crucial for maintaining fast adhesion assembly and disassembly. Paxillin is known to bind to a GIT1-xcexb2PIX-PAK1 complex, which increases the local activation of the small GTPase Rac. To understand quantitatively the behaviour of this system and how it relates to adhesion assembly/disassembly, we developed a mathematical model describing the dynamics of the small GTPases Rac and Rho as determined by paxillin S273 phosphorylation. Our model revealed that the system possesses bistability, where switching between uninduced (active Rho) and induced (active Rac) states can occur through a change in rate of paxillin phosphorylation or PAK1 activation. The bistable switch is characterized by the presence of memory, minimal change in the levels of active Rac and Rho within the induced and uninduced states, respectively, and the limited regime of monostability associated with the uninduced state. These results were validated experimentally by showing the presence of bimodality in adhesion assembly and disassembly rates, and demonstrating that Rac activity increases after treating Chinese Hamster Ovary cells with okadaic acid (a paxillin phosphatase inhibitor), followed by a modest recovery after 20 min washout. Spatial gradients of phosphorylated paxillin in a reaction-diffusion model gave rise to distinct regions of Rac and Rho activities, resembling polarization of a cell into front and rear. Perturbing several parameters of the model also revealed important insights into how signalling components upstream and downstream of paxillin phosphorylation affect dynamics.'),
(89132, 2018, 'plos', 'Subgraphs of functional brain networks identify dynamical constraints of cognitive control', 'Khambhati, Ankit N|Medaglia, John D|Karuza, Elisabeth A|Thompson-Schill, Sharon L|Bassett, Danielle S', 'Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, Drexel University, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Adult|Brain|Brain Mapping|Cognition|Female|Humans|Machine Learning|Magnetic Resonance Imaging|Male|Nerve Net|Perception|Stroop Test|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006234', '29979673', 'Brain anatomy and physiology support the human ability to navigate a complex space of perceptions and actions. To maneuver across an ever-changing landscape of mental states, the brain invokes cognitive control-a set of dynamic processes that engage and disengage different groups of brain regions to modulate attention, switch between tasks, and inhibit prepotent responses. Current theory posits that correlated and anticorrelated brain activity may signify cooperative and competitive interactions between brain areas that subserve adaptive behavior. In this study, we use a quantitative approach to identify distinct topological motifs of functional interactions and examine how their expression relates to cognitive control processes and behavior. In particular, we acquire fMRI BOLD signal in twenty-eight healthy subjects as they perform two cognitive control tasks-a Stroop interference task and a local-global perception switching task using Navon figures-each with low and high cognitive control demand conditions. Based on these data, we construct dynamic functional brain networks and use a parts-based, network decomposition technique called non-negative matrix factorization to identify putative cognitive control subgraphs whose temporal expression captures distributed network structures involved in different phases of cooperative and competitive control processes. Our results demonstrate that temporal expression of the subgraphs fluctuate alongside changes in cognitive demand and are associated with individual differences in task performance. These findings offer insight into how coordinated changes in the cooperative and competitive roles of cognitive systems map trajectories between cognitively demanding brain states.'),
(89133, 2018, 'plos', 'Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagation', 'Setareh, Hesam|Deger, Moritz|Gerstner, Wulfram', 'School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Switzerland.|School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Switzerland.|School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 1, 'Action Potentials|Animals|Brain|Mice|Models, Neurological|Nerve Net|Neurons|Somatosensory Cortex|Synaptic Potentials|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1006216', '29979674', 'The time scale of neuronal network dynamics is determined by synaptic interactions and neuronal signal integration, both of which occur on the time scale of milliseconds. Yet many behaviors like the generation of movements or vocalizations of sounds occur on the much slower time scale of seconds. Here we ask the question of how neuronal networks of the brain can support reliable behavior on this time scale. We argue that excitable neuronal assemblies with spike-frequency adaptation may serve as building blocks that can flexibly adjust the speed of execution of neural circuit function. We show in simulations that a chain of neuronal assemblies can propagate signals reliably, similar to the well-known synfire chain, but with the crucial difference that the propagation speed is slower and tunable to the behaviorally relevant range. Moreover we study a grid of excitable neuronal assemblies as a simplified model of the somatosensory barrel cortex of the mouse and demonstrate that various patterns of experimentally observed spatial activity propagation can be explained.'),
(89134, 2018, 'plos', 'A local uPAR-plasmin-TGFxcexb21 positive feedback loop in a qualitative computational model of angiogenic sprouting explains the in vitro effect of fibrinogen variants', 'Boas, Sonja E M|Carvalho, Joao|van den Broek, Marloes|Weijers, Ester M|Goumans, Marie-Josxc3xa9|Koolwijk, Pieter|Merks, Roeland M H', 'Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands.|Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands.|Amsterdam Cardiovascular Sciences, VU University medical Center, Dept. of Physiology, Amsterdam, The Netherlands.|Amsterdam Cardiovascular Sciences, VU University medical Center, Dept. of Physiology, Amsterdam, The Netherlands.|Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands.|Amsterdam Cardiovascular Sciences, VU University medical Center, Dept. of Physiology, Amsterdam, The Netherlands.|Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Biological Availability|Cell Movement|Cells, Cultured|Computer Simulation|Endothelial Cells|Endothelium, Vascular|Extracellular Matrix|Fibrin|Fibrinogen|Fibrinolysin|Fibrinolysis|Humans|In Vitro Techniques|Molecular Weight|Neovascularization, Physiologic|Proteolysis|Receptors, Urokinase Plasminogen Activator|Reproducibility of Results|Transforming Growth Factor beta1', 'Journal Article', '10.1371/journal.pcbi.1006239', '29979675', 'In experimental assays of angiogenesis in three-dimensional fibrin matrices, a temporary scaffold formed during wound healing, the type and composition of fibrin impacts the level of sprouting. More sprouts form on high molecular weight (HMW) than on low molecular weight (LMW) fibrin. It is unclear what mechanisms regulate the number and the positions of the vascular-like structures in cell cultures. To address this question, we propose a mechanistic simulation model of endothelial cell migration and fibrin proteolysis by the plasmin system. The model is a hybrid, cell-based and continuum, computational model based on the cellular Potts model and sets of partial-differential equations. Based on the model results, we propose that a positive feedback mechanism between uPAR, plasmin and transforming growth factor xcexb21 (TGFxcexb21) selects cells in the monolayer for matrix invasion. Invading cells releases TGFxcexb21 from the extracellular matrix through plasmin-mediated fibrin degradation. The activated TGFxcexb21 further stimulates fibrin degradation and keeps proteolysis active as the sprout invades the fibrin matrix. The binding capacity for TGFxcexb21 of LMW is reduced relative to that of HMW. This leads to reduced activation of proteolysis and, consequently, reduced cell ingrowth in LMW fibrin compared to HMW fibrin. Thus our model predicts that endothelial cells in LMW fibrin matrices compared to HMW matrices show reduced sprouting due to a lower bio-availability of TGFxcexb21.'),
(89135, 2018, 'plos', 'Unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles using a novel dissimilarity measure', 'Grossberger, Lukas|Battaglia, Francesco P|Vinck, Martin', 'Donders Institute for Brain, Cognition and Behaviour, Radboud Universiteit, Nijmegen, the Netherlands.|Donders Institute for Brain, Cognition and Behaviour, Radboud Universiteit, Nijmegen, the Netherlands.|Ernst Strüngmann Institute for Neuroscience in cooperation with Max Planck Society, Frankfurt am Main, Germany.', 'Netherlands|Netherlands|Germany', 0, 'Action Potentials|Algorithms|Animals|Cerebral Cortex|Cluster Analysis|Macaca mulatta|Male|Models, Neurological|Neuronal Plasticity|Neurons|Photic Stimulation|Signal-To-Noise Ratio|Systems Biology|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1006283', '29979681', 'Temporally ordered multi-neuron patterns likely encode information in the brain. We introduce an unsupervised method, SPOTDisClust (Spike Pattern Optimal Transport Dissimilarity Clustering), for their detection from high-dimensional neural ensembles. SPOTDisClust measures similarity between two ensemble spike patterns by determining the minimum transport cost of transforming their corresponding normalized cross-correlation matrices into each other (SPOTDis). Then, it performs density-based clustering based on the resulting inter-pattern dissimilarity matrix. SPOTDisClust does not require binning and can detect complex patterns (beyond sequential activation) even when high levels of out-of-pattern noise spiking are present. Our method handles efficiently the additional information from increasingly large neuronal ensembles and can detect a number of patterns that far exceeds the number of recorded neurons. In an application to neural ensemble data from macaque monkey V1 cortex, SPOTDisClust can identify different moving stimulus directions on the sole basis of temporal spiking patterns.'),
(89136, 2018, 'plos', 'Age-dependent Pavlovian biases influence motor decision-making', 'Chen, Xiuli|Rutledge, Robb B|Brown, Harriet R|Dolan, Raymond J|Bestmann, Sven|Galea, Joseph M', 'School of Psychology, University of Birmingham, Birmingham, United Kingdom.|Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.|Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.|Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.|Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.|School of Psychology, University of Birmingham, Birmingham, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Adolescent|Adult|Aged|Aging|Choice Behavior|Computer Simulation|Conditioning, Classical|Decision Making|Female|Humans|Male|Middle Aged|Mobile Applications|Motor Activity|Punishment|Reward|Task Performance and Analysis|Video Games', 'Journal Article', '10.1371/journal.pcbi.1006304', '29979685', 'Motor decision-making is an essential component of everyday life which requires weighing potential rewards and punishments against the probability of successfully executing an action. To achieve this, humans rely on two key mechanisms, a flexible, instrumental, value-dependent process and a hardwired, Pavlovian, value-independent process. In economic decision-making, age-related decline in risk taking is explained by reduced Pavlovian biases that promote action toward reward. Although healthy ageing has also been associated with decreased risk-taking in motor decision-making, it is currently unknown whether this is a result of changes in Pavlovian biases, instrumental processes or a combination of both. Using a newly established approach-avoidance computational model together with a novel app-based motor decision-making task, we measured sensitivity to reward and punishment when participants (n = 26,532) made a go/no-go motor gamble based on their perceived ability to execute a complex action. We show that motor decision-making can be better explained by a model with both instrumental and Pavlovian parameters, and reveal age-related changes across punishment- and reward-based instrumental and Pavlovian processes. However, the most striking effect of ageing was a decrease in Pavlovian attraction towards rewards, which was associated with a reduction in optimality of choice behaviour. In a subset of participants who also played an independent economic decision-making task (n = 17,220), we found similar decision-making tendencies for motor and economic domains across a majority of age groups. Pavlovian biases, therefore, play an important role in not only explaining motor decision-making behaviour but also the changes which occur through normal ageing. This provides a deeper understanding of the mechanisms which shape motor decision-making across the lifespan.'),
(89137, 2018, 'plos', 'Correction: A mechanistic pan-cancer pathway model informed by multi-omics data interprets stochastic cell fate responses to drugs and mitogens', 'PLOS Computational Biology Staff', 'School of Psychology, University of Birmingham, Birmingham, United Kingdom.', 'United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006189', '29985911', '[This corrects the article DOI: 10.1371/journal.pcbi.1005985.].');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89138, 2018, 'plos', 'The importance of mechanical constraints for proper polarization and psuedo-cleavage furrow generation in the early Caenorhabditis elegans embryo', 'Aras, Betül Senay|Zhou, Y C|Dawes, Adriana|Chou, Ching-Shan', 'Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.|Department of Mathematics, Colorado State University, Fort Collins, Colorado, United States of America.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.', 'United States|United States|United States|United States', 1, 'Actin Cytoskeleton|Actomyosin|Animals|Biochemical Phenomena|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Cell Polarity|Cell Shape|Embryo, Nonmammalian|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1006294', '29985915', 'Intracellular polarization, where a cell specifies a spatial axis by segregation of specific factors, is a fundamental biological process. In the early embryo of the nematode worm Caenorhabditis elegans (C. elegans), polarization is often accompanied by deformations of the cortex, a highly contractile structure consisting of actin filaments cross-linked by the motor protein myosin (actomyosin). It has been suggested that the eggshell surrounding the early embryo plays a role in polarization although its function is not understood. Here we develop a mathematical model which couples a reaction-diffusion model of actomyosin dynamics with a phase field model of the cell cortex to implicitly track cell shape changes in the early C. elegans embryo. We investigate the potential rigidity effect of the geometric constraint imposed by the presence and size of the eggshell on polarization dynamics. Our model suggests that the geometric constraint of the eggshell is essential for proper polarization and the size of the eggshell also affects the dynamics of polarization. Therefore, we conclude that geometric constraint on a cell might affect the dynamics of a biochemical process.'),
(89139, 2018, 'plos', 'Gain control with A-type potassium current: IA as a switch between divisive and subtractive inhibition', 'Goldwyn, Joshua H|Slabe, Bradley R|Travers, Joseph B|Terman, David', 'Department of Mathematics and Statistics, Swarthmore College, Swarthmore, Pennsylvania, United States of America.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.|Division of Biosciences, College of Dentistry, The Ohio State University, Columbus, Ohio, United States of America.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.', 'United States|United States|United States|United States', 0, 'Action Potentials|Animals|Models, Neurological|Neural Inhibition|Neuronal Plasticity|Neurons|Poisson Distribution|Potassium Channels, Voltage-Gated|Solitary Nucleus|Synapses|Synaptic Potentials', 'Journal Article', '10.1371/journal.pcbi.1006292', '29985917', 'Neurons process and convey information by transforming barrages of synaptic inputs into spiking activity. Synaptic inhibition typically suppresses the output firing activity of a neuron, and is commonly classified as having a subtractive or divisive effect on a neurons output firing activity. Subtractive inhibition can narrow the range of inputs that evoke spiking activity by eliminating responses to non-preferred inputs. Divisive inhibition is a form of gain control: it modifies firing rates while preserving the range of inputs that evoke firing activity. Since these two modes of inhibition have distinct impacts on neural coding, it is important to understand the biophysical mechanisms that distinguish these response profiles. In this study, we use simulations and mathematical analysis of a neuron model to find the specific conditions (parameter sets) for which inhibitory inputs have subtractive or divisive effects. Significantly, we identify a novel role for the A-type Potassium current (IA). In our model, this fast-activating, slowly-inactivating outward current acts as a switch between subtractive and divisive inhibition. In particular, if IA is strong (large maximal conductance) and fast (activates on a time-scale similar to spike initiation), then inhibition has a subtractive effect on neural firing. In contrast, if IA is weak or insufficiently fast-activating, then inhibition has a divisive effect on neural firing. We explain these findings using dynamical systems methods (plane analysis and fast-slow dissection) to define how a spike threshold condition depends on synaptic inputs and IA. Our findings suggest that neurons can self-regulate the gain control effects of inhibition via combinations of synaptic plasticity and/or modulation of the conductance and kinetics of A-type Potassium channels. This novel role for IA would add flexibility to neurons and networks, and may relate to recent observations of divisive inhibitory effects on neurons in the nucleus of the solitary tract.'),
(89140, 2018, 'plos', 'Differential roles of sleep spindles and sleep slow oscillations in memory consolidation', 'Wei, Yina|Krishnan, Giri P|Komarov, Maxim|Bazhenov, Maxim', 'Department of Medicine, University of California at San Diego, La Jolla, CA, United States of America.|Department of Medicine, University of California at San Diego, La Jolla, CA, United States of America.|Department of Medicine, University of California at San Diego, La Jolla, CA, United States of America.|Department of Medicine, University of California at San Diego, La Jolla, CA, United States of America.', 'United States|United States|United States|United States', 13, 'Action Potentials|Animals|Biophysical Phenomena|Cerebral Cortex|Computer Simulation|Electroencephalography|Humans|Memory Consolidation|Neuronal Plasticity|Neurotransmitter Agents|Sleep Stages|Sleep, REM|Thalamus|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1006322', '29985966', 'Sleep plays an important role in the consolidation of recent memories. However, the cellular and synaptic mechanisms of consolidation during sleep remain poorly understood. In this study, using a realistic computational model of the thalamocortical network, we tested the role of Non-Rapid Eye Movement (NREM) sleep in memory consolidation. We found that sleep spindles (the hallmark of N2 stage sleep) and slow oscillations (the hallmark of N3 stage sleep) both promote replay of the spike sequences learned in the awake state and replay was localized at the trained network locations. Memory performance improved after a period of NREM sleep but not after the same time period in awake. When multiple memories were trained, the local nature of the spike sequence replay during spindles allowed replay of the distinct memory traces independently, while slow oscillations promoted competition that could prevent replay of the weak memories in a presence of the stronger memory traces. This could lead to extinction of the weak memories unless when sleep spindles (N2 sleep) preceded slow oscillations (N3 sleep), as observed during the natural sleep cycle. Our study presents a mechanistic explanation for the role of sleep rhythms in memory consolidation and proposes a testable hypothesis how the natural structure of sleep stages provides an optimal environment to consolidate memories.'),
(89141, 2018, 'plos', 'Phase-lags in large scale brain synchronization: Methodological considerations and in-silico analysis', 'Petkoski, Spase|Palva, J Matias|Jirsa, Viktor K', 'Aix-Marseille Universitxc3xa9, Inserm, INS UMR_S 1106, Marseille, France.|Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.|Aix-Marseille Universitxc3xa9, Inserm, INS UMR_S 1106, Marseille, France.', 'France|Finland|France', 20, 'Brain|Computer Simulation|Connectome|Cortical Synchronization|Humans|Models, Neurological|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1006160', '29990339', 'Architecture of phase relationships among neural oscillations is central for their functional significance but has remained theoretically poorly understood. We use phenomenological model of delay-coupled oscillators with increasing degree of topological complexity to identify underlying principles by which the spatio-temporal structure of the brain governs the phase lags between oscillatory activity at distant regions. Phase relations and their regions of stability are derived and numerically confirmed for two oscillators and for networks with randomly distributed or clustered bimodal delays, as a first approximation for the brain structural connectivity. Besides in-phase, clustered delays can induce anti-phase synchronization for certain frequencies, while the sign of the lags is determined by the natural frequencies and by the inhomogeneous network interactions. For in-phase synchronization faster oscillators always phase lead, while stronger connected nodes lag behind the weaker during frequency depression, which consistently arises for in-silico results. If nodes are in anti-phase regime, then a distance xcfx80 is added to the in-phase trends. The statistics of the phases is calculated from the phase locking values (PLV), as in many empirical studies, and we scrutinize the methods impact. The choice of surrogates do not affects the mean of the observed phase lags, but higher significance levels that are generated by some surrogates, cause decreased variance and might fail to detect the generally weaker coherence of the interhemispheric links. These links are also affected by the non-stationary and intermittent synchronization, which causes multimodal phase lags that can be misleading if averaged. Taken together, the results describe quantitatively the impact of the spatio-temporal connectivity of the brain to the synchronization patterns between brain regions, and to uncover mechanisms through which the spatio-temporal structure of the brain renders phases to be distributed around 0 and xcfx80.'),
(89142, 2018, 'plos', 'Information-theoretic analysis of realistic odor plumes: What cues are useful for determining location?', 'Boie, Sebastian D|Connor, Erin G|McHugh, Margaret|Nagel, Katherine I|Ermentrout, G Bard|Crimaldi, John P|Victor, Jonathan D', 'Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York, United States of America.|Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, Colorado, United States of America.|Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, Colorado, United States of America.|Department of Neuroscience & Physiology, NYU Langone Medical Center, New York, New York, United States of America.|Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, Colorado, United States of America.|Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Behavior, Animal|Cues|Fluorescence|Information Theory|Odorants|Olfactory Receptor Neurons|Smell|Spatial Navigation', 'Journal Article', '10.1371/journal.pcbi.1006275', '29990365', 'Many species rely on olfaction to navigate towards food sources or mates. Olfactory navigation is a challenging task since odor environments are typically turbulent. While time-averaged odor concentration varies smoothly with the distance to the source, instaneous concentrations are intermittent and obtaining stable averages takes longer than the typical intervals between animals navigation decisions. How to effectively sample from the odor distribution to determine sampling location is the focus in this article. To investigate which sampling strategies are most informative about the location of an odor source, we recorded three naturalistic stimuli with planar lased-induced fluorescence and used an information-theoretic approach to quantify the information that different sampling strategies provide about sampling location. Specifically, we compared multiple sampling strategies based on a fixed number of coding bits for encoding the olfactory stimulus. When the coding bits were all allocated to representing odor concentration at a single sensor, information rapidly saturated. Using the same number of coding bits in two sensors provides more information, as does coding multiple samples at different times. When accumulating multiple samples at a fixed location, the temporal sequence does not yield a large amount of information and can be averaged with minimal loss. Furthermore, we show that histogram-equalization is not the most efficient way to use coding bits when using the olfactory sample to determine location.'),
(89143, 2018, 'plos', 'Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection', 'Venugopal, Vishnu|Padmanabhan, Pranesh|Raja, Rubesh|Dixit, Narendra M', 'Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.|Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.|Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.|Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.', 'India|India|India|India', 3, 'Antiviral Agents|Drug Resistance, Viral|Hepacivirus|Hepatitis C, Chronic|Humans|Interferon-alpha|Models, Biological|Point Mutation|Treatment Outcome|Viral Proteins|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1006335', '30001324', 'Direct-acting antiviral agents (DAAs) for hepatitis C treatment tend to fare better in individuals who are also likely to respond well to interferon-alpha (IFN), a surprising correlation given that DAAs target specific viral proteins whereas IFN triggers a generic antiviral immune response. Here, we posit a causal relationship between IFN-responsiveness and DAA treatment outcome. IFN-responsiveness restricts viral replication, which would prevent the growth of viral variants resistant to DAAs and improve treatment outcome. To test this hypothesis, we developed a multiscale mathematical model integrating IFN-responsiveness at the cellular level, viral kinetics and evolution leading to drug resistance at the individual level, and treatment outcome at the population level. Model predictions quantitatively captured data from over 50 clinical trials demonstrating poorer response to DAAs in previous non-responders to IFN than treatment-naïve individuals, presenting strong evidence supporting the hypothesis. Model predictions additionally described several unexplained clinical observations, viz., the percentages of infected individuals who 1) spontaneously clear HCV, 2) get chronically infected but respond to IFN-based therapy, and 3) fail IFN-based therapy but respond to DAA-based therapy, resulting in a comprehensive understanding of HCV infection and treatment. An implication of the causal relationship is that failure of DAA-based treatments may be averted by adding IFN, a strategy of potential use in settings with limited access to DAAs. A second, wider implication is that individuals with greater IFN-responsiveness would require shorter DAA-based treatment durations, presenting a basis and a promising population for response-guided therapy.'),
(89144, 2018, 'plos', 'miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts', 'Pla, Albert|Zhong, Xiangfu|Rayner, Simon', 'Department of Medical Genetics, University of Oslo, Oslo, Norway.|Department of Medical Genetics, University of Oslo, Oslo, Norway.|Department of Medical Genetics, University of Oslo, Oslo, Norway.', 'Norway|Norway|Norway', 0, '3 Untranslated Regions|Binding Sites|Computer Simulation|Datasets as Topic|Deep Learning|Gene Expression Regulation|Gene Targeting|Humans|MicroRNAs|Neural Networks (Computer)|RNA, Messenger|Reproducibility of Results|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006185', '30005074', 'MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3UTR of their target genes. Computational methods play an important role in target prediction and assume that the miRNA seed region (nt 2 to 8) is required for functional targeting, but typically only identify xe2x88xbc80% of known bindings. Recent studies have highlighted a role for the entire miRNA, suggesting that a more flexible methodology is needed. We present a novel approach for miRNA target prediction based on Deep Learning (DL) which, rather than incorporating any knowledge (such as seed regions), investigates the entire miRNA and 3TR mRNA nucleotides to learn a uninhibited set of feature descriptors related to the targeting process. We collected more than 150,000 experimentally validated homo sapiens miRNA:gene targets and cross referenced them with different CLIP-Seq, CLASH and iPAR-CLIP datasets to obtain xe2x88xbc20,000 validated miRNA:gene exact target sites. Using this data, we implemented and trained a deep neural network-composed of autoencoders and a feed-forward network-able to automatically learn features describing miRNA-mRNA interactions and assess functionality. Predictions were then refined using information such as site location or site accessibility energy. In a comparison using independent datasets, our DL approach consistently outperformed existing prediction methods, recognizing the seed region as a common feature in the targeting process, but also identifying the role of pairings outside this region. Thermodynamic analysis also suggests that site accessibility plays a role in targeting but that it cannot be used as a sole indicator for functionality. Data and source code available at: https://bitbucket.org/account/user/bipous/projects/MIRAW.'),
(89145, 2018, 'plos', 'Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks', 'Do, Duc|Bozdag, Serdar', 'Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, Wisconsin, United States of America.|Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, Wisconsin, United States of America.', 'United States|United States', 7, 'Atlases as Topic|Breast Neoplasms|Cell Line, Tumor|Computer Simulation|DNA Copy Number Variations|DNA Methylation|Datasets as Topic|Female|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Genes, Neoplasm|Humans|MicroRNAs|Neoplasm Proteins|Prognosis|Protein Binding|RNA Processing, Post-Transcriptional|RNA, Neoplasm', 'Journal Article', '10.1371/journal.pcbi.1006318', '30011266', 'MicroRNAs (miRNAs) inhibit expression of target genes by binding to their RNA transcripts. It has been recently shown that RNA transcripts targeted by the same miRNA could compete for the miRNA molecules and thereby indirectly regulate each other. Experimental evidence has suggested that the aberration of such miRNA-mediated interaction between RNAs-called competing endogenous RNA (ceRNA) interaction-can play important roles in tumorigenesis. Given the difficulty of deciphering context-specific miRNA binding, and the existence of various gene regulatory factors such as DNA methylation and copy number alteration, inferring context-specific ceRNA interactions accurately is a computationally challenging task. Here we propose a computational method called Cancerin to identify cancer-associated ceRNA interactions. Cancerin incorporates DNA methylation, copy number alteration, gene and miRNA expression datasets to construct cancer-specific ceRNA networks. We applied Cancerin to three cancer datasets from the Cancer Genome Atlas (TCGA) project. Our results indicated that ceRNAs were enriched with cancer-related genes, and ceRNA modules in the inferred ceRNA networks were involved in cancer-associated biological processes. Using LINCS-L1000 shRNA-mediated gene knockdown experiment in breast cancer cell line to assess accuracy, Cancerin was able to predict expression outcome of ceRNA genes with high accuracy.'),
(89146, 2018, 'plos', 'Interaction of the human erythrocyte Band 3 anion exchanger 1 (AE1, SLC4A1) with lipids and glycophorin A: Molecular organization of the Wright (Wr) blood group antigen', 'Kalli, Antreas C|Reithmeier, Reinhart A F', 'Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom.|Department of Biochemistry, University of Toronto, Toronto, Canada.', 'United Kingdom|Canada', 9, 'Anion Exchange Protein 1, Erythrocyte|Anions|Arginine|Blood Group Antigens|Cholesterol|Dimerization|Glutamic Acid|Glycophorin|Humans|Lipid Bilayers|Membrane Proteins|Molecular Dynamics Simulation|Phospholipids|Protein Binding|Protein Folding', 'Journal Article', '10.1371/journal.pcbi.1006284', '30011272', 'The Band 3 (AE1, SLC4A1) membrane protein is found in red blood cells and in kidney where it functions as an electro-neutral chloride/bicarbonate exchanger. In this study, we have used molecular dynamics simulations to provide the first realistic model of the dimeric membrane domain of human Band 3 in an asymmetric lipid bilayer containing a full complement of phospholipids, including phosphatidylinositol 4,5-bisphosphate (PIP2) and cholesterol, and its partner membrane protein Glycophorin A (GPA). The simulations show that the annular layer in the inner leaflet surrounding Band 3 was enriched in phosphatidylserine and PIP2 molecules. Cholesterol was also enriched around Band 3 but also at the dimer interface. The interaction of these lipids with specific sites on Band 3 may play a role in the folding and function of this anion transport membrane protein. GPA associates with Band 3 to form the Wright (Wr) blood group antigen, an interaction that involves an ionic bond between Glu658 in Band 3 and Arg61 in GPA. We were able to recreate this complex by performing simulations to allow the dimeric transmembrane portion of GPA to interact with Band 3 in a model membrane. Large-scale simulations showed that the GPA dimer can bridge Band 3 dimers resulting in the dynamic formation of long strands of alternating Band 3 and GPA dimers.'),
(89147, 2018, 'plos', 'Microheterogeneity-induced conduction slowing and wavefront collisions govern macroscopic conduction behavior: A computational and experimental study', 'Gokhale, Tanmay A|Asfour, Huda|Verma, Shravan|Bursac, Nenad|Henriquez, Craig S', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Action Potentials|Animals|Anisotropy|Arrhythmias, Cardiac|Cell Line|Computational Biology|Computer Simulation|HEK293 Cells|Heart Conduction System|Humans|In Vitro Techniques|Models, Cardiovascular', 'Journal Article', '10.1371/journal.pcbi.1006276', '30011279', 'The incidence of cardiac arrhythmias is known to be associated with tissue heterogeneities including fibrosis. However, the impact of microscopic structural heterogeneities on conduction in excitable tissues remains poorly understood. In this study, we investigated how acellular microheterogeneities affect macroscopic conduction under conditions of normal and reduced excitability by utilizing a novel platform of paired in vitro and in silico studies to examine the mechanisms of conduction. Regular patterns of nonconductive micro-obstacles were created in confluent monolayers of the previously described engineered-excitable Ex293 cell line. Increasing the relative ratio of obstacle size to intra-obstacle strand width resulted in significant conduction slowing up to 23.6% and a significant increase in wavefront curvature anisotropy, a measure of spatial variation in wavefront shape. Changes in bulk electrical conductivity and in path tortuosity were insufficient to explain these observed macroscopic changes. Rather, microscale behaviors including local conduction slowing due to microscale branching, and conduction acceleration due to wavefront merging were shown to contribute to macroscopic phenomena. Conditions of reduced excitability led to further conduction slowing and a reversal of wavefront curvature anisotropy due to spatially non-uniform effects on microscopic slowing and acceleration. This unique experimental and computation platform provided critical mechanistic insights in the impact of microscopic heterogeneities on macroscopic conduction, pertinent to settings of fibrotic heart disease.'),
(89148, 2018, 'plos', 'A quantitative physical model of the TMS-induced discharge artifacts in EEG', 'Freche, Dominik|Naim-Feil, Jodie|Peled, Avi|Levit-Binnun, Nava|Moses, Elisha', 'Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya, Israel.|Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya, Israel.|Rappaport Faculty of Medicine, Technion, Haifa, Israel.|Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya, Israel.|Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel', 1, 'Artifacts|Electrodes|Electroencephalography|Evoked Potentials, Motor|Humans|Knee|Models, Neurological|Muscle, Skeletal|Phantoms, Imaging|Reproducibility of Results|Skin Physiological Phenomena|Transcranial Magnetic Stimulation', 'Journal Article', '10.1371/journal.pcbi.1006177', '30016315', 'The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brains global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brains response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research.'),
(89149, 2018, 'plos', 'Stochastic resonance enhances the rate of evidence accumulation during combined brain stimulation and perceptual decision-making', 'van der Groen, Onno|Tang, Matthew F|Wenderoth, Nicole|Mattingley, Jason B', 'Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.|Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, Australia.|Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.|Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, Australia.', 'Switzerland|Australia|Switzerland|Australia', 14, 'Adolescent|Adult|Computer Simulation|Decision Making|Female|Humans|Male|Models, Neurological|Motion Perception|Noise|Stochastic Processes|Visual Cortex|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006301', '30020922', 'Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence. It is often assumed that such decisions are degraded by adding noise to a stimulus, or to the neural systems involved in the decision making process itself. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic resonance. Here we asked whether perceptual decisions made by human observers obey these stochastic resonance principles, by adding noise directly to the visual cortex using transcranial random noise stimulation (tRNS) while participants judged the direction of coherent motion in random-dot kinematograms presented at the fovea. We found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were just below perceptual threshold, but not when they were well below or above threshold. We modelled the data under a drift diffusion framework, and showed that bilateral tRNS selectively increased the drift rate parameter, which indexes the rate of evidence accumulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and to show that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.'),
(89150, 2018, 'plos', 'A biophysically detailed computational model of urinary bladder small DRG neuron soma', 'Mandge, Darshan|Manchanda, Rohit', 'Computational Neurophysiology Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India 400076.|Computational Neurophysiology Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India 400076.', 'India|India', 0, 'Action Potentials|Animals|Biophysical Phenomena|Calcium|Coloring Agents|Computer Simulation|Cytoplasm|Endoplasmic Reticulum|Ganglia, Spinal|Humans|Inositol 1,4,5-Trisphosphate Receptors|Membrane Potentials|Mitochondria|Neurons|Plasma Membrane Calcium-Transporting ATPases|Potassium Channels, Calcium-Activated|Ryanodine Receptor Calcium Release Channel|Sarcoplasmic Reticulum Calcium-Transporting ATPases|Sodium Channels|Urinary Bladder', 'Journal Article', '10.1371/journal.pcbi.1006293', '30020934', 'Bladder small DRG neurons, which are putative nociceptors pivotal to urinary bladder function, express more than a dozen different ionic membrane mechanisms: ion channels, pumps and exchangers. Small-conductance Ca2+-activated K+ (SKCa) channels which were earlier thought to be gated solely by intracellular Ca2+ concentration ([Ca]i) have recently been shown to exhibit inward rectification with respect to membrane potential. The effect of SKCa inward rectification on the excitability of these neurons is unknown. Furthermore, studies on the role of KCa channels in repetitive firing and their contributions to different types of afterhyperpolarization (AHP) in these neurons are lacking. In order to study these phenomena, we first constructed and validated a biophysically detailed single compartment model of bladder small DRG neuron soma constrained by physiological data. The model includes twenty-two major known membrane mechanisms along with intracellular Ca2+ dynamics comprising Ca2+ diffusion, cytoplasmic buffering, and endoplasmic reticulum (ER) and mitochondrial mechanisms. Using modelling studies, we show that inward rectification of SKCa is an important parameter regulating neuronal repetitive firing and that its absence reduces action potential (AP) firing frequency. We also show that SKCa is more potent in reducing AP spiking than the large-conductance KCa channel (BKCa) in these neurons. Moreover, BKCa was found to contribute to the fast AHP (fAHP) and SKCa to the medium-duration (mAHP) and slow AHP (sAHP). We also report that the slow inactivating A-type K+ channel (slow KA) current in these neurons is composed of 2 components: an initial fast inactivating (time constant xe2x88xbc 25-100 ms) and a slow inactivating (time constant xe2x88xbc 200-800 ms) current. We discuss the implications of our findings, and how our detailed model can help further our understanding of the role of C-fibre afferents in the physiology of urinary bladder as well as in certain disorders.'),
(89151, 2018, 'plos', 'A minimally invasive neurostimulation method for controlling abnormal synchronisation in the neuronal activity', 'Asllani, Malbor|Expert, Paul|Carletti, Timoteo', 'naXys, Namur Institute for Complex Systems, University of Namur, Namur, Belgium.|Department of Mathematics, Imperial College London, London, United Kingdom.|naXys, Namur Institute for Complex Systems, University of Namur, Namur, Belgium.', 'Belgium|United Kingdom|Belgium', 3, 'Brain|Cortical Synchronization|Deep Brain Stimulation|Humans|Microelectrodes|Minimally Invasive Surgical Procedures|Models, Neurological|Neurodegenerative Diseases|Neurons|Parkinson Disease|Seizures|Tremor', 'Evaluation Studies', '10.1371/journal.pcbi.1006296', '30024878', 'Many collective phenomena in Nature emerge from the -partial- synchronisation of the units comprising a system. In the case of the brain, this self-organised process allows groups of neurons to fire in highly intricate partially synchronised patterns and eventually lead to high level cognitive outputs and control over the human body. However, when the synchronisation patterns are altered and hypersynchronisation occurs, undesirable effects can occur. This is particularly striking and well documented in the case of epileptic seizures and tremors in neurodegenerative diseases such as Parkinsons disease. In this paper, we propose an innovative, minimally invasive, control method that can effectively desynchronise misfiring brain regions and thus mitigate and even eliminate the symptoms of the diseases. The control strategy, grounded in the Hamiltonian control theory, is applied to ensembles of neurons modelled via the Kuramoto or the Stuart-Landau models and allows for heterogeneous coupling among the interacting unities. The theory has been complemented with dedicated numerical simulations performed using the small-world Newman-Watts network and the random Erdxc5x91s-Rxc3xa9nyi network. Finally the method has been compared with the gold-standard Proportional-Differential Feedback control technique. Our method is shown to achieve equivalent levels of desynchronisation using lesser control strength and/or fewer controllers, being thus minimally invasive.'),
(89152, 2018, 'plos', 'Correction of copy number induced false positives in CRISPR screens', 'de Weck, Antoine|Golji, Javad|Jones, Michael D|Korn, Joshua M|Billy, Eric|McDonald, E Robert|Schmelzle, Tobias|Bitter, Hans|Kauffmann, Audrey', 'Novartis Institutes for Biomedical Research, Basel, Switzerland.|Novartis Institutes for Biomedical Research, Cambridge, MA, United States of America.|Novartis Institutes for Biomedical Research, Cambridge, MA, United States of America.|Novartis Institutes for Biomedical Research, Cambridge, MA, United States of America.|Novartis Institutes for Biomedical Research, Basel, Switzerland.|Novartis Institutes for Biomedical Research, Cambridge, MA, United States of America.|Novartis Institutes for Biomedical Research, Basel, Switzerland.|Novartis Institutes for Biomedical Research, Cambridge, MA, United States of America.|Novartis Institutes for Biomedical Research, Basel, Switzerland.', 'Switzerland|United States|United States|United States|Switzerland|United States|Switzerland|United S', 0, 'Artifacts|Astrocytoma|Brain Neoplasms|Cell Line, Tumor|Cell Proliferation|Clustered Regularly Interspaced Short Palindromic Repeats|DNA Copy Number Variations|Datasets as Topic|False Positive Reactions|Genomics|Humans|Models, Theoretical|Neoplasms|Stomach Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1006279', '30024886', 'Cell autonomous cancer dependencies are now routinely identified using CRISPR loss-of-function viability screens. However, a bias exists that makes it difficult to assess the true essentiality of genes located in amplicons, since the entire amplified region can exhibit lethal scores. These false-positive hits can either be discarded from further analysis, which in cancer models can represent a significant number of hits, or methods can be developed to rescue the true-positives within amplified regions. We propose two methods to rescue true positive hits in amplified regions by correcting for this copy number artefact. The Local Drop Out (LDO) method uses the relative lethality scores within genomic regions to assess true essentiality and does not require additional orthogonal data (e.g. copy number value). LDO is meant to be used in screens covering a dense region of the genome (e.g. a whole chromosome or the whole genome). The General Additive Model (GAM) method models the screening data as a function of the known copy number values and removes the systematic effect from the measured lethality. GAM does not require the same density as LDO, but does require prior knowledge of the copy number values. Both methods have been developed with single sample experiments in mind so that the correction can be applied even in smaller screens. Here we demonstrate the efficacy of both methods at removing the copy number effect and rescuing hits from some of the amplified regions. We estimate a 70-80% decrease of false positive hits with either method in regions of high copy number compared to no correction.'),
(89153, 2018, 'plos', 'Exploration and stabilization of Ras1 mating zone: A mechanism with positive and negative feedbacks', 'Khalili, Bita|Merlini, Laura|Vincenzetti, Vincent|Martin, Sophie G|Vavylonis, Dimitrios', 'Department of Physics, Lehigh University, Bethlehem, Pennsylvania, United States of America.|Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.|Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.|Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.|Department of Physics, Lehigh University, Bethlehem, Pennsylvania, United States of America.', 'United States|Switzerland|Switzerland|Switzerland|United States', 4, 'Actins|GTPase-Activating Proteins|Guanine Nucleotide Exchange Factors|Models, Biological|Pheromones|Protein Binding|Reproduction|Schizosaccharomyces|Schizosaccharomyces pombe Proteins|Signal Transduction|Stochastic Processes|cdc42 GTP-Binding Protein|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1006317', '30028833', 'In mating fission yeast cells, sensing and response to extracellular pheromone concentrations occurs through an exploratory Cdc42 patch that stochastically samples the cell cortex before stabilizing towards a mating partner. Active Ras1 (Ras1-GTP), an upstream regulator of Cdc42, and Gap1, the GTPase-activating protein for Ras1, localize at the patch. We developed a reaction-diffusion model of Ras1 patch appearance and disappearance with a positive feedback by a Guanine nucleotide Exchange Factor (GEF) and Gap1 inhibition. The model is based on new estimates of Ras1-GDP, Ras1-GTP and Gap1 diffusion coefficients and rates of cytoplasmic exchange studied by FRAP. The model reproduces exploratory patch behavior and lack of Ras1 patch in cells lacking Gap1. Transition to a stable patch can occur by change of Gap1 rates constants or local increase of the positive feedback rate constants. The model predicts that the patch size and number of patches depend on the strength of positive and negative feedbacks. Measurements of Ras1 patch size and number in cells overexpressing the Ras1 GEF or Gap1 are consistent with the model.'),
(89154, 2018, 'plos', 'Punishment and inspection for governing the commons in a feedback-evolving game', 'Chen, Xiaojie|Szolnoki, Attila', 'School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China.|Institute of Technical Physics and Materials Science, Centre for Energy Research, Hungarian Academy of Sciences, Budapest, Hungary.', 'China|Hungary', 39, 'Competitive Behavior|Cooperative Behavior|Feedback|Game Theory|Humans|Interpersonal Relations|Models, Psychological|Punishment', 'Journal Article', '10.1371/journal.pcbi.1006347', '30028836', 'Utilizing common resources is always a dilemma for community members. While cooperator players restrain themselves and consider the proper state of resources, defectors demand more than their supposed share for a higher payoff. To avoid the tragedy of the common state, punishing the latter group seems to be an adequate reaction. This conclusion, however, is less straightforward when we acknowledge the fact that resources are finite and even a renewable resource has limited growing capacity. To clarify the possible consequences, we consider a coevolutionary model where beside the payoff-driven competition of cooperator and defector players the level of a renewable resource depends sensitively on the fraction of cooperators and the total consumption of all players. The applied feedback-evolving game reveals that beside a delicately adjusted punishment it is also fundamental that cooperators should pay special attention to the growing capacity of renewable resources. Otherwise, even the usage of tough punishment cannot save the community from an undesired end.'),
(89155, 2018, 'plos', 'The evolutionary dynamics of metabolic protocells', 'Pechuan, Ximo|Puzio, Raymond|Bergman, Aviv', 'Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.', 'United States|United States|United States', 0, 'Artificial Cells|Biochemical Phenomena|Catalysis|Evolution, Molecular|Kinetics|Metabolic Networks and Pathways|Models, Theoretical|Mutation|RNA', 'Journal Article', '10.1371/journal.pcbi.1006265', '30028838', 'Protocell multilevel selection models have been proposed to study the evolutionary dynamics of vesicles encapsulating a set of replicating, competing and mutating sequences. The frequency of the different sequence types determines protocell survival through a fitness function. One of the defining features of these models is the genetic load generated when the protocell divides and its sequences are assorted between the offspring vesicles. However, these stochastic assortment effects disappear when the redundancy of each sequence type is sufficiently high. The fitness dependence of the vesicle with its sequence content is usually defined without considering a realistic account on how the lower level dynamics would specify the protocell fitness. Here, we present a protocell model with a fitness function determined by the output flux of a simple metabolic network with the aim of understanding how the evolution of both kinetic and topological features of metabolism would have been constrained by the particularities of the protocell evolutionary dynamics. In our model, the sequences inside the vesicle are both the carriers of information and Michaelis-Menten catalysts exhibiting saturation. We found that the saturation of the catalysts controlling the metabolic fluxes, achievable by modifying the kinetic or stoichiometric parameters, provides a mechanism to ameliorate the assortment load by increasing the redundancy of the catalytic sequences required to achieve the maximum flux. Regarding the network architecture, we conclude that combinations of parallel network motifs and bimolecular catalysts are a robust way to increase the complexity of the metabolism enclosed by the protocell.'),
(89156, 2018, 'plos', 'A marginalized two-part Beta regression model for microbiome compositional data', 'Chai, Haitao|Jiang, Hongmei|Lin, Lu|Liu, Lei', 'Institute for Financial Studies, Shandong University, Jinan, Shandong, China.|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America.|Institute for Financial Studies, Shandong University, Jinan, Shandong, China.|Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America.', 'China|United States|China|United States', 0, 'Animals|Colony Count, Microbial|Likelihood Functions|Logistic Models|Metagenomics|Mice|Microbiota|Skin', 'Journal Article', '10.1371/journal.pcbi.1006329', '30036363', 'In microbiome studies, an important goal is to detect differential abundance of microbes across clinical conditions and treatment options. However, the microbiome compositional data (quantified by relative abundance) are highly skewed, bounded in [0, 1), and often have many zeros. A two-part model is commonly used to separate zeros and positive values explicitly by two submodels: a logistic model for the probability of a specie being present in Part I, and a Beta regression model for the relative abundance conditional on the presence of the specie in Part II. However, the regression coefficients in Part II cannot provide a marginal (unconditional) interpretation of covariate effects on the microbial abundance, which is of great interest in many applications. In this paper, we propose a marginalized two-part Beta regression model which captures the zero-inflation and skewness of microbiome data and also allows investigators to examine covariate effects on the marginal (unconditional) mean. We demonstrate its practical performance using simulation studies and apply the model to a real metagenomic dataset on mouse skin microbiota. We find that under the proposed marginalized model, without loss in power, the likelihood ratio test performs better in controlling the type I error than those under conventional methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89157, 2018, 'plos', 'Real-time decision-making during emergency disease outbreaks', 'Probert, William J M|Jewell, Chris P|Werkman, Marleen|Fonnesbeck, Christopher J|Goto, Yoshitaka|Runge, Michael C|Sekiguchi, Satoshi|Shea, Katriona|Keeling, Matt J|Ferrari, Matthew J|Tildesley, Michael J', 'Department of Life Sciences, University of Warwick, Coventry, United Kingdom.|CHICAS, Lancaster University, Bailrigg, Lancaster, United Kingdom.|Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Marys Campus, Imperial College London, London, United Kingdom.|Department of Biostatistics, Vanderbilt University, Nashville, Tennessee, United States of America.|Center for Animal Disease Control, University of Miyazaki, Miyazaki, Japan.|US Geological Survey, Patuxent Wildlife Research Center, Laurel, Maryland, United States of America.|Center for Animal Disease Control, University of Miyazaki, Miyazaki, Japan.|Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, Pennsylvania, United States of America.|Department of Life Sciences, University of Warwick, Coventry, United Kingdom.|Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, Pennsylvania, United States of America.|Department of Life Sciences, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|Japan|United States|Japan|United States|U', 0, 'Animals|Animals, Domestic|Cattle|Cattle Diseases|Decision Making, Organizational|Disease Outbreaks|Foot-and-Mouth Disease|Foot-and-Mouth Disease Virus|Health Policy|Humans|Japan|Models, Theoretical|Sheep|Sheep Diseases|Swine|Swine Diseases|Time Factors|United Kingdom|Viral Vaccines', 'Journal Article', '10.1371/journal.pcbi.1006202', '30040815', 'In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect. Our results show that the control policy that would have been chosen using all the data is also identified from an early stage in an outbreak using only the available data, despite high variability in projections of epidemic size. Critically, we find that it is an improved understanding of the locations of infected farms, rather than improved estimates of transmission parameters, that drives improved prediction of the relative performance of control interventions. However, the ability to estimate undetected infectious premises is a function of uncertainty in the transmission parameters. Here, we demonstrate the need for both real-time model fitting and generating projections to evaluate alternative control interventions throughout an outbreak. Our results highlight the use of using models at outbreak onset to inform policy and the importance of state-dependent interventions that adapt in response to additional information throughout an outbreak.'),
(89158, 2018, 'plos', 'FusionPathway: Prediction of pathways and therapeutic targets associated with gene fusions in cancer', 'Wu, Chia-Chin|Beird, Hannah C|Zhang, Jianhua|Futreal, P Andrew', 'Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.', 'United States|United States|United States|United States', 0, 'Antineoplastic Agents|Carcinogenesis|DNA, Neoplasm|Fusion Proteins, bcr-abl|Gene Regulatory Networks|Humans|Metabolic Networks and Pathways|Neoplasm Proteins|Oncogene Proteins, Fusion|Proto-Oncogene Protein c-fli-1|RNA-Binding Protein EWS|Sarcoma|Software Design', 'Journal Article', '10.1371/journal.pcbi.1006266', '30040819', 'Numerous gene fusions have been uncovered across multiple cancer types. Although the ability to target several of these fusions has led to the development of some successful anti-cancer drugs, most of them are not druggable. Understanding the molecular pathways of a fusion is important in determining its function in oncogenesis and in developing therapeutic strategies for patients harboring the fusion. However, the molecular pathways have been elucidated for only a few fusions, in part because of the labor-intensive nature of the required functional assays. Therefore, we developed a domain-based network approach to infer the pathways of a fusion. Molecular interactions of a fusion are first predicted by using its protein domain composition, and its associated pathways are then inferred from these molecular interactions. We demonstrated the capabilities of this approach by primarily applying it to the well-studied BCR-ABL1 fusion. The approach was also applied to two undruggable fusions in sarcoma, EWS-FL1 and FUS-DDIT3. We successfully identified known genes and pathways associated with these fusions and satisfactorily validated these predictions using several benchmark sets. The predictions of EWS-FL1 and FUS-DDIT3 also correlate with results of high-throughput drug screening. To our best knowledge, this is the first approach for inferring pathways of fusions.'),
(89159, 2018, 'plos', 'Shared spatiotemporal category representations in biological and artificial deep neural networks', 'Greene, Michelle R|Hansen, Bruce C', 'Neuroscience Program, Bates College, Lewiston, ME, United States of America.|Department of Psychological and Brain Sciences, Neuroscience Program, Colgate University, Hamilton, NY, United States of America.', 'United States|United States', 11, 'Adolescent|Brain Mapping|Electrodes|Electroencephalography|Evoked Potentials|Evoked Potentials, Somatosensory|Female|Humans|Male|Neural Networks (Computer)|Photic Stimulation|Somatosensory Cortex|Vision, Ocular|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006327', '30040821', 'Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level accuracy using a feedforward architecture, providing neuroscientists with the opportunity to assess one successful series of representational transformations that enable categorization in silico. The goal of the current study is to assess the extent to which sequential scene category representations built by a CNN map onto those built in the human brain as assessed by high-density, time-resolved event-related potentials (ERPs). We found correspondence both over time and across the scalp: earlier (0-200 ms) ERP activity was best explained by early CNN layers at all electrodes. Although later activity at most electrode sites corresponded to earlier CNN layers, activity in right occipito-temporal electrodes was best explained by the later, fully-connected layers of the CNN around 225 ms post-stimulus, along with similar patterns in frontal electrodes. Taken together, these results suggest that the emergence of scene category representations develop through a dynamic interplay between early activity over occipital electrodes as well as later activity over temporal and frontal electrodes.'),
(89160, 2018, 'plos', 'An enormous potential for niche construction through bacterial cross-feeding in a homogeneous environment', 'San Roman, Magdalena|Wagner, Andreas', 'Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.|Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland', 8, 'Biodiversity|Biological Coevolution|Bioreactors|Carbon|Ecosystem|Escherichia coli|Fermentation|Genes, Bacterial|Genetic Variation|Glucose|Metabolic Networks and Pathways|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006340', '30040834', 'Microorganisms modify their environment by excreting by-products of metabolism, which can create new ecological niches that can help microbial populations diversify. A striking example comes from experimental evolution of genetically identical Escherichia coli populations that are grown in a homogeneous environment with the single carbon source glucose. In such experiments, stable communities of genetically diverse cross-feeding E. coli cells readily emerge. Some cells that consume the primary carbon source glucose excrete a secondary carbon source, such as acetate, that sustains other community members. Few such cross-feeding polymorphisms are known experimentally, because they are difficult to screen for. We studied the potential of bacterial metabolism to create new ecological niches based on cross-feeding. To do so, we used genome scale models of the metabolism of E. coli and metabolisms of similar complexity, to identify unique pairs of primary and secondary carbon sources in these metabolisms. We then combined dynamic flux balance analysis with analytical calculations to identify which pair of carbon sources can sustain a polymorphic cross-feeding community. We identified almost 10,000 such pairs of carbon sources, each of them corresponding to a unique ecological niche. Bacterial metabolism shows an immense potential for the construction of new ecological niches through cross feeding.'),
(89161, 2018, 'plos', 'A model for hydrophobic protrusions on peripheral membrane proteins', 'Fuglebakk, Edvin|Reuter, Nathalie', 'Computational Biology Unit, University of Bergen, Bergen, Norway.|Computational Biology Unit, University of Bergen, Bergen, Norway.', 'Norway|Norway', 2, 'Amino Acids|Binding Sites|Datasets as Topic|Hydrophobic and Hydrophilic Interactions|Membrane Proteins|Models, Biological|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1006325', '30048443', 'With remarkable spatial and temporal specificities, peripheral membrane proteins bind to biological membranes. They do this without compromising solubility of the protein, and their binding sites are not easily distinguished. Prototypical peripheral membrane binding sites display a combination of patches of basic and hydrophobic amino acids that are also frequently present on other protein surfaces. The purpose of this contribution is to identify simple but essential components for membrane binding, through structural criteria that distinguish exposed hydrophobes at membrane binding sites from those that are frequently found on any protein surface. We formulate the concepts of protruding hydrophobes and co-insertability and have analysed more than 300 families of proteins that are classified as peripheral membrane binders. We find that this structural motif strongly discriminates the surfaces of membrane-binding and non-binding proteins. Our model constitutes a novel formulation of a structural pattern for membrane recognition and emphasizes the importance of subtle structural properties of hydrophobic membrane binding sites.'),
(89162, 2018, 'plos', 'OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement', 'Seth, Ajay|Hicks, Jennifer L|Uchida, Thomas K|Habib, Ayman|Dembia, Christopher L|Dunne, James J|Ong, Carmichael F|DeMers, Matthew S|Rajagopal, Apoorva|Millard, Matthew|Hamner, Samuel R|Arnold, Edith M|Yong, Jennifer R|Lakshmikanth, Shrinidhi K|Sherman, Michael A|Ku, Joy P|Delp, Scott L', 'Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Mechanical Engineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 5, 'Animals|Biomechanical Phenomena|Computer Simulation|Gait|Hand Strength|Humans|Man-Machine Systems|Motor Neurons|Movement|Muscle, Skeletal|Paralysis|Self-Help Devices|Software Design|Walking', 'Journal Article', '10.1371/journal.pcbi.1006223', '30048444', 'Movement is fundamental to human and animal life, emerging through interaction of complex neural, muscular, and skeletal systems. Study of movement draws from and contributes to diverse fields, including biology, neuroscience, mechanics, and robotics. OpenSim unites methods from these fields to create fast and accurate simulations of movement, enabling two fundamental tasks. First, the software can calculate variables that are difficult to measure experimentally, such as the forces generated by muscles and the stretch and recoil of tendons during movement. Second, OpenSim can predict novel movements from models of motor control, such as kinematic adaptations of human gait during loaded or inclined walking. Changes in musculoskeletal dynamics following surgery or due to human-device interaction can also be simulated, these simulations have played a vital role in several applications, including the design of implantable mechanical devices to improve human grasping in individuals with paralysis. OpenSim is an extensible and user-friendly software package built on decades of knowledge about computational modeling and simulation of biomechanical systems. OpenSims design enables computational scientists to create new state-of-the-art software tools and empowers others to use these tools in research and clinical applications. OpenSim supports a large and growing community of biomechanics and rehabilitation researchers, facilitating exchange of models and simulations for reproducing and extending discoveries. Examples, tutorials, documentation, and an active user forum support this community. The OpenSim software is covered by the Apache License 2.0, which permits its use for any purpose including both nonprofit and commercial applications. The source code is freely and anonymously accessible on GitHub, where the community is welcomed to make contributions. Platform-specific installers of OpenSim include a GUI and are available on simtk.org.'),
(89163, 2018, 'plos', 'PyPhi: A toolbox for integrated information theory', 'Mayner, William G P|Marshall, William|Albantakis, Larissa|Findlay, Graham|Marchman, Robert|Tononi, Giulio', 'Neuroscience Training Program, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Psychiatry Department, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Psychiatry Department, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Neuroscience Training Program, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Psychiatry Department, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Psychiatry Department, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Information Theory|Markov Chains|Software Design|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1006343', '30048445', 'Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software package that implements this framework for causal analysis and unfolds the full cause-effect structure of discrete dynamical systems of binary elements. The software allows users to easily study these structures, serves as an up-to-date reference implementation of the formalisms of integrated information theory, and has been applied in research on complexity, emergence, and certain biological questions. We first provide an overview of the main algorithm and demonstrate PyPhis functionality in the course of analyzing an example system, and then describe details of the algorithms design and implementation. PyPhi can be installed with Pythons package manager via the command pip install pyphi on Linux and macOS systems equipped with Python 3.4 or higher. PyPhi is open-source and licensed under the GPLv3, the source code is hosted on GitHub at https://github.com/wmayner/pyphi. Comprehensive and continually-updated documentation is available at https://pyphi.readthedocs.io. The pyphi-users mailing list can be joined at https://groups.google.com/forum/#!forum/pyphi-users. A web-based graphical interface to the software is available at http://integratedinformationtheory.org/calculate.html.'),
(89164, 2018, 'plos', 'Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception', 'Acerbi, Luigi|Dokka, Kalpana|Angelaki, Dora E|Ma, Wei Ji', 'Center for Neural Science, New York University, New York, NY, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States of America.|Center for Neural Science, New York University, New York, NY, United States of America.', 'United States|United States|United States|United States', 0, 'Adult|Bayes Theorem|Brain|Cues|Discrimination (Psychology)|Female|Humans|Male|Models, Psychological|Motion Perception|Reproducibility of Results|Task Performance and Analysis|Vestibule, Labyrinth|Visual Perception|Young Adult', 'Comparative Study', '10.1371/journal.pcbi.1006110', '30052625', 'The precision of multisensory perception improves when cues arising from the same cause are integrated, such as visual and vestibular heading cues for an observer moving through a stationary environment. In order to determine how the cues should be processed, the brain must infer the causal relationship underlying the multisensory cues. In heading perception, however, it is unclear whether observers follow the Bayesian strategy, a simpler non-Bayesian heuristic, or even perform causal inference at all. We developed an efficient and robust computational framework to perform Bayesian model comparison of causal inference strategies, which incorporates a number of alternative assumptions about the observers. With this framework, we investigated whether human observers performance in an explicit cause attribution and an implicit heading discrimination task can be modeled as a causal inference process. In the explicit causal inference task, all subjects accounted for cue disparity when reporting judgments of common cause, although not necessarily all in a Bayesian fashion. By contrast, but in agreement with previous findings, data from the heading discrimination task only could not rule out that several of the same observers were adopting a forced-fusion strategy, whereby cues are integrated regardless of disparity. Only when we combined evidence from both tasks we were able to rule out forced-fusion in the heading discrimination task. Crucially, findings were robust across a number of variants of models and analyses. Our results demonstrate that our proposed computational framework allows researchers to ask complex questions within a rigorous Bayesian framework that accounts for parameter and model uncertainty.'),
(89165, 2018, 'plos', 'Activation of the DNA-repair mechanism through NBS1 and MRE11 diffusion', 'Friis, Ida|Solovyov, Ilia A', 'Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark.|Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark.', 'Denmark|Denmark', 2, 'Algorithms|Computer Simulation|DNA Breaks|DNA End-Joining Repair|DNA Repair|Diffusion|HMGN Proteins|Humans|MRE11 Homologue Protein|Models, Theoretical|Monte Carlo Method|Trans-Activators', 'Journal Article', '10.1371/journal.pcbi.1006362', '30052627', 'The non-homologous end joining of a DNA double strand break is initiated by the MRE11-NBS1-RAD50 complex whose subunits are the first three proteins to arrive to the breakage site thereby making the recruitment time of MRE11, NBS1 and RAD50 essential for cell survival. In the present investigation, the nature of MRE11 and NBS1 transportation from the cytoplasm to the nucleus, hosting the damaged DNA strand, is hypothesized to be a passive diffusive process. The feasibility of such a mechanism is addressed through theoretical and computational approaches which permit establishing the characteristic recruitment time of MRE11 and NBS1 by the nucleus. A computational model of a cell is constructed from a set of biological parameters and the kinetic Monte Carlo algorithm is used to simulate the diffusing MRE11 and NBS1 particles as a random walk process. To accurately describe the experimented data, it is discovered that MRE11 and NBS1 should start diffusion from significantly different starting positions which suggests that diffusion might not be the only transport mechanism of repair protein recruitment to the DNA break.'),
(89166, 2018, 'plos', 'Inter-trial effects in visual pop-out search: Factorial comparison of Bayesian updating models', 'Allenmark, Fredrik|Müller, Hermann J|Shi, Zhuanghua', 'Experimental Psychology, Department of Psychology, LMU Munich, Munich, Germany.|Experimental Psychology, Department of Psychology, LMU Munich, Munich, Germany.|Experimental Psychology, Department of Psychology, LMU Munich, Munich, Germany.', 'Germany|Germany|Germany', 3, 'Adult|Attention|Bayes Theorem|Color Perception|Decision Making|Female|Humans|Male|Models, Neurological|Observer Variation|Pattern Recognition, Visual|Photic Stimulation|Probability|Reaction Time|Reproducibility of Results|Young Adult', 'Comparative Study', '10.1371/journal.pcbi.1006328', '30059500', 'Many previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton (pop-out) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit top-down modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.'),
(89167, 2018, 'plos', 'Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning', 'Zhou, Naihui|Siegel, Zachary D|Zarecor, Scott|Lee, Nigel|Campbell, Darwin A|Andorf, Carson M|Nettleton, Dan|Lawrence-Dill, Carolyn J|Ganapathysubramanian, Baskar|Kelly, Jonathan W|Friedberg, Iddo', 'Program in Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America.|Department of Psychology, Iowa State University, Ames, Iowa, United States of America.|Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, United States of America.|Department of Mechanical Engineering, Iowa State University, Ames, Iowa, United States of America.|Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, United States of America.|Agricultural Research Services, United States Department of Agriculture, Ames, Iowa, United States of America.|Program in Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America.|Program in Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America.|Department of Mechanical Engineering, Iowa State University, Ames, Iowa, United States of America.|Department of Psychology, Iowa State University, Ames, Iowa, United States of America.|Program in Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 11, 'Algorithms|Crops, Agricultural|Crowdsourcing|Data Accuracy|Food Supply|Humans|Image Processing, Computer-Assisted|Internet|Machine Learning|Phenotype|Pilot Projects', 'Journal Article', '10.1371/journal.pcbi.1006337', '30059508', 'The accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals, however, this can be costly in time, effort, and money. Here we explore the use of crowdsourcing to generate a large number of training data of good quality. We explore an image analysis task involving the segmentation of corn tassels from images taken in a field setting. We investigate the accuracy, speed and other quality metrics when this task is performed by students for academic credit, Amazon MTurk workers, and Master Amazon MTurk workers. We conclude that the Amazon MTurk and Master Mturk workers perform significantly better than the for-credit students, but with no significant difference between the two MTurk worker types. Furthermore, the quality of the segmentation produced by Amazon MTurk workers rivals that of an expert worker. We provide best practices to assess the quality of ground truth data, and to compare data quality produced by different sources. We conclude that properly managed crowdsourcing can be used to establish large volumes of viable ground truth data at a low cost and high quality, especially in the context of high throughput plant phenotyping. We also provide several metrics for assessing the quality of the generated datasets.'),
(89168, 2018, 'plos', 'The role of the encapsulated cargo in microcompartment assembly', 'Mohajerani, Farzaneh|Hagan, Michael F', 'Martin A. Fisher School of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Martin A. Fisher School of Physics, Brandeis University, Waltham, Massachusetts, United States of America.', 'United States|United States', 5, 'Algorithms|Bacterial Proteins|Biological Transport|Cell Compartmentation|Computer Simulation|Kinetics|Metabolic Networks and Pathways|Models, Theoretical|Organelles|Synthetic Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006351', '30063715', 'Bacterial microcompartments are large, roughly icosahedral shells that assemble around enzymes and reactants involved in certain metabolic pathways in bacteria. Motivated by microcompartment assembly, we use coarse-grained computational and theoretical modeling to study the factors that control the size and morphology of a protein shell assembling around hundreds to thousands of molecules. We perform dynamical simulations of shell assembly in the presence and absence of cargo over a range of interaction strengths, subunit and cargo stoichiometries, and the shell spontaneous curvature. Depending on these parameters, we find that the presence of a cargo can either increase or decrease the size of a shell relative to its intrinsic spontaneous curvature, as seen in recent experiments. These features are controlled by a balance of kinetic and thermodynamic effects, and the shell size is assembly pathway dependent. We discuss implications of these results for synthetic biology efforts to target new enzymes to microcompartment interiors.'),
(89169, 2018, 'plos', 'Modeling the impact of changes in day-care contact patterns on the dynamics of varicella transmission in France between 1991 and 2015', 'Marziano, Valentina|Poletti, Piero|Béraud, Guillaume|Boëlle, Pierre-Yves|Merler, Stefano|Colizza, Vittoria', 'Center for Information Technology, Bruno Kessler Foundation, Trento, Italy.|Center for Information Technology, Bruno Kessler Foundation, Trento, Italy.|Médecine Interne et Maladies Infectieuses, Centre Hospitalier de Poitiers, Poitiers, France.|INSERM, Sorbonne Université, Institut Pierre Louis dEpidémiologie et de Santé Publique IPLESP, Paris, France.|Center for Information Technology, Bruno Kessler Foundation, Trento, Italy.|INSERM, Sorbonne Université, Institut Pierre Louis dEpidémiologie et de Santé Publique IPLESP, Paris, France.', 'Italy|Italy|France|France|Italy|France', 3, 'Age Factors|Chickenpox|Child Day Care Centers|Child, Preschool|Disease Transmission, Infectious|Female|France|Herpesvirus 3, Human|History, 20th Century|History, 21st Century|Humans|Incidence|Infant|Infant, Newborn|Male|Models, Theoretical|Vaccination', 'Historical Article', '10.1371/journal.pcbi.1006334', '30067732', 'Annual incidence rates of varicella infection in the general population in France have been rather stable since 1991 when clinical surveillance started. Rates however show a statistically significant increase over time in children aged 0-3 years, and a decline in older individuals. A significant increase in day-care enrolment and structures capacity in France was also observed in the last decade. In this work we investigate the potential interplay between an increase of contacts of young children possibly caused by earlier socialization in the community and varicella transmission dynamics. To this aim, we develop an age-structured mathematical model, informed with historical demographic data and contact matrix estimates in the country, accounting for longitudinal linear increase of early childhood contacts. While the reported overall varicella incidence is well reproduced independently of mixing variations, age-specific empirical trends are better captured by accounting for an increase in contacts among pre-school children in the last decades. We found that the varicella data are consistent with a 30% increase in the number of contacts at day-care facilities, which would imply a 50% growth in the contribution of 0-3y old children to overall yearly infections in 1991-2015. Our findings suggest that an earlier exposure to pathogens due to changes in day-care contact patterns, represents a plausible explanation for the epidemiological patterns observed in France. Obtained results suggest that considering temporal changes in social factors in addition to demographic ones is critical to correctly interpret varicella transmission dynamics.'),
(89170, 2018, 'plos', 'Irrelevance by inhibition: Learning, computation, and implications for schizophrenia', 'Insel, Nathan|Guerguiev, Jordan|Richards, Blake A', 'Department of Psychology, University of Montana, Missoula, Montana, United States of America.|Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada.|Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada.', 'United States|Canada|Canada', 1, 'Action Potentials|Interneurons|Learning|Models, Biological|Models, Neurological|Models, Theoretical|Nerve Net|Neural Inhibition|Neural Networks (Computer)|Neuronal Plasticity|Schizophrenia', 'Journal Article', '10.1371/journal.pcbi.1006315', '30067746', 'Symptoms of schizophrenia may arise from a failure of cortical circuits to filter-out irrelevant inputs. Schizophrenia has also been linked to disruptions in cortical inhibitory interneurons, consistent with the possibility that in the normally functioning brain, these cells are in some part responsible for determining which sensory inputs are relevant versus irrelevant. Here, we develop a neural network model that demonstrates how the cortex may learn to ignore irrelevant inputs through plasticity processes affecting inhibition. The model is based on the proposal that the amount of excitatory output from a cortical circuit encodes the expected magnitude of reward or punishment (relevance), which can be trained using a temporal difference learning mechanism acting on feedforward inputs to inhibitory interneurons. In the model, irrelevant and blocked stimuli drive lower levels of excitatory activity compared with novel and relevant stimuli, and this difference in activity levels is lost following disruptions to inhibitory units. When excitatory units are connected to a competitive-learning output layer with a threshold, the relevance code can be shown to gate both learning and behavioral responses to irrelevant stimuli. Accordingly, the combined network is capable of recapitulating published experimental data linking inhibition in frontal cortex with fear learning and expression. Finally, the model demonstrates how relevance learning can take place in parallel with other types of learning, through plasticity rules involving inhibitory and excitatory components, respectively. Altogether, this work offers a theory of how the cortex learns to selectively inhibit inputs, providing insight into how relevance-assignment problems may emerge in schizophrenia.'),
(89171, 2018, 'plos', 'The permeation mechanism of organic cations through a CNG mimic channel', 'Napolitano, Luisa M R|Marchesi, Arin|Rodriguez, Alex|De March, Matteo|Onesti, Silvia|Laio, Alessandro|Torre, Vincent', 'International School for Advanced Studies (SISSA), Trieste, Italy.|INSERM U1006, Aix-Marseille Université, Parc Scientifique et Technologique de Luminy, Marseille, France.|International School for Advanced Studies (SISSA), Trieste, Italy.|Structural Biology Laboratory, Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Trieste, Italy.|Structural Biology Laboratory, Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.', 'Italy|France|Italy|Italy|Italy|Italy|Italy', 0, 'Animals|Biophysical Phenomena|Cations|Computer Simulation|Cyclic Nucleotide-Gated Cation Channels|Dimethylamines|Gap Junctions|Membrane Potentials|Molecular Dynamics Simulation|Oocytes|Organic Cation Transport Proteins|Quaternary Ammonium Compounds|Sodium|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1006295', '30071012', 'Several channels, ranging from TRP receptors to Gap junctions, allow the exchange of small organic solute across cell membrane. However, very little is known about the molecular mechanism of their permeation. Cyclic Nucleotide Gated (CNG) channels, despite their homology with K+ channels and in contrast with them, allow the passage of larger methylated and ethylated ammonium ions like dimethylammonium (DMA) and ethylammonium (EA). We combined electrophysiology and molecular dynamics simulations to examine how DMA interacts with the pore and permeates through it. Due to the presence of hydrophobic groups, DMA enters easily in the channel and, unlike the alkali cations, does not need to cross any barrier. We also show that while the crystal structure is consistent with the presence of a single DMA ion at full occupancy, the channel is able to conduct a sizable current of DMA ions only when two ions are present inside the channel. Moreover, the second DMA ion dramatically changes the free energy landscape, destabilizing the crystallographic binding site and lowering by almost 25 kJ/mol the binding affinity between DMA and the channel. Based on the results of the simulation the experimental electron density maps can be re-interpreted with the presence of a second ion at lower occupancy. In this mechanism the flexibility of the channel plays a key role, extending the classical multi-ion permeation paradigm in which conductance is enhanced by the plain interaction between the ions.'),
(89172, 2018, 'plos', 'Profiling cellular morphodynamics by spatiotemporal spectrum decomposition', 'Ma, Xiao|Dagliyan, Onur|Hahn, Klaus M|Danuser, Gaudenz', 'Dept. of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Dept. of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.', 'United States|United States|United States|United States', 8, 'Algorithms|Animals|COS Cells|Cell Movement|Cell Shape|Cercopithecus aethiops|Data Analysis|Guanine Nucleotide Exchange Factors|Motion|Proto-Oncogene Proteins c-vav|Signal Transduction|Spatial Analysis|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1006321', '30071020', 'Cellular morphology and associated morphodynamics are widely used for qualitative and quantitative assessments of cell state. Here we implement a framework to profile cellular morphodynamics based on an adaptive decomposition of local cell boundary motion into instantaneous frequency spectra defined by the Hilbert-Huang transform (HHT). Our approach revealed that spontaneously migrating cells with approximately homogeneous molecular makeup show remarkably consistent instantaneous frequency distributions, though they have markedly heterogeneous mobility. Distinctions in cell edge motion between these cells are captured predominantly by differences in the magnitude of the frequencies. We found that acute photo-inhibition of Vav2 guanine exchange factor, an activator of the Rho family of signaling proteins coordinating cell motility, produces significant shifts in the frequency distribution, but does not affect frequency magnitude. We therefore concluded that the frequency spectrum encodes the wiring of the molecular circuitry that regulates cell boundary movements, whereas the magnitude captures the activation level of the circuitry. We also used HHT spectra as multi-scale spatiotemporal features in statistical region merging to identify subcellular regions of distinct motion behavior. In line with our conclusion that different HHT spectra relate to different signaling regimes, we found that subcellular regions with different morphodynamics indeed exhibit distinct Rac1 activities. This algorithm thus can serve as an accurate and sensitive classifier of cellular morphodynamics to pinpoint spatial and temporal boundaries between signaling regimes.'),
(89173, 2018, 'plos', 'Rare-event sampling of epigenetic landscapes and phenotype transitions', 'Tse, Margaret J|Chu, Brian K|Gallivan, Cameron P|Read, Elizabeth L', 'Department of Chemical Engineering & Materials Science, University of California, Irvine, Irvine, California, United States of America.|Department of Chemical Engineering & Materials Science, University of California, Irvine, Irvine, California, United States of America.|Department of Chemical Engineering & Materials Science, University of California, Irvine, Irvine, California, United States of America.|Department of Chemical Engineering & Materials Science, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States', 7, 'Cell Differentiation|Cellular Reprogramming|Computer Simulation|Data Interpretation, Statistical|Data Mining|Embryonic Stem Cells|Epigenomics|Gene Expression Regulation|Gene Regulatory Networks|Kinetics|Models, Biological|Models, Genetic|Phenotype|Probability|Software|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006336', '30074987', 'Stochastic simulation has been a powerful tool for studying the dynamics of gene regulatory networks, particularly in terms of understanding how cell-phenotype stability and fate-transitions are impacted by noisy gene expression. However, gene networks often have dynamics characterized by multiple attractors. Stochastic simulation is often inefficient for such systems, because most of the simulation time is spent waiting for rare, barrier-crossing events to occur. We present a rare-event simulation-based method for computing epigenetic landscapes and phenotype-transitions in metastable gene networks. Our computational pipeline was inspired by studies of metastability and barrier-crossing in protein folding, and provides an automated means of computing and visualizing essential stationary and dynamic information that is generally inaccessible to conventional simulation. Applied to a network model of pluripotency in Embryonic Stem Cells, our simulations revealed rare phenotypes and approximately Markovian transitions among phenotype-states, occurring with a broad range of timescales. The relative probabilities of phenotypes and the transition paths linking pluripotency and differentiation are sensitive to global kinetic parameters governing transcription factor-DNA binding kinetics. Our approach significantly expands the capability of stochastic simulation to investigate gene regulatory network dynamics, which may help guide rational cell reprogramming strategies. Our approach is also generalizable to other types of molecular networks and stochastic dynamics frameworks.'),
(89174, 2018, 'plos', 'A mechanism for bistability in glycosylation', 'McDonald, Andrew G|Tipton, Keith F|Davey, Gavin P', 'School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.|School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.|School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 0, 'Biophysical Phenomena|Catalysis|Enzyme Activation|Feedback, Physiological|Galactosyltransferases|Glycosylation|Glycosyltransferases|Humans|Kinetics|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1006348', '30074989', 'Glycosyltransferases are a class of enzymes that catalyse the posttranslational modification of proteins to produce a large number of glycoconjugate acceptors from a limited number of nucleotide-sugar donors. The products of one glycosyltransferase can be the substrates of several other enzymes, causing a combinatorial explosion in the number of possible glycan products. The kinetic behaviour of systems where multiple acceptor substrates compete for a single enzyme is presented, and the case in which high concentrations of an acceptor substrate are inhibitory as a result of abortive complex formation, is shown to result in non-Michaelian kinetics that can lead to bistability in an open system. A kinetic mechanism is proposed that is consistent with the available experimental evidence and provides a possible explanation for conflicting observations on the xcexb2-1,4-galactosyltransferases. Abrupt switching between steady states in networks of glycosyltransferase-catalysed reactions may account for the observed changes in glycosyl-epitopes in cancer cells.'),
(89175, 2018, 'plos', 'A new dynamic correlation algorithm reveals novel functional aspects in single cell and bulk RNA-seq data', 'Yu, Tianwei', 'Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States of America.', 'United States', 4, 'Algorithms|Animals|Cluster Analysis|Databases, Genetic|Gene Expression|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Oligonucleotide Array Sequence Analysis|RNA|Sequence Analysis, RNA|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1006391', '30080856', 'Dynamic correlations are pervasive in high-throughput data. Large numbers of gene pairs can change their correlation patterns in response to observed/unobserved changes in physiological states. Finding changes in correlation patterns can reveal important regulatory mechanisms. Currently there is no method that can effectively detect global dynamic correlation patterns in a dataset. Given the challenging nature of the problem, the currently available methods use genes as surrogate measurements of physiological states, which cannot faithfully represent true underlying biological signals. In this study we develop a new method that directly identifies strong latent dynamic correlation signals from the data matrix, named DCA: Dynamic Correlation Analysis. At the center of the method is a new metric for the identification of pairs of variables that are highly likely to be dynamically correlated, without knowing the underlying physiological states that govern the dynamic correlation. We validate the performance of the method with extensive simulations. We applied the method to three real datasets: a single cell RNA-seq dataset, a bulk RNA-seq dataset, and a microarray gene expression dataset. In all three datasets, the method reveals novel latent factors with clear biological meaning, bringing new insights into the data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89176, 2018, 'plos', 'Network supporting contextual fear learning after dorsal hippocampal damage has increased dependence on retrosplenial cortex', 'Coelho, Cesar A O|Ferreira, Tatiana L|Kramer-Soares, Juliana C|Sato, João R|Oliveira, Maria Gabriela M', 'Departamento de Psicobiologia, Universidade Federal de São Paulo - UNIFESP, São Paulo, São Paulo, Brazil.|Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, UFABC, São Bernardo do Campo, São Paulo, Brazil.|Departamento de Psicobiologia, Universidade Federal de São Paulo - UNIFESP, São Paulo, São Paulo, Brazil.|Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, UFABC, São Bernardo do Campo, São Paulo, Brazil.|Departamento de Psicobiologia, Universidade Federal de São Paulo - UNIFESP, São Paulo, São Paulo, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 5, 'Animals|Cerebral Cortex|Conditioning, Classical|Cyclic AMP Response Element-Binding Protein|Fear|Hippocampus|Learning|Male|Memory|Rats|Rats, Wistar|Temporal Lobe', 'Journal Article', '10.1371/journal.pcbi.1006207', '30086129', 'Hippocampal damage results in profound retrograde, but no anterograde amnesia in contextual fear conditioning (CFC). Although the content learned in the latter have been discussed, alternative regions supporting CFC learning were seldom proposed and never empirically addressed. Here, we employed network analysis of pCREB expression quantified from brain slices of rats with dorsal hippocampal lesion (dHPC) after undergoing CFC session. Using inter-regional correlations of pCREB-positive nuclei between brain regions, we modelled functional networks using different thresholds. The dHPC network showed small-world topology, equivalent to SHAM (control) network. However, diverging hubs were identified in each network. In a direct comparison, hubs in both networks showed consistently higher centrality values compared to the other network. Further, the distribution of correlation coefficients was different between the groups, with most significantly stronger correlation coefficients belonging to the SHAM network. These results suggest that dHPC network engaged in CFC learning is partially different, and engage alternative hubs. We next tested if pre-training lesions of dHPC and one of the new dHPC network hubs (perirhinal, Per, or disgranular retrosplenial, RSC, cortices) would impair CFC. Only dHPC-RSC, but not dHPC-Per, impaired CFC. Interestingly, only RSC showed a consistently higher centrality in the dHPC network, suggesting that the increased centrality reflects an increased functional dependence on RSC. Our results provide evidence that, without hippocampus, the RSC, an anatomically central region in the medial temporal lobe memory system might support CFC learning and memory.'),
(89177, 2018, 'plos', 'Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials', 'Yurkovich, James T|Alcantar, Miguel A|Haiman, Zachary B|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.', 'United States|United States|United States|United States', 1, 'Allosteric Regulation|Biophysical Phenomena|Catalysis|Computer Simulation|Glycolysis|Hexokinase|Humans|Kinetics|Ligands|Phosphofructokinase-1|Protein Binding|Pyruvate Kinase|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006356', '30086174', 'Allosteric regulation has traditionally been described by mathematically-complex allosteric rate laws in the form of ratios of polynomials derived from the application of simplifying kinetic assumptions. Alternatively, an approach that explicitly describes all known ligand-binding events requires no simplifying assumptions while allowing for the computation of enzymatic states. Here, we employ such a modeling approach to examine the catalytic potential of an enzyme-an enzymes capacity to catalyze a biochemical reaction. The catalytic potential is the fundamental result of multiple ligand-binding events that represents a tug of war among the various regulators and substrates within the network. This formalism allows for the assessment of interacting allosteric enzymes and development of a network-level understanding of regulation. We first define the catalytic potential and use it to characterize the response of three key kinases (hexokinase, phosphofructokinase, and pyruvate kinase) in human red blood cell glycolysis to perturbations in ATP utilization. Next, we examine the sensitivity of the catalytic potential by using existing personalized models, finding that the catalytic potential allows for the identification of subtle but important differences in how individuals respond to such perturbations. Finally, we explore how the catalytic potential can help to elucidate how enzymes work in tandem to maintain a homeostatic state. Taken together, this work provides an interpretation and visualization of the dynamic interactions and network-level effects of interacting allosteric enzymes.'),
(89178, 2018, 'plos', 'Correction: Limits on reliable information flows through stochastic populations', 'PLOS Computational Biology Staff', 'Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.', 'United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006404', '30091970', '[This corrects the article DOI: 10.1371/journal.pcbi.1006195.].'),
(89179, 2018, 'plos', 'Flexible resonance in prefrontal networks with strong feedback inhibition', 'Sherfey, Jason S|Ardid, Salva|Hass, Joachim|Hasselmo, Michael E|Kopell, Nancy J', 'Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.|Department of Theoretical Neuroscience, Bernstein Center for Computational Neuroscience, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.|Department of Psychological and Brain Sciences, Center for Systems Neuroscience, Boston University, Massachusetts, United States of America.|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|Germany|United States|United States', 6, 'Action Potentials|Animals|Brain Waves|Computer Simulation|Excitatory Postsynaptic Potentials|Humans|Inhibitory Postsynaptic Potentials|Models, Neurological|Neurons|Patch-Clamp Techniques|Prefrontal Cortex|Pyramidal Cells', 'Journal Article', '10.1371/journal.pcbi.1006357', '30091975', 'Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation, and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells, we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering.'),
(89180, 2018, 'plos', 'Phylogeny-corrected identification of microbial gene families relevant to human gut colonization', 'Bradley, Patrick H|Nayfach, Stephen|Pollard, Katherine S', 'Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.|Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.|Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.', 'United States|United States|United States', 8, 'Bacteria|Gastrointestinal Microbiome|Gene Expression Regulation, Bacterial|Genes, Microbial|Humans|Metagenome|Metagenomics|Microbiota|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1006242', '30091981', 'The mechanisms by which different microbes colonize the healthy human gut versus other body sites, the gut in disease states, or other environments remain largely unknown. Identifying microbial genes influencing fitness in the gut could lead to new ways to engineer probiotics or disrupt pathogenesis. We approach this problem by measuring the statistical association between a species having a gene and the probability that the species is present in the gut microbiome. The challenge is that closely related species tend to be jointly present or absent in the microbiome and also share many genes, only a subset of which are involved in gut adaptation. We show that this phylogenetic correlation indeed leads to many false discoveries and propose phylogenetic linear regression as a powerful solution. To apply this method across the bacterial tree of life, where most species have not been experimentally phenotyped, we use metagenomes from hundreds of people to quantify each species prevalence in and specificity for the gut microbiome. This analysis reveals thousands of genes potentially involved in adaptation to the gut across species, including many novel candidates as well as processes known to contribute to fitness of gut bacteria, such as acid tolerance in Bacteroidetes and sporulation in Firmicutes. We also find microbial genes associated with a preference for the gut over other body sites, which are significantly enriched for genes linked to fitness in an in vivo competition experiment. Finally, we identify gene families associated with higher prevalence in patients with Crohns disease, including Proteobacterial genes involved in conjugation and fimbria regulation, processes previously linked to inflammation. These gene targets may represent new avenues for modulating host colonization and disease. Our strategy of combining metagenomics with phylogenetic modeling is general and can be used to identify genes associated with adaptation to any environment.'),
(89181, 2018, 'plos', 'scPipe: A flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data', 'Tian, Luyi|Su, Shian|Dong, Xueyi|Amann-Zalcenstein, Daniela|Biben, Christine|Seidi, Azadeh|Hilton, Douglas J|Naik, Shalin H|Ritchie, Matthew E', 'Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Australian Genome Research Facility, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 23, 'Animals|Base Sequence|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|RNA|Sequence Analysis, RNA|Single-Cell Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1006361', '30096152', 'Single-cell RNA sequencing (scRNA-seq) technology allows researchers to profile the transcriptomes of thousands of cells simultaneously. Protocols that incorporate both designed and random barcodes have greatly increased the throughput of scRNA-seq, but give rise to a more complex data structure. There is a need for new tools that can handle the various barcoding strategies used by different protocols and exploit this information for quality assessment at the sample-level and provide effective visualization of these results in preparation for higher-level analyses. To this end, we developed scPipe, an R/Bioconductor package that integrates barcode demultiplexing, read alignment, UMI-aware gene-level quantification and quality control of raw sequencing data generated by multiple protocols that include CEL-seq, MARS-seq, Chromium 10X, Drop-seq and Smart-seq. scPipe produces a count matrix that is essential for downstream analysis along with an HTML report that summarises data quality. These results can be used as input for downstream analyses including normalization, visualization and statistical testing. scPipe performs this processing in a few simple R commands, promoting reproducible analysis of single-cell data that is compatible with the emerging suite of open-source scRNA-seq analysis tools available in R/Bioconductor and beyond. The scPipe R package is available for download from https://www.bioconductor.org/packages/scPipe.'),
(89182, 2018, 'plos', 'Modeling subjective relevance in schizophrenia and its relation to aberrant salience', 'Katthagen, Teresa|Mathys, Christoph|Deserno, Lorenz|Walter, Henrik|Kathmann, Norbert|Heinz, Andreas|Schlagenhauf, Florian', 'Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy CCM, Berlin, Germany.|Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.|Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy CCM, Berlin, Germany.|Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy CCM, Berlin, Germany.|Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.|Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy CCM, Berlin, Germany.|Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy CCM, Berlin, Germany.', 'Germany|Italy|Germany|Germany|Germany|Germany|Germany', 7, 'Adult|Bayes Theorem|Brain Mapping|Computer Simulation|Cues|Female|Humans|Image Processing, Computer-Assisted|Learning|Magnetic Resonance Imaging|Male|Psychotic Disorders|Reaction Time|Schizophrenia|Schizophrenic Psychology', 'Journal Article', '10.1371/journal.pcbi.1006319', '30096179', 'In schizophrenia, increased aberrant salience to irrelevant events and reduced learning of relevant information may relate to an underlying deficit in relevance detection. So far, subjective estimates of relevance have not been probed in schizophrenia patients. The mechanisms underlying belief formation about relevance and their translation into decisions are unclear. Using novel computational methods, we investigated relevance detection during implicit learning in 42 schizophrenia patients and 42 healthy individuals. Participants underwent functional magnetic resonance imaging while detecting the outcomes in a learning task. These were preceded by cues differing in color and shape, which were either relevant or irrelevant for outcome prediction. We provided a novel definition of relevance based on Bayesian precision and modeled reaction times as a function of relevance weighted unsigned prediction errors (UPE). For aberrant salience, we assessed responses to subjectively irrelevant cue manifestations. Participants learned the contingencies and slowed down their responses following unexpected events. Model selection revealed that individuals inferred the relevance of cue features and used it for behavioral adaption to the relevant cue feature. Relevance weighted UPEs correlated with dorsal anterior cingulate cortex activation and hippocampus deactivation. In patients, the aberrant salience bias to subjectively task-irrelevant information was increased and correlated with decreased striatal UPE activation and increased negative symptoms. This study shows that relevance estimates based on Bayesian precision can be inferred from observed behavior. This underscores the importance of relevance detection as an underlying mechanism for behavioral adaptation in complex environments and enhances the understanding of aberrant salience in schizophrenia.'),
(89183, 2018, 'plos', 'Discerning evolutionary trends in post-translational modification and the effect of intrinsic disorder: Analysis of methylation, acetylation and ubiquitination sites in human proteins', 'Narasumani, Mohanalakshmi|Harrison, Paul M', 'Department of Biology, McGill University, Montreal, QC, Canada.|Department of Biology, McGill University, Montreal, QC, Canada.', 'Canada|Canada', 0, 'Acetylation|Amino Acid Sequence|Animals|Biological Evolution|Computational Biology|Eukaryota|Evolution, Molecular|Humans|Intrinsically Disordered Proteins|Methylation|Protein Processing, Post-Translational|Proteome|Ubiquitination', 'Journal Article', '10.1371/journal.pcbi.1006349', '30096183', 'Intrinsically disordered regions (IDRs) of proteins play significant biological functional roles despite lacking a well-defined 3D structure. For example, IDRs provide efficient housing for large numbers of post-translational modification (PTM) sites in eukaryotic proteins. Here, we study the distribution of more than 15,000 experimentally determined human methylation, acetylation and ubiquitination sites (collectively termed MAU sites) in ordered and disordered regions, and analyse their conservation across 380 eukaryotic species. Conservation signals for the maintenance and novel emergence of MAU sites are examined at 11 evolutionary levels from the whole eukaryotic domain down to the ape superfamily, in both ordered and disordered regions. We discover that MAU PTM is a major driver of conservation for arginines and lysines in both ordered and disordered regions, across the 11 levels, most significantly across the mammalian clade. Conservation of human methylatable arginines is very strongly favoured for ordered regions rather than for disordered, whereas methylatable lysines are conserved in either set of regions, and conservation of acetylatable and ubiquitinatable lysines is favoured in disordered over ordered. Notably, we find evidence for the emergence of new lysine MAU sites in disordered regions of proteins in deuterostomes and mammals, and in ordered regions after the dawn of eutherians. For histones specifically, MAU sites demonstrate an idiosyncratic significant conservation pattern that is evident since the last common ancestor of mammals. Similarly, folding-on-binding (FB) regions are highly enriched for MAU sites relative to either ordered or disordered regions, with ubiquitination sites in FBs being highly conserved at all evolutionary levels back as far as mammals. This investigation clearly demonstrates the complex patterns of PTM evolution across the human proteome and that it is necessary to consider conservation of sequence features at multiple evolutionary levels in order not to get an incomplete or misleading picture.'),
(89184, 2018, 'plos', 'riboWaltz: Optimization of ribosome P-site positioning in ribosome profiling data', 'Lauria, Fabio|Tebaldi, Toma|Bernabò, Paola|Groen, Ewout J N|Gillingwater, Thomas H|Viero, Gabriella', 'Institute of Biophysics, CNR Unit at Trento, Trento, Italy.|Centre for Integrative Biology, University of Trento, Trento, Italy.|Institute of Biophysics, CNR Unit at Trento, Trento, Italy.|Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, United Kingdom.|Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, United Kingdom.|Institute of Biophysics, CNR Unit at Trento, Trento, Italy.', 'Italy|Italy|Italy|United Kingdom|United Kingdom|Italy', 15, 'Computational Biology|High-Throughput Nucleotide Sequencing|Protein Biosynthesis|RNA, Messenger|Ribosomes|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006169', '30102689', 'Ribosome profiling is a powerful technique used to study translation at the genome-wide level, generating unique information concerning ribosome positions along RNAs. Optimal localization of ribosomes requires the proper identification of the ribosome P-site in each ribosome protected fragment, a crucial step to determine the trinucleotide periodicity of translating ribosomes, and draw correct conclusions concerning where ribosomes are located. To determine the P-site within ribosome footprints at nucleotide resolution, the precise estimation of its offset with respect to the protected fragment is necessary. Here we present riboWaltz, an R package for calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data. Compared to existing tools, riboWaltz shows improved accuracies for P-site estimation and neat ribosome positioning in multiple case studies. riboWaltz was implemented in R and is available as an R package at https://github.com/LabTranslationalArchitectomics/RiboWaltz.'),
(89185, 2018, 'plos', 'Regulation of Pom cluster dynamics in Myxococcus xanthus', 'Bergeler, Silke|Frey, Erwin', 'Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.|Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.', 'Germany|Germany', 0, 'Adenosine Triphosphatases|Bacterial Proteins|Cell Division|Cytokinesis|Cytoskeletal Proteins|Models, Theoretical|Myxococcus xanthus|Reproduction', 'Journal Article', '10.1371/journal.pcbi.1006358', '30102692', 'Precise positioning of the cell division site is essential for the correct segregation of the genetic material into the two daughter cells. In the bacterium Myxococcus xanthus, the proteins PomX and PomY form a cluster on the chromosome that performs a biased random walk to midcell and positively regulates cell division there. PomZ, an ATPase, is necessary for tethering of the cluster to the nucleoid and regulates its movement towards midcell. It has remained unclear how the cluster dynamics change when the biochemical parameters, such as the attachment rates of PomZ dimers to the nucleoid and the cluster, the ATP hydrolysis rate of PomZ or the mobility of PomZ interacting with the nucleoid and cluster, are varied. To answer these questions, we investigate a one-dimensional model that includes the nucleoid, the Pom cluster and PomZ proteins. We find that a mechanism based on the diffusive PomZ fluxes on the nucleoid into the cluster can explain the latters midnucleoid localization for a broad parameter range. Furthermore, there is an ATP hydrolysis rate that minimizes the time the cluster needs to reach midnucleoid. If the dynamics of PomZ on the nucleoid is slow relative to the clusters velocity, we observe oscillatory cluster movements around midnucleoid. To understand midnucleoid localization, we developed a semi-analytical approach that dissects the net movement of the cluster into its components: the difference in PomZ fluxes into the cluster from either side, the force exerted by a single PomZ dimer on the cluster and the effective friction coefficient of the cluster. Importantly, we predict that the Pom cluster oscillates around midnucleoid if the diffusivity of PomZ on the nucleoid is reduced. A similar approach to that applied here may also prove useful for cargo localization in ParABS systems.'),
(89186, 2018, 'plos', 'SILGGM: An extensive R package for efficient statistical inference in large-scale gene networks', 'Zhang, Rong|Ren, Zhao|Chen, Wei', 'Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Division of Pulmonary Medicine, Department of Pediatrics, Childrens Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States', 5, 'Algorithms|Animals|Base Sequence|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|High-Throughput Nucleotide Sequencing|Humans|Normal Distribution|RNA|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006369', '30102702', 'Gene co-expression network analysis is extremely useful in interpreting a complex biological process. The recent droplet-based single-cell technology is able to generate much larger gene expression data routinely with thousands of samples and tens of thousands of genes. To analyze such a large-scale gene-gene network, remarkable progress has been made in rigorous statistical inference of high-dimensional Gaussian graphical model (GGM). These approaches provide a formal confidence interval or a p-value rather than only a single point estimator for conditional dependence of a gene pair and are more desirable for identifying reliable gene networks. To promote their widespread use, we herein introduce an extensive and efficient R package named SILGGM (Statistical Inference of Large-scale Gaussian Graphical Model) that includes four main approaches in statistical inference of high-dimensional GGM. Unlike the existing tools, SILGGM provides statistically efficient inference on both individual gene pair and whole-scale gene pairs. It has a novel and consistent false discovery rate (FDR) procedure in all four methodologies. Based on the user-friendly design, it provides outputs compatible with multiple platforms for interactive network visualization. Furthermore, comparisons in simulation illustrate that SILGGM can accelerate the existing MATLAB implementation to several orders of magnitudes and further improve the speed of the already very efficient R package FastGGM. Testing results from the simulated data confirm the validity of all the approaches in SILGGM even in a very large-scale setting with the number of variables or genes to a ten thousand level. We have also applied our package to a novel single-cell RNA-seq data set with pan T cells. The results show that the approaches in SILGGM significantly outperform the conventional ones in a biological sense. The package is freely available via CRAN at https://cran.r-project.org/package=SILGGM.'),
(89187, 2018, 'plos', 'Scaling up data curation using deep learning: An application to literature triage in genomic variation resources', 'Lee, Kyubum|Famiglietti, Maria Livia|McMahon, Aoife|Wei, Chih-Hsuan|MacArthur, Jacqueline Ann Langdon|Poux, Sylvain|Breuza, Lionel|Bridge, Alan|Cunningham, Fiona|Xenarios, Ioannis|Lu, Zhiyong', 'National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.|Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.|Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.|Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Center for Integrative Genomics, University of Lausanne, Lausanne Switzerland.|National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.', 'United States|Switzerland|United Kingdom|United States|United Kingdom|Switzerland|Switzerland|Switze', 0, 'Data Curation|Databases, Genetic|Databases, Protein|Deep Learning|Genomics|Information Storage and Retrieval|Knowledge Bases|Machine Learning|Publications', 'Journal Article', '10.1371/journal.pcbi.1006390', '30102703', 'Manually curating biomedical knowledge from publications is necessary to build a knowledge based service that provides highly precise and organized information to users. The process of retrieving relevant publications for curation, which is also known as document triage, is usually carried out by querying and reading articles in PubMed. However, this query-based method often obtains unsatisfactory precision and recall on the retrieved results, and it is difficult to manually generate optimal queries. To address this, we propose a machine-learning assisted triage method. We collect previously curated publications from two databases UniProtKB/Swiss-Prot and the NHGRI-EBI GWAS Catalog, and used them as a gold-standard dataset for training deep learning models based on convolutional neural networks. We then use the trained models to classify and rank new publications for curation. For evaluation, we apply our method to the real-world manual curation process of UniProtKB/Swiss-Prot and the GWAS Catalog. We demonstrate that our machine-assisted triage method outperforms the current query-based triage methods, improves efficiency, and enriches curated content. Our method achieves a precision 1.81 and 2.99 times higher than that obtained by the current query-based triage methods of UniProtKB/Swiss-Prot and the GWAS Catalog, respectively, without compromising recall. In fact, our method retrieves many additional relevant publications that the query-based method of UniProtKB/Swiss-Prot could not find. As these results show, our machine learning-based method can make the triage process more efficient and is being implemented in production so that human curators can focus on more challenging tasks to improve the quality of knowledge bases.'),
(89188, 2018, 'plos', 'Interplay of multiple pathways and activity-dependent rules in STDP', 'Vignoud, Gaëtan|Venance, Laurent|Touboul, Jonathan D', 'Center for Interdisciplinary Research in Biology (CIRB) - Collège de France (CNRS UMR 7241, INSERM U1050), 11 Place Marcelin Berthelot, 75005 Paris, France.|Center for Interdisciplinary Research in Biology (CIRB) - Collège de France (CNRS UMR 7241, INSERM U1050), 11 Place Marcelin Berthelot, 75005 Paris, France.|Center for Interdisciplinary Research in Biology (CIRB) - Collège de France (CNRS UMR 7241, INSERM U1050), 11 Place Marcelin Berthelot, 75005 Paris, France.', 'France|France|France', 0, 'Action Potentials|Animals|Calcium Channels|Endocannabinoids|Humans|Long-Term Potentiation|Long-Term Synaptic Depression|Models, Theoretical|Neuronal Plasticity|Neurons|Receptors, N-Methyl-D-Aspartate|Signal Transduction|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006184', '30106953', 'Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.'),
(89189, 2018, 'plos', 'Integration and multiplexing of positional and contextual information by the hippocampal network', 'Posani, Lorenzo|Cocco, Simona|Monasson, Rémi', 'Laboratory of Statistical Physics, Ecole Normale Supérieure and CNRS UMR 8550, PSL Research, Paris Sorbonne UPMC, 24 rue Lhomond, 75005 Paris, France.|Laboratory of Statistical Physics, Ecole Normale Supérieure and CNRS UMR 8550, PSL Research, Paris Sorbonne UPMC, 24 rue Lhomond, 75005 Paris, France.|Laboratory of Theoretical Physics, Ecole Normale Supérieure and CNRS UMR 8549, PSL Research, Paris Sorbonne UPMC, 24 rue Lhomond, 75005 Paris, France.', 'France|France|France', 4, 'Action Potentials|Animals|CA3 Region, Hippocampal|Cues|Hippocampus|Male|Memory, Episodic|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neurons|Rats|Space Perception|Spatial Behavior', 'Journal Article', '10.1371/journal.pcbi.1006320', '30106966', 'The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and processed by the hippocampus to maintain these representations accurate over time remains unclear. To answer this question, we propose a two-way data analysis and modeling approach to CA3 multi-electrode recordings of a moving rat submitted to rapid changes of contextual (light) cues, triggering back-and-forth instabitilies between two cognitive representations (teleportation experiment of Jezek et al). We develop a dual neural activity decoder, capable of independently identifying the recalled cognitive map at high temporal resolution (comparable to theta cycle) and the position of the rodent given a map. Remarkably, position can be reconstructed at any time with an accuracy comparable to fixed-context periods, even during highly unstable periods. These findings provide evidence for the capability of the hippocampal neural activity to maintain an accurate encoding of spatial and contextual variables, while one of these variables undergoes rapid changes independently of the other. To explain this result we introduce an attractor neural network model for the hippocampal activity that process inputs from external cues and the path integrator. Our model allows us to make predictions on the frequency of the cognitive map instability, its duration, and the detailed nature of the place-cell population activity, which are validated by a further analysis of the data. Our work therefore sheds light on the mechanisms by which the hippocampal network achieves and updates multi-dimensional neural representations from various input streams.'),
(89190, 2018, 'plos', 'Accounting for non-stationarity in epidemiology by embedding time-varying parameters in stochastic models', 'Cazelles, Bernard|Champagne, Clara|Dureau, Joseph', 'Institut de Biologie de lEcole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS UMR 8197, Paris, France.|Institut de Biologie de lEcole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS UMR 8197, Paris, France.|SNIPS, Paris, France.', 'France|France|France', 0, 'Epidemiologic Methods|Epidemiology|Humans|Models, Biological|Models, Theoretical|Stochastic Processes|Time Factors|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1006211', '30110322', 'The spread of disease through human populations is complex. The characteristics of disease propagation evolve with time, as a result of a multitude of environmental and anthropic factors, this non-stationarity is a key factor in this huge complexity. In the absence of appropriate external data sources, to correctly describe the disease propagation, we explore a flexible approach, based on stochastic models for the disease dynamics, and on diffusion processes for the parameter dynamics. Using such a diffusion process has the advantage of not requiring a specific mathematical function for the parameter dynamics. Coupled with particle MCMC, this approach allows us to reconstruct the time evolution of some key parameters (average transmission rate for instance). Thus, by capturing the time-varying nature of the different mechanisms involved in disease propagation, the epidemic can be described. Firstly we demonstrate the efficiency of this methodology on a toy model, where the parameters and the observation process are known. Applied then to real datasets, our methodology is able, based solely on simple stochastic models, to reconstruct complex epidemics, such as flu or dengue, over long time periods. Hence we demonstrate that time-varying parameters can improve the accuracy of model performances, and we suggest that our methodology can be used as a first step towards a better understanding of a complex epidemic, in situation where data is limited and/or uncertain.'),
(89191, 2018, 'plos', 'MimicrEE2: Genome-wide forward simulations of Evolve and Resequencing studies', 'Vlachos, Christos|Kofler, Robert', 'Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz, Wien, Austria.|Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz, Wien, Austria.', 'Austria|Austria', 10, 'Algorithms|Animals|Base Sequence|Biological Evolution|Computational Biology|Computer Simulation|Databases, Genetic|Evolution, Molecular|Gene Expression Profiling|Gene Regulatory Networks|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006413', '30114186', 'Evolve and Resequencing (E&R) studies allow us to monitor adaptation at the genomic level. By sequencing evolving populations at regular time intervals, E&R studies promise to shed light on some of the major open questions in evolutionary biology such as the repeatability of evolution and the molecular basis of adaptation. However, data interpretation, statistical analysis and the experimental design of E&R studies increasingly require simulations of evolving populations, a task that is difficult to accomplish with existing tools, which may i) be too slow, ii) require substantial reformatting of data, iii) not support an adaptive scenario of interest or iv) not sufficiently capture the biology of the used model organism. Therefore we developed MimicrEE2, a multi-threaded Java program for genome-wide forward simulations of evolving populations. MimicrEE2 enables the convenient usage of available genomic resources, supports biological particulars of model organism frequently used in E&R studies and offers a wide range of different adaptive models (selective sweeps, polygenic adaptation, epistasis). Due to its user-friendly and efficient design MimicrEE2 will facilitate simulations of E&R studies even for small labs with limited bioinformatics expertise or computational resources. Additionally, the scripts provided for executing MimicrEE2 on a computer cluster permit the coverage even of a large parameter space. MimicrEE2 runs on any computer with Java installed. It is distributed under the GPLv3 license at https://sourceforge.net/projects/mimicree2/.'),
(89192, 2018, 'plos', 'Characterising seasonal influenza epidemiology using primary care surveillance data', 'Cope, Robert C|Ross, Joshua V|Chilver, Monique|Stocks, Nigel P|Mitchell, Lewis', 'School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.|School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.|Discipline of General Practice, The University of Adelaide, Adelaide, South Australia, Australia.|Discipline of General Practice, The University of Adelaide, Adelaide, South Australia, Australia.|School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.', 'Australia|Australia|Australia|Australia|Australia', 1, 'Adaptive Immunity|Australia|Basic Reproduction Number|Bayes Theorem|Disease Outbreaks|Humans|Influenza, Human|Models, Theoretical|Population Surveillance|Primary Health Care|Seasons', 'Journal Article', '10.1371/journal.pcbi.1006377', '30114215', 'Understanding the epidemiology of seasonal influenza is critical for healthcare resource allocation and early detection of anomalous seasons. It can be challenging to obtain high-quality data of influenza cases specifically, as clinical presentations with influenza-like symptoms may instead be cases of one of a number of alternate respiratory viruses. We use a new dataset of confirmed influenza virological data from 2011-2016, along with high-quality denominators informing a hierarchical observation process, to model seasonal influenza dynamics in New South Wales, Australia. We use approximate Bayesian computation to estimate parameters in a climate-driven stochastic epidemic model, including the basic reproduction number R0, the proportion of the population susceptible to the circulating strain at the beginning of the season, and the probability an infected individual seeks treatment. We conclude that R0 and initial population susceptibility were strongly related, emphasising the challenges of identifying these parameters. Relatively high R0 values alongside low initial population susceptibility were among the results most consistent with these data. Our results reinforce the importance of distinguishing between R0 and the effective reproduction number (Re) in modelling studies.'),
(89193, 2018, 'plos', 'Exploring of the feature space of de novo developed post-transcriptional riboregulators', 'Peters, Gert|Maertens, Jo|Lammertyn, Jeroen|De Mey, Marjan', 'Centre for Synthetic Biology, Ghent University, Ghent, Belgium.|Centre for Synthetic Biology, Ghent University, Ghent, Belgium.|BIOSYST-MeBioS, KU Leuven, Leuven, Belgium.|Centre for Synthetic Biology, Ghent University, Ghent, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 1, 'Escherichia coli|Escherichia coli Proteins|Gene Expression|Gene Expression Regulation|Genes, Regulator|Metabolic Engineering|Nucleic Acid Conformation|Protein Engineering|RNA|RNA Processing, Post-Transcriptional|Repressor Proteins', 'Journal Article', '10.1371/journal.pcbi.1006170', '30118473', 'Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.'),
(89194, 2018, 'plos', 'How ecological feedbacks between human population and land cover influence sustainability', 'Henderson, Kirsten|Loreau, Michel', 'Centre for Biodiversity, Theory, and Modelling, Theoretical and Experimental Ecology Station, CNRS, Moulis, France.|Centre for Biodiversity, Theory, and Modelling, Theoretical and Experimental Ecology Station, CNRS, Moulis, France.', 'France|France', 0, 'Agriculture|Biodiversity|Computer Simulation|Conservation of Natural Resources|Demography|Earth (Planet)|Ecology|Ecosystem|Environment|Food Supply|Forecasting|Humans|Population Dynamics|Population Growth|Sustainable Growth', 'Journal Article', '10.1371/journal.pcbi.1006389', '30118474', 'It is estimated that the Earths biocapacity is unable to meet current demands, which begs the question: is a sustainable future possible for both humans and the environment? The UN projects a human population of approximately 11 billion by the end of the 21st century, requiring additional agricultural land, greater demands for natural resources, and technological advancements. We model human population over the next century, emphasizing feedbacks between natural and agricultural resource availability and human demography. We argue that an intensive agriculture approach to feeding the growing population is ill-conceived, without considering biodiversity and ecosystem services (e.g., nutrient cycling, pollination, water purification, pest control). The productivity of agricultural land and human population dynamics are dependent on the area of natural land-generally, tipping at 5 billion ha of natural land (approximately 40% of the Earths terrestrial area). Furthermore, our model shows that an imprudent proactive approach (i.e., focusing on agriculture and ignoring ecosystem services) limits the success of reactive measures (i.e., restoration) in the future, while the inability to react to changes and recover natural systems leads to human population decline.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89195, 2018, 'plos', 'ggsashimi: Sashimi plot revised for browser- and annotation-independent splicing visualization', 'Garrido-Martín, Diego|Palumbo, Emilio|Guigó, Roderic|Breschi, Alessandra', 'Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 14, 'Alternative Splicing|Animals|Computational Biology|Computers|Genome|Genomics|Humans|RNA Splicing|Sequence Analysis, RNA|Single-Cell Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1006360', '30118475', 'We present ggsashimi, a command-line tool for the visualization of splicing events across multiple samples. Given a specified genomic region, ggsashimi creates sashimi plots for individual RNA-seq experiments as well as aggregated plots for groups of experiments, a feature unique to this software. Compared to the existing versions of programs generating sashimi plots, it uses popular bioinformatics file formats, it is annotation-independent, and allows the visualization of splicing events even for large genomic regions by scaling down the genomic segments between splice sites. ggsashimi is freely available at https://github.com/guigolab/ggsashimi. It is implemented in python, and internally generates R code for plotting.'),
(89196, 2018, 'plos', 'The role of curvature feedback in the energetics and dynamics of lamprey swimming: A closed-loop model', 'Hamlet, Christina L|Hoffman, Kathleen A|Tytell, Eric D|Fauci, Lisa J', 'Department of Mathematics, Bucknell University, Lewisburg, Pennsylvania, United States of America.|Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, Maryland, United States of America.|Department of Biology, Tufts University, Medford, Massachusetts, United States of America.|Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America.', 'United States|United States|United States|United States', 3, 'Animals|Biomechanical Phenomena|Central Pattern Generators|Computer Simulation|Feedback|Lampreys|Locomotion|Models, Biological|Muscles|Nerve Net|Spinal Cord|Swimming', 'Journal Article', '10.1371/journal.pcbi.1006324', '30118476', 'Like other animals, lampreys have a central pattern generator (CPG) circuit that activates muscles for locomotion and also adjusts the activity to respond to sensory inputs from the environment. Such a feedback system is crucial for responding appropriately to unexpected perturbations, but it is also active during normal unperturbed steady swimming and influences the baseline swimming pattern. In this study, we investigate different functional forms of body curvature-based sensory feedback and evaluate their effects on steady swimming energetics and kinematics, since little is known experimentally about the functional form of curvature feedback. The distributed CPG is modeled as chains of coupled oscillators. Pairs of phase oscillators represent the left and right sides of segments along the lamprey body. These activate muscles that flex the body and move the lamprey through a fluid environment, which is simulated using a full Navier-Stokes model. The emergent curvature of the body then serves as an input to the CPG oscillators, closing the loop. We consider two forms of feedback, each consistent with experimental results on lamprey proprioceptive sensory receptors. The first, referred to as directional feedback, excites or inhibits the oscillators on the same side, depending on the sign of a chosen gain parameter, and has the opposite effect on oscillators on the opposite side. We find that directional feedback does not affect beat frequency, but does change the duration of muscle activity. The second feedback model, referred to as magnitude feedback, provides a symmetric excitatory or inhibitory effect to oscillators on both sides. This model tends to increase beat frequency and reduces the energetic cost to the lamprey when the gain is high and positive. With both types of feedback, the body curvature has a similar magnitude. Thus, these results indicate that the same magnitude of curvature-based feedback on the CPG with different functional forms can cause distinct differences in swimming performance.'),
(89197, 2018, 'plos', 'Unraveling the mechanism of the cadherin-catenin-actin catch bond', 'Adhikari, Shishir|Moran, Jacob|Weddle, Christopher|Hinczewski, Michael', 'Department of Physics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Physics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Physics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Physics, Case Western Reserve University, Cleveland, Ohio, United States of America.', 'United States|United States|United States|United States', 1, 'Actin Cytoskeleton|Actins|Adherens Junctions|Animals|Cadherins|Catenins|Cell Adhesion|Computer Simulation|Epithelial Cells|Humans|Mechanotransduction, Cellular|Models, Theoretical|Protein Binding|Protein Domains|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1006399', '30118477', 'The adherens junctions between epithelial cells involve a protein complex formed by E-cadherin, xcexb2-catenin, xcexb1-catenin and F-actin. The stability of this complex was a puzzle for many years, since in vitro studies could reconstitute various stable subsets of the individual proteins, but never the entirety. The missing ingredient turned out to be mechanical tension: a recent experiment that applied physiological forces to the complex with an optical tweezer dramatically increased its lifetime, a phenomenon known as catch bonding. However, in the absence of a crystal structure for the full complex, the microscopic details of the catch bond mechanism remain mysterious. Building on structural clues that point to xcexb1-catenin as the force transducer, we present a quantitative theoretical model for how the catch bond arises, fully accounting for the experimental lifetime distributions. The underlying hypothesis is that force induces a rotational transition between two conformations of xcexb1-catenin, overcoming a significant energy barrier due to a network of salt bridges. This transition allosterically regulates the energies at the interface between xcexb1-catenin and F-actin. The model allows us to predict these energetic changes, as well as highlighting the importance of the salt bridge rotational barrier. By stabilizing one of the xcexb1-catenin states, this barrier could play a role in how the complex responds to additional in vivo binding partners like vinculin. Since significant conformational energy barriers are a common feature of other adhesion systems that exhibit catch bonds, our model can be adapted into a general theoretical framework for integrating structure and function in a variety of force-regulated protein complexes.'),
(89198, 2018, 'plos', 'Domes and cones: Adhesion-induced fission of membranes by ESCRT proteins', 'Agudo-Canalejo, Jaime|Lipowsky, Reinhard', 'Theory & Bio-Systems Department, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.|Theory & Bio-Systems Department, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.', 'Germany|Germany', 9, 'Animals|Biophysical Phenomena|Cell Membrane|Computer Simulation|Cytokinesis|Endocytosis|Endosomal Sorting Complexes Required for Transport|Endosomes|Humans|Intracellular Membranes', 'Journal Article', '10.1371/journal.pcbi.1006422', '30130367', 'ESCRT proteins participate in the fission step of exocytic membrane budding, by assisting in the closure and scission of the membrane neck that connects the nascent bud to the plasma membrane. However, the precise mechanism by which the proteins achieve this so-called reverse-topology membrane scission remains to be elucidated. One mechanism is described by the dome model, which postulates that ESCRT-III proteins assemble in the shape of a hemispherical dome at the location of the neck, and guide the closure of this neck via membrane-protein adhesion. A different mechanism is described by the flattening cone model, in which the ESCRT-III complex first assembles at the neck in the shape of a cone, which then flattens leading to neck closure. Here, we use the theoretical framework of curvature elasticity and membrane-protein adhesion to quantitatively describe and compare both mechanisms. This comparison shows that the minimal adhesive strength of the membrane-protein interactions required for scission is much lower for cones than for domes, and that the geometric constraints on the shape of the assembly required to induce scission are more stringent for domes than for cones. Finally, we compute for the first time the adhesion-induced constriction forces exerted by the ESCRT assemblies onto the membrane necks. These forces are higher for cones and of the order of 100 pN.'),
(89199, 2018, 'plos', 'Lineage space and the propensity of bacterial cells to undergo growth transitions', 'Bandyopadhyay, Arnab|Wang, Huijing|Ray, J Christian J', 'Center for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.|Center for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.|Center for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.', 'United States|United States|United States', 3, 'Anti-Bacterial Agents|Bacteria|Bacterial Physiological Phenomena|Cell Growth Processes|Cell Proliferation|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Regulatory Networks|Models, Genetic|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1006380', '30133447', 'The molecular makeup of the offspring of a dividing cell gradually becomes phenotypically decorrelated from the parent cell by noise and regulatory mechanisms that amplify phenotypic heterogeneity. Such regulatory mechanisms form networks that contain thresholds between phenotypes. Populations of cells can be poised near the threshold so that a subset of the population probabilistically undergoes the phenotypic transition. We sought to characterize the diversity of bacterial populations around a growth-modulating threshold via analysis of the effect of non-genetic inheritance, similar to conditions that create antibiotic-tolerant persister cells and other examples of bet hedging. Using simulations and experimental lineage data in Escherichia coli, we present evidence that regulation of growth amplifies the dependence of growth arrest on cellular lineage, causing clusters of related cells undergo growth arrest in certain conditions. Our simulations predict that lineage correlations and the sensitivity of growth to changes in toxin levels coincide in a critical regime. Below the critical regime, the sizes of related growth arrested clusters are distributed exponentially, while in the critical regime clusters sizes are more likely to become large. Furthermore, phenotypic diversity can be nearly as high as possible near the critical regime, but for most parameter values it falls far below the theoretical limit. We conclude that lineage information is indispensable for understanding regulation of cellular growth.'),
(89200, 2018, 'plos', 'NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics', 'Sanz-Leon, Paula|Robinson, Peter A|Knock, Stuart A|Drysdale, Peter M|Abeysuriya, Romesh G|Fung, Felix K|Rennie, Chris J|Zhao, Xuelong', 'School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.|School of Physics, University of Sydney, Sydney, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 9, 'Algorithms|Animals|Axons|Brain|Computational Biology|Gene Regulatory Networks|Humans|Models, Theoretical|Nerve Net|Neurons|Normal Distribution|Software', 'Journal Article', '10.1371/journal.pcbi.1006387', '30133448', 'A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license.'),
(89201, 2018, 'plos', 'Inferring hidden structure in multilayered neural circuits', 'Maheswaranathan, Niru|Kastner, David B|Baccus, Stephen A|Ganguli, Surya', 'Neurosciences Graduate Program, Stanford University, Stanford, California, United States of America.|Neurosciences Graduate Program, Stanford University, Stanford, California, United States of America.|Department of Neurobiology, Stanford University, Stanford, California, United States of America.|Department of Applied Physics, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States', 20, 'Action Potentials|Algorithms|Ambystoma|Animals|Models, Neurological|Models, Theoretical|Nerve Net|Nonlinear Dynamics|Photic Stimulation|Retina|Retinal Ganglion Cells', 'Journal Article', '10.1371/journal.pcbi.1006291', '30138312', 'A central challenge in sensory neuroscience involves understanding how neural circuits shape computations across cascaded cell layers. Here we attempt to reconstruct the response properties of experimentally unobserved neurons in the interior of a multilayered neural circuit, using cascaded linear-nonlinear (LN-LN) models. We combine non-smooth regularization with proximal consensus algorithms to overcome difficulties in fitting such models that arise from the high dimensionality of their parameter space. We apply this framework to retinal ganglion cell processing, learning LN-LN models of retinal circuitry consisting of thousands of parameters, using 40 minutes of responses to white noise. Our models demonstrate a 53% improvement in predicting ganglion cell spikes over classical linear-nonlinear (LN) models. Internal nonlinear subunits of the model match properties of retinal bipolar cells in both receptive field structure and number. Subunits have consistently high thresholds, supressing all but a small fraction of inputs, leading to sparse activity patterns in which only one subunit drives ganglion cell spiking at any time. From the models parameters, we predict that the removal of visual redundancies through stimulus decorrelation across space, a central tenet of efficient coding theory, originates primarily from bipolar cell synapses. Furthermore, the composite nonlinear computation performed by retinal circuitry corresponds to a boolean OR function applied to bipolar cell feature detectors. Our methods are statistically and computationally efficient, enabling us to rapidly learn hierarchical non-linear models as well as efficiently compute widely used descriptive statistics such as the spike triggered average (STA) and covariance (STC) for high dimensional stimuli. This general computational framework may aid in extracting principles of nonlinear hierarchical sensory processing across diverse modalities from limited data.'),
(89202, 2018, 'plos', 'Calcium imaging and dynamic causal modelling reveal brain-wide changes in effective connectivity and synaptic dynamics during epileptic seizures', 'Rosch, Richard E|Hunter, Paul R|Baldeweg, Torsten|Friston, Karl J|Meyer, Martin P', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Department of Developmental Neurobiology & MRC Center for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Developmental Neurosciences Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Department of Developmental Neurobiology & MRC Center for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 10, 'Animals|Bayes Theorem|Brain|Calcium|Connectome|Electroencephalography|Epilepsy|Larva|Models, Neurological|Nerve Net|Neurons|Seizures|Synaptic Transmission|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1006375', '30138336', 'Pathophysiological explanations of epilepsy typically focus on either the micro/mesoscale (e.g. excitation-inhibition imbalance), or on the macroscale (e.g. network architecture). Linking abnormalities across spatial scales remains difficult, partly because of technical limitations in measuring neuronal signatures concurrently at the scales involved. Here we use light sheet imaging of the larval zebrafish brain during acute epileptic seizure induced with pentylenetetrazole. Spectral changes of spontaneous neuronal activity during the seizure are then modelled using neural mass models, allowing Bayesian inference on changes in effective network connectivity and their underlying synaptic dynamics. This dynamic causal modelling of seizures in the zebrafish brain reveals concurrent changes in synaptic coupling at macro- and mesoscale. Fluctuations of both synaptic connection strength and their temporal dynamics are required to explain observed seizure patterns. These findings highlight distinct changes in local (intrinsic) and long-range (extrinsic) synaptic transmission dynamics as a possible seizure pathomechanism and illustrate how our Bayesian model inversion approach can be used to link existing neural mass models of seizure activity and novel experimental methods.'),
(89203, 2018, 'plos', 'coTRaCTE predicts co-occurring transcription factors within cell-type specific enhancers', 'van Bömmel, Alena|Love, Michael I|Chung, Ho-Ryun|Vingron, Martin', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Biostatistics, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Otto Warburg Laboratory, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.', 'Germany|United States|Germany|Germany', 2, 'Algorithms|Binding Sites|Chromatin|Chromatin Assembly and Disassembly|Computer Simulation|Enhancer Elements, Genetic|Forecasting|Gene Expression Regulation|Humans|Promoter Regions, Genetic|Protein Binding|Regulatory Sequences, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006372', '30142147', 'Cell-type specific gene expression is regulated by the combinatorial action of transcription factors (TFs). In this study, we predict transcription factor (TF) combinations that cooperatively bind in a cell-type specific manner. We first divide DNase hypersensitive sites into cell-type specifically open vs. ubiquitously open sites in 64 cell types to describe possible cell-type specific enhancers. Based on the pattern contrast between these two groups of sequences we develop co-occurring TF predictor on Cell-Type specific Enhancers (coTRaCTE) - a novel statistical method to determine regulatory TF co-occurrences. Contrasting the co-binding of TF pairs between cell-type specific and ubiquitously open chromatin guarantees the high cell-type specificity of the predictions. coTRaCTE predicts more than 2000 co-occurring TF pairs in 64 cell types. The large majority (70%) of these TF pairs is highly cell-type specific and overlaps in TF pair co-occurrence are highly consistent among related cell types. Furthermore, independently validated co-occurring and directly interacting TFs are significantly enriched in our predictions. Focusing on the regulatory network derived from the predicted co-occurring TF pairs in embryonic stem cells (ESCs) we find that it consists of three subnetworks with distinct functions: maintenance of pluripotency governed by OCT4, SOX2 and NANOG, regulation of early development governed by KLF4, STAT3, ZIC3 and ZNF148 and general functions governed by MYC, TCF3 and YY1. In summary, coTRaCTE predicts highly cell-type specific co-occurring TFs which reveal new insights into transcriptional regulatory mechanisms.'),
(89204, 2018, 'plos', 'Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner', 'Silvetti, Massimo|Vassena, Eliana|Abrahamse, Elger|Verguts, Tom', 'Department of Experimental Psychology, Ghent University, Ghent, Belgium.|Department of Experimental Psychology, Ghent University, Ghent, Belgium.|Department of Experimental Psychology, Ghent University, Ghent, Belgium.|Department of Experimental Psychology, Ghent University, Ghent, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 17, 'Animals|Brain Mapping|Brain Stem|Cognition|Computer Simulation|Decision Making|Gyrus Cinguli|Humans|Learning|Locus Coeruleus|Models, Theoretical|Reinforcement (Psychology)|Reward|Ventral Tegmental Area', 'Journal Article', '10.1371/journal.pcbi.1006370', '30142152', 'Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model-the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.'),
(89205, 2018, 'plos', 'MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction', 'Chen, Xing|Yin, Jun|Qu, Jia|Huang, Li', 'School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|Business Analytics Centre, National University of Singapore, Singapore.', 'China|China|China|Singapore', 117, 'Algorithms|Animals|Biological Evolution|Computational Biology|Computer Simulation|Databases, Genetic|Esophageal Neoplasms|Evolution, Molecular|Forecasting|Genetic Association Studies|Genetic Predisposition to Disease|Genome|Genomics|Humans|Lung Neoplasms|Lymphoma|MicroRNAs|Models, Genetic|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006418', '30142158', 'Recently, a growing number of biological research and scientific experiments have demonstrated that microRNA (miRNA) affects the development of human complex diseases. Discovering miRNA-disease associations plays an increasingly vital role in devising diagnostic and therapeutic tools for diseases. However, since uncovering associations via experimental methods is expensive and time-consuming, novel and effective computational methods for association prediction are in demand. In this study, we developed a computational model of Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction (MDHGI) to discover new miRNA-disease associations by integrating the predicted association probability obtained from matrix decomposition through sparse learning method, the miRNA functional similarity, the disease semantic similarity, and the Gaussian interaction profile kernel similarity for diseases and miRNAs into a heterogeneous network. Compared with previous computational models based on heterogeneous networks, our model took full advantage of matrix decomposition before the construction of heterogeneous network, thereby improving the prediction accuracy. MDHGI obtained AUCs of 0.8945 and 0.8240 in the global and the local leave-one-out cross validation, respectively. Moreover, the AUC of 0.8794+/-0.0021 in 5-fold cross validation confirmed its stability of predictive performance. In addition, to further evaluate the models accuracy, we applied MDHGI to four important human cancers in three different kinds of case studies. In the first type, 98% (Esophageal Neoplasms) and 98% (Lymphoma) of top 50 predicted miRNAs have been confirmed by at least one of the two databases (dbDEMC and miR2Disease) or at least one experimental literature in PubMed. In the second type of case study, what made a difference was that we removed all known associations between the miRNAs and Lung Neoplasms before implementing MDHGI on Lung Neoplasms. As a result, 100% (Lung Neoplasms) of top 50 related miRNAs have been indexed by at least one of the three databases (dbDEMC, miR2Disease and HMDD V2.0) or at least one experimental literature in PubMed. Furthermore, we also tested our prediction method on the HMDD V1.0 database to prove the applicability of MDHGI to different datasets. The results showed that 50 out of top 50 miRNAs related with the breast neoplasms were validated by at least one of the three databases (HMDD V2.0, dbDEMC, and miR2Disease) or at least one experimental literature.'),
(89206, 2018, 'plos', 'Identification of excitatory-inhibitory links and network topology in large-scale neuronal assemblies from multi-electrode recordings', 'Pastore, Vito Paolo|Massobrio, Paolo|Godjoski, Aleksandar|Martinoia, Sergio', 'University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.', 'Italy|Italy|Italy|Italy', 1, 'Action Potentials|Animals|Cerebral Cortex|Connectome|Electrodes|Excitatory Postsynaptic Potentials|Inhibitory Postsynaptic Potentials|Interneurons|Nerve Net|Neurons|Rats|Rats, Sprague-Dawley', 'Journal Article', '10.1371/journal.pcbi.1006381', '30148879', 'Functional-effective connectivity and network topology are nowadays key issues for studying brain physiological functions and pathologies. Inferring neuronal connectivity from electrophysiological recordings presents open challenges and unsolved problems. In this work, we present a cross-correlation based method for reliably estimating not only excitatory but also inhibitory links, by analyzing multi-unit spike activity from large-scale neuronal networks. The method is validated by means of realistic simulations of large-scale neuronal populations. New results related to functional connectivity estimation and network topology identification obtained by experimental electrophysiological recordings from high-density and large-scale (i.e., 4096 electrodes) microtransducer arrays coupled to in vitro neural populations are presented. Specifically, we show that: (i) functional inhibitory connections are accurately identified in in vitro cortical networks, providing that a reasonable firing rate and recording length are achieved, (ii) small-world topology, with scale-free and rich-club features are reliably obtained, on condition that a minimum number of active recording sites are available. The method and procedure can be directly extended and applied to in vivo multi-units brain activity recordings.'),
(89207, 2018, 'plos', 'Correction: Subgraphs of functional brain networks identify dynamical constraints of cognitive control', 'Khambhati, Ankit N|Medaglia, John D|Karuza, Elisabeth A|Thompson-Schill, Sharon L|Bassett, Danielle S', 'University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.|University of Genova, Dept. of Informatics, Bioengineering, Robotics and System Engineering, Genova, Italy.', 'Italy|Italy|Italy|Italy|Italy', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1006420', '30153248', '[This corrects the article DOI: 10.1371/journal.pcbi.1006234.].'),
(89208, 2018, 'plos', 'General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain', 'Zappacosta, Stefano|Mannella, Francesco|Mirolli, Marco|Baldassarre, Gianluca', 'Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council of Italy (LOCEN-ISTC-CNR), Roma, Italy.|Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council of Italy (LOCEN-ISTC-CNR), Roma, Italy.|Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council of Italy (LOCEN-ISTC-CNR), Roma, Italy.|Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council of Italy (LOCEN-ISTC-CNR), Roma, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Action Potentials|Biophysical Phenomena|Brain|Computer Simulation|Humans|Learning|Models, Theoretical|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006227', '30153263', 'Learning in biologically relevant neural-network models usually relies on Hebb learning rules. The typical implementations of these rules change the synaptic strength on the basis of the co-occurrence of the neural events taking place at a certain time in the pre- and post-synaptic neurons. Differential Hebbian learning (DHL) rules, instead, are able to update the synapse by taking into account the temporal relation, captured with derivatives, between the neural events happening in the recent past. The few DHL rules proposed so far can update the synaptic weights only in few ways: this is a limitation for the study of dynamical neurons and neural-network models. Moreover, empirical evidence on brain spike-timing-dependent plasticity (STDP) shows that different neurons express a surprisingly rich repertoire of different learning processes going far beyond existing DHL rules. This opens up a second problem of how capturing such processes with DHL rules. Here we propose a general DHL (G-DHL) rule generating the existing rules and many others. The rule has a high expressiveness as it combines in different ways the pre- and post-synaptic neuron signals and derivatives. The rule flexibility is shown by applying it to various signals of artificial neurons and by fitting several different STDP experimental data sets. To these purposes, we propose techniques to pre-process the neural signals and capture the temporal relations between the neural events of interest. We also propose a procedure to automatically identify the rule components and parameters that best fit different STDP data sets, and show how the identified components might be used to heuristically guide the search of the biophysical mechanisms underlying STDP. Overall, the results show that the G-DHL rule represents a useful means to study time-sensitive learning processes in both artificial neural networks and brain.'),
(89209, 2018, 'plos', 'New methods for computational decomposition of whole-mount in situ images enable effective curation of a large, highly redundant collection of Xenopus images', 'Patrushev, Ilya|James-Zorn, Christina|Ciau-Uitz, Aldo|Patient, Roger|Gilchrist, Michael J', 'The Francis Crick Institute, London, United Kingdom.|Cincinnati Childrens Hospital, Division of Developmental Biology, Cincinnati, Ohio.|MRC Molecular Haematology Unit, The Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford.|MRC Molecular Haematology Unit, The Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford.|The Francis Crick Institute, London, United Kingdom.', 'United Kingdom|-|-|-|United Kingdom', 0, 'Animals|Computational Biology|Data Curation|Embryo, Nonmammalian|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Developmental|Image Processing, Computer-Assisted|In Situ Hybridization|In Situ Hybridization, Fluorescence|Software|Transcriptome|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1006077', '30157169', 'The precise anatomical location of gene expression is an essential component of the study of gene function. For most model organisms this task is usually undertaken via visual inspection of gene expression images by interested researchers. Computational analysis of gene expression has been developed in several model organisms, notably in Drosophila which exhibits a uniform shape and outline in the early stages of development. Here we address the challenge of computational analysis of gene expression in Xenopus, where the range of developmental stages of interest encompasses a wide range of embryo size and shape. Embryos may have different orientation across images, and, in addition, embryos have a pigmented epidermis that can mask or confuse underlying gene expression. Here we report the development of a set of computational tools capable of processing large image sets with variable characteristics. These tools efficiently separate the Xenopus embryo from the background, separately identify both histochemically stained and naturally pigmented regions within the embryo, and can sort images from the same gene and developmental stage according to similarity of gene expression patterns without information about relative orientation. We tested these methods on a large, but highly redundant, collection of 33,289 in situ hybridization images, allowing us to select representative images of expression patterns at different embryo orientations. This has allowed us to put a much smaller subset of these images into the public domain in an effective manner. The isimage module and the scripts developed are implemented in Python and freely available on https://pypi.python.org/pypi/isimage/.'),
(89210, 2018, 'plos', 'Mechanisms of hysteresis in human brain networks during transitions of consciousness and unconsciousness: Theoretical principles and empirical evidence', 'Kim, Hyoungkyu|Moon, Joon-Young|Mashour, George A|Lee, UnCheol', 'Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America.', 'United States|United States|United States|United States', 9, 'Adult|Anesthetics, General|Brain|Connectome|Consciousness|Cortical Synchronization|Electroencephalography|Electroencephalography Phase Synchronization|Female|Healthy Volunteers|Humans|Ketamine|Male|Nerve Net|Sevoflurane|Unconsciousness', 'Journal Article', '10.1371/journal.pcbi.1006424', '30161118', 'Hysteresis, the discrepancy in forward and reverse pathways of state transitions, is observed during changing levels of consciousness. Identifying the underlying mechanism of hysteresis phenomena in the brain will enhance the ability to understand, monitor, and control state transitions related to consciousness. We hypothesized that hysteresis in brain networks shares the same underlying mechanism of hysteresis as other biological and non-biological networks. In particular, we hypothesized that the principle of explosive synchronization, which can mediate abrupt state transitions, would be critical to explaining hysteresis in the brain during conscious state transitions. We analyzed high-density electroencephalogram (EEG) that was acquired in healthy human volunteers during conscious state transitions induced by the general anesthetics sevoflurane or ketamine. We developed a novel method to monitor the temporal evolution of EEG networks in a parameter space, which consists of the strength and topography of EEG-based networks. Furthermore, we studied conditions of explosive synchronization in anatomically informed human brain network models. We identified hysteresis in the trajectory of functional brain networks during state transitions. The model study and empirical data analysis explained various hysteresis phenomena during the loss and recovery of consciousness in a principled way: (1) more potent anesthetics induce a larger hysteresis, (2) a larger range of EEG frequencies facilitates transitions into unconsciousness and impedes the return of consciousness, (3) hysteresis of connectivity is larger than that of EEG power, and (4) the structure and strength of functional brain networks reconfigure differently during the loss vs. recovery of consciousness. We conclude that the hysteresis phenomena observed during the loss and recovery of consciousness are generic network features. Furthermore, the state transitions are grounded in the same principle as state transitions in complex non-biological networks, especially during perturbation. These findings suggest the possibility of predicting and modulating hysteresis of conscious state transitions in large-scale brain networks.'),
(89211, 2018, 'plos', 'The low spike density of HIV may have evolved because of the effects of T helper cell depletion on affinity maturation', 'Amitai, Assaf|Chakraborty, Arup K|Kardar, Mehran', 'Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Antibodies, Neutralizing|HIV|HIV Antibodies|HIV Envelope Protein gp120|HIV Infections|Humans|T-Lymphocytes, Helper-Inducer|Viral Structures', 'Journal Article', '10.1371/journal.pcbi.1006408', '30161121', 'The spikes on virus surfaces bind receptors on host cells to propagate infection. High spike densities (SDs) can promote infection, but spikes are also targets of antibody-mediated immune responses. Thus, diverse evolutionary pressures can influence virus SDs. HIVs SD is about two orders of magnitude lower than that of other viruses, a surprising feature of unknown origin. By modeling antibody evolution through affinity maturation, we find that an intermediate SD maximizes the affinity of generated antibodies. We argue that this leads most viruses to evolve high SDs. T helper cells, which are depleted during early HIV infection, play a key role in antibody evolution. We find that T helper cell depletion results in high affinity antibodies when SD is high, but not if SD is low. This special feature of HIV infection may have led to the evolution of a low SD to avoid potent immune responses early in infection.'),
(89212, 2018, 'plos', 'Interactive implementations of thermodynamics-based RNA structure and RNA-RNA interaction prediction approaches for example-driven teaching', 'Raden, Martin|Mohamed, Mostafa Mahmoud|Ali, Syed Mohsin|Backofen, Rolf', 'Chair of Forest Growth and Dendroecology, University of Freiburg, Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany.', 'Germany|Germany|Germany|Germany', 5, 'Algorithms|Forecasting|Internet|Nucleic Acid Conformation|RNA|RNA Folding|Sequence Analysis, RNA|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006341', '30161123', 'The investigation of RNA-based regulation of cellular processes is becoming an increasingly important part of biological or medical research. For the analysis of this type of data, RNA-related prediction tools are integrated into many pipelines and workflows. In order to correctly apply and tune these programs, the user has to have a precise understanding of their limitations and concepts. Within this manuscript, we provide the mathematical foundations and extract the algorithmic ideas that are core to state-of-the-art RNA structure and RNA-RNA interaction prediction algorithms. To allow the reader to change and adapt the algorithms or to play with different inputs, we provide an open-source web interface to JavaScript implementations and visualizations of each algorithm. The conceptual, teaching-focused presentation enables a high-level survey of the approaches, while providing sufficient details for understanding important concepts. This is boosted by the simple generation and study of examples using the web interface available at http://rna.informatik.uni-freiburg.de/Teaching/. In combination, we provide a valuable resource for teaching, learning, and understanding the discussed prediction tools and thus enable a more informed analysis of RNA-related effects.'),
(89213, 2018, 'plos', 'Ten simple rules for measuring the impact of workshops', 'Sufi, Shoaib|Nenadic, Aleksandra|Silva, Raniere|Duckles, Beth|Simera, Iveta|de Beyer, Jennifer A|Struthers, Caroline|Nurmikko-Fuller, Terhi|Bellis, Louisa|Miah, Wadud|Wilde, Adriana|Emsley, Iain|Philippe, Olivier|Balzano, Melissa|Coelho, Sara|Ford, Heather|Jones, Catherine|Higgins, Vanessa', 'School of Computer Science, University of Manchester, Manchester, United Kingdom.|School of Computer Science, University of Manchester, Manchester, United Kingdom.|School of Computer Science, University of Manchester, Manchester, United Kingdom.|Portland State University, Portland, Oregon, United States of America.|UK EQUATOR Centre, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.|UK EQUATOR Centre, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.|UK EQUATOR Centre, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.|College of Arts and Social Sciences, Australian National University, Canberra, Australia.|Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom.|Numerical Algorithms Group, Oxford, United Kingdom.|School of Computer Science, University of St. Andrews, St. Andrews, Scotland, United Kingdom.|Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom.|Electronics and Computer Science, University of Southampton, Southampton, United Kingdom.|ELIXIR Hub, Wellcome Genome Campus, Cambridge, United Kingdom.|EGI Foundation, Amsterdam, the Netherlands.|School of Media and Communication, University of Leeds, Leeds, United Kingdom.|Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot, United Kingdom.|School of Social Sciences, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|United Kingdom|United Kingdom|United King', 2, 'Education|Humans|Knowledge|Learning|Research|Weights and Measures', 'Editorial', '10.1371/journal.pcbi.1006191', '30161124', 'Workshops are used to explore a specific topic, to transfer knowledge, to solve identified problems, or to create something new. In funded research projects and other research endeavours, workshops are the mechanism used to gather the wider project, community, or interested people together around a particular topic. However, natural questions arise: how do we measure the impact of these workshops? Do we know whether they are meeting the goals and objectives we set for them? What indicators should we use? In response to these questions, this paper will outline rules that will improve the measurement of the impact of workshops.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89214, 2018, 'plos', 'Norepinephrine stimulates glycogenolysis in astrocytes to fuel neurons with lactate', 'Coggan, Jay S|Keller, Daniel|Calì, Corrado|Lehväslaiho, Heikki|Markram, Henry|Schürmann, Felix|Magistretti, Pierre J', 'Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.|Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.|Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.', 'Switzerland|Switzerland|Saudi Arabia|Saudi Arabia|Switzerland|Switzerland|Switzerland', 0, 'Animals|Astrocytes|Brain|Computer Simulation|Cyclic AMP|Energy Metabolism|Glucose|Glycogen|Glycogenolysis|Glycolysis|Humans|Lactic Acid|Models, Neurological|Neurons|Neurotransmitter Agents|Norepinephrine', 'Journal Article', '10.1371/journal.pcbi.1006392', '30161133', 'The mechanism of rapid energy supply to the brain, especially to accommodate the heightened metabolic activity of excited states, is not well-understood. We explored the role of glycogen as a fuel source for neuromodulation using the noradrenergic stimulation of glia in a computational model of the neural-glial-vasculature ensemble (NGV). The detection of norepinephrine (NE) by the astrocyte and the coupled cAMP signal are rapid and largely insensitive to the distance of the locus coeruleus projection release sites from the glia, implying a diminished impact for volume transmission in high affinity receptor transduction systems. Glucosyl-conjugated units liberated from glial glycogen by NE-elicited cAMP second messenger transduction winds sequentially through the glycolytic cascade, generating robust increases in NADH and ATP before pyruvate is finally transformed into lactate. This astrocytic lactate is rapidly exported by monocarboxylate transporters to the associated neuron, demonstrating that the astrocyte-to-neuron lactate shuttle activated by glycogenolysis is a likely fuel source for neuromodulation and enhanced neural activity. Altogether, the energy supply for both astrocytes and neurons can be supplied rapidly by glycogenolysis upon neuromodulatory stimulus.'),
(89215, 2018, 'plos', 'A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila', 'Liu, Guangda|Nath, Tanmay|Linneweber, Gerit A|Claeys, Annelies|Guo, Zhengyu|Li, Jin|Bengochea, Mercedes|De Backer, Steve|Weyn, Barbara|Sneyders, Manu|Nicasy, Hans|Yu, Peng|Scheunders, Paul|Hassan, Bassem A', 'VIB Center for the Biology of Disease, VIB, Leuven, Belgium.|IMEC-Vision Lab, University of Antwerp, Antwerp, Belgium.|VIB Center for the Biology of Disease, VIB, Leuven, Belgium.|VIB Center for the Biology of Disease, VIB, Leuven, Belgium.|Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering (CBGSE), Texas A&M University, College Station, Texas, United States of America.|Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering (CBGSE), Texas A&M University, College Station, Texas, United States of America.|Institut du Cerveau et de la Moelle Epinière (ICM) - Hôpital Pitié-Salpêtrière, Sorbonne Université, Inserm, CNRS, Paris, France.|DCILabs, Keerbergen, Belgium.|DCILabs, Keerbergen, Belgium.|Peira bvba, Turnhout, Belgium.|Peira bvba, Turnhout, Belgium.|Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering (CBGSE), Texas A&M University, College Station, Texas, United States of America.|IMEC-Vision Lab, University of Antwerp, Antwerp, Belgium.|VIB Center for the Biology of Disease, VIB, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|United States|United States|France|Belgium|Belgium|Belgium|Belgium|U', 7, 'Algorithms|Animals|Behavior, Animal|Computers|Drosophila Proteins|Drosophila melanogaster|Interpersonal Relations|Population Surveillance|Social Behavior|Social Isolation|Software', 'Journal Article', '10.1371/journal.pcbi.1006410', '30161262', 'Isolation profoundly influences social behavior in all animals. In humans, isolation has serious effects on health. Drosophila melanogaster is a powerful model to study small-scale, temporally-transient social behavior. However, longer-term analysis of large groups of flies is hampered by the lack of effective and reliable tools. We built a new imaging arena and improved the existing tracking algorithm to reliably follow a large number of flies simultaneously. Next, based on the automatic classification of touch and graph-based social network analysis, we designed an algorithm to quantify changes in the social network in response to prior social isolation. We observed that isolation significantly and swiftly enhanced individual and local social network parameters depicting near-neighbor relationships. We explored the genome-wide molecular correlates of these behavioral changes and found that whereas behavior changed throughout the six days of isolation, gene expression alterations occurred largely on day one. These changes occurred mostly in metabolic genes, and we verified the metabolic changes by showing an increase of lipid content in isolated flies. In summary, we describe a highly reliable tracking and analysis pipeline for large groups of flies that we use to unravel the behavioral, molecular and physiological impact of isolation on social network dynamics in Drosophila.'),
(89216, 2018, 'plos', 'Human Pavlovian fear conditioning conforms to probabilistic learning', 'Tzovara, Athina|Korn, Christoph W|Bach, Dominik R', 'Clinical Psychiatry Research, Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland.|Clinical Psychiatry Research, Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland.|Clinical Psychiatry Research, Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Autonomic Nervous System|Conditioning, Classical|Cues|Fear|Humans|Learning|Machine Learning|Models, Theoretical|Probability Learning', 'Journal Article', '10.1371/journal.pcbi.1006243', '30169519', 'Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.'),
(89217, 2018, 'plos', 'An automated approach to the quantitation of vocalizations and vocal learning in the songbird', 'Mets, David G|Brainard, Michael S', 'Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, California, United States of America.|Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States', 2, 'Adult|Animals|Behavior, Animal|Computer Simulation|Data Analysis|Electronic Data Processing|Female|Finches|Healthy Volunteers|Humans|Learning|Male|Pattern Recognition, Automated|Songbirds|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1006437', '30169523', 'Studies of learning mechanisms critically depend on the ability to accurately assess learning outcomes. This assessment can be impeded by the often complex, multidimensional nature of behavior. We present a novel, automated approach to evaluating imitative learning. Conceptually, our approach estimates how much of the content present in a reference behavior is absent from the learned behavior. We validate our approach through examination of songbird vocalizations, complex learned behaviors the study of which has provided many insights into sensory-motor learning in general and vocal learning in particular. Historically, learning has been holistically assessed by human inspection or through comparison of specific song features selected by experimenters (e.g. fundamental frequency, spectral entropy). In contrast, our approach uses statistical models to broadly capture the structure of each song, and then estimates the divergence between the two models. We show that our measure of song learning (the Kullback-Leibler divergence between two distributions corresponding to specific song data, or, Song DKL) is well correlated with human evaluation of song learning. We then expand the analysis beyond learning and show that Song DKL also detects the typical song deterioration that occurs following deafening. Finally, we illustrate how this measure can be extended to quantify differences in other complex behaviors such as human speech and handwriting. This approach potentially provides a framework for assessing learning across a broad range of behaviors like song that can be described as a set of discrete and repeated motor actions.'),
(89218, 2018, 'plos', 'clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets', 'Risso, Davide|Purvis, Liam|Fletcher, Russell B|Das, Diya|Ngai, John|Dudoit, Sandrine|Purdom, Elizabeth', 'Division of Biostatistics and Epidemiology, Weill Cornell Medicine, New York, New York, United States of America.|Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America.|Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America.|Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America.|Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America.|Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America.|Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Astrocytes|Biomarkers|Cluster Analysis|Computational Biology|Databases, Factual|Gene Expression Profiling|Gene Expression Regulation|Humans|Hypothalamus|Microglia|Multigene Family|Neurons|Olfactory Mucosa|Oligodendroglia|Programming Languages|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006378', '30180157', 'Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of finding biologically meaningful subtypes within the samples. This is an application that is particularly appropriate when there are large numbers of samples, as in many human disease studies. With the increasing popularity of single-cell transcriptome sequencing (RNA-Seq), many more controlled experiments on model organisms are similarly creating large gene expression datasets with the goal of detecting previously unknown heterogeneity within cells. It is common in the detection of novel subtypes to run many clustering algorithms, as well as rely on subsampling and ensemble methods to improve robustness. We introduce a Bioconductor R package, clusterExperiment, that implements a general and flexible strategy we entitle Resampling-based Sequential Ensemble Clustering (RSEC). RSEC enables the user to easily create multiple, competing clusterings of the data based on different techniques and associated tuning parameters, including easy integration of resampling and sequential clustering, and then provides methods for consolidating the multiple clusterings into a final consensus clustering. The package is modular and allows the user to separately apply the individual components of the RSEC procedure, i.e., apply multiple clustering algorithms, create a consensus clustering or choose tuning parameters, and merge clusters. Additionally, clusterExperiment provides a variety of visualization tools for the clustering process, as well as methods for the identification of possible cluster signatures or biomarkers. The R package clusterExperiment is publicly available through the Bioconductor Project, with a detailed manual (vignette) as well as well documented help pages for each function.'),
(89219, 2018, 'plos', 'SIG-DB: Leveraging homomorphic encryption to securely interrogate privately held genomic databases', 'Titus, Alexander J|Flower, Audrey|Hagerty, Patrick|Gamble, Paul|Lewis, Charlie|Stavish, Todd|OConnell, Kevin P|Shipley, Greg|Rogers, Stephanie M', 'B.Next, In-Q-Tel, Arlington, VA, United States of America.|Lab41, In-Q-Tel, Arlington, VA, United States of America.|CosmiQ Works, In-Q-Tel, Arlington, VA, United States of America.|Lab41, In-Q-Tel, Arlington, VA, United States of America.|Cyber Reboot, In-Q-Tel, Arlington, VA, United States of America.|Lab41, In-Q-Tel, Arlington, VA, United States of America.|B.Next, In-Q-Tel, Arlington, VA, United States of America.|Cyber Reboot, In-Q-Tel, Arlington, VA, United States of America.|B.Next, In-Q-Tel, Arlington, VA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 2, 'Algorithms|Cloud Computing|Computer Security|DNA Mutational Analysis|Databases, Factual|Escherichia coli|Escherichia coli O157|Genomics|Humans|Motivation|Mutation|Sequence Analysis, DNA|Staphylococcus aureus|Synthetic Biology', 'Journal Article', '10.1371/journal.pcbi.1006454', '30180163', 'Genomic data are becoming increasingly valuable as we develop methods to utilize the information at scale and gain a greater understanding of how genetic information relates to biological function. Advances in synthetic biology and the decreased cost of sequencing are increasing the amount of privately held genomic data. As the quantity and value of private genomic data grows, so does the incentive to acquire and protect such data, which creates a need to store and process these data securely. We present an algorithm for the Secure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm enables databases of genomic sequences to be searched with an encrypted query sequence without revealing the query sequence to the Database Owner or any of the database sequences to the Querier. SIG-DB is the first application of its kind to take advantage of locality-sensitive hashing and homomorphic encryption to allow generalized sequence-to-sequence comparisons of genomic data.'),
(89220, 2018, 'plos', 'Optimal multi-source forecasting of seasonal influenza', 'Ertem, Zeynep|Raymond, Dorrie|Meyers, Lauren Ancel', 'Department of Statistics and Data Science, The University of Texas at Austin, Austin, Texas, United States of America.|athenaResearch, Watertown, Massachusetts, United States of America.|Departments of Integrative Biology and Statistics and Data Science, The University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|United States', 7, 'Algorithms|Centers for Disease Control and Prevention (U.S.)|Data Collection|Electronic Health Records|Epidemiological Monitoring|Forecasting|Humans|Influenza, Human|Internet|Linear Models|Machine Learning|Public Health Surveillance|Reproducibility of Results|Search Engine|Seasons|Social Media|United States', 'Journal Article', '10.1371/journal.pcbi.1006236', '30180212', 'Forecasting the emergence and spread of influenza viruses is an important public health challenge. Timely and accurate estimates of influenza prevalence, particularly of severe cases requiring hospitalization, can improve control measures to reduce transmission and mortality. Here, we extend a previously published machine learning method for influenza forecasting to integrate multiple diverse data sources, including traditional surveillance data, electronic health records, internet search traffic, and social media activity. Our hierarchical framework uses multi-linear regression to combine forecasts from multiple data sources and greedy optimization with forward selection to sequentially choose the most predictive combinations of data sources. We show that the systematic integration of complementary data sources can substantially improve forecast accuracy over single data sources. When forecasting the Center for Disease Control and Prevention (CDC) influenza-like-illness reports (ILINet) from week 48 through week 20, the optimal combination of predictors includes public health surveillance data and commercially available electronic medical records, but neither search engine nor social media data.'),
(89221, 2018, 'plos', 'Inter-nucleosomal communication between histone modifications for nucleosome phasing', 'Chen, Weizhong|Liu, Yi|Zhu, Shanshan|Chen, Guoyu|Han, Jing-Dong J', 'Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.|Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.|Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.|Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.|Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.', 'China|China|China|China|China', 0, 'Bayes Theorem|Binding Sites|CD4-Positive T-Lymphocytes|Chromatin|Chromatin Assembly and Disassembly|Computational Biology|Epigenesis, Genetic|Gene Expression Regulation|Histone Code|Histones|Humans|Nucleosomes|Protein Processing, Post-Translational|Signal Transduction|Transcription Factors|Transcription Initiation Site|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1006416', '30188887', 'Combinatorial effects of epigenetic modifications on transcription activity have been proposed as histone codes. However, it is unclear whether there also exist inter-nucleosomal communications among epigenetic modifications at single nucleosome level, and if so, what functional roles they play. Meanwhile, how clear nucleosome patterns, such as nucleosome phasing and depletion, are formed at functional regions remains an intriguing enigma. To address these questions, we developed a Bayesian network model for interactions among different histone modifications across neighboring nucleosomes, based on the framework of dynamic Bayesian network (DBN). From this model, we found that robust inter-nucleosomal interactions exist around transcription start site (TSS), transcription termination sites (TTS) or around CTCF binding sites, and these inter-nucleosomal interactions are often involved in transcription regulation. In addition to these general principles, DBN also uncovered a novel specific epigenetic interaction between H2A.Z and H4K20me1 on neighboring nucleosomes, involved in nucleosome free region (NFR) and nucleosome phasing establishment or maintenance. The level of negative correlation between neighboring H2A.Z and H4K20me1 strongly correlate with the size of NFR and the strength of nucleosome phasing around TSS. Our study revealed inter-nucleosomal communications as important players in signal propagation, chromatin remodeling and transcription regulation.'),
(89222, 2018, 'plos', 'Network mechanisms underlying the role of oscillations in cognitive tasks', 'Schmidt, Helmut|Avitabile, Daniele|Montbrió, Ernest|Roxin, Alex', 'Centre de Recerca Matemàtica, Campus de Bellaterra Edifici C, 08193 Bellaterra, Barcelona, Spain.|School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2QL, United Kingdom.|Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, C. Ramon Trias Fargas 25 - 27, 08005 Barcelona, Spain.|Centre de Recerca Matemàtica, Campus de Bellaterra Edifici C, 08193 Bellaterra, Barcelona, Spain.', 'Spain|United Kingdom|Spain|Spain', 0, 'Action Potentials|Brain Waves|Cluster Analysis|Cognition|Humans|Memory, Short-Term|Mental Recall|Models, Neurological|Models, Statistical|Neurons|Normal Distribution|Oscillometry|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006430', '30188889', 'Oscillatory activity robustly correlates with task demands during many cognitive tasks. However, not only are the network mechanisms underlying the generation of these rhythms poorly understood, but it is also still unknown to what extent they may play a functional role, as opposed to being a mere epiphenomenon. Here we study the mechanisms underlying the influence of oscillatory drive on network dynamics related to cognitive processing in simple working memory (WM), and memory recall tasks. Specifically, we investigate how the frequency of oscillatory input interacts with the intrinsic dynamics in networks of recurrently coupled spiking neurons to cause changes of state: the neuronal correlates of the corresponding cognitive process. We find that slow oscillations, in the delta and theta band, are effective in activating network states associated with memory recall. On the other hand, faster oscillations, in the beta range, can serve to clear memory states by resonantly driving transient bouts of spike synchrony which destabilize the activity. We leverage a recently derived set of exact mean-field equations for networks of quadratic integrate-and-fire neurons to systematically study the bifurcation structure in the periodically forced spiking network. Interestingly, we find that the oscillatory signals which are most effective in allowing flexible switching between network states are not smooth, pure sinusoids, but rather burst-like, with a sharp onset. We show that such periodic bursts themselves readily arise spontaneously in networks of excitatory and inhibitory neurons, and that the burst frequency can be tuned via changes in tonic drive. Finally, we show that oscillations in the gamma range can actually stabilize WM states which otherwise would not persist.'),
(89223, 2018, 'plos', 'A fully autonomous terrestrial bat-like acoustic robot', 'Eliakim, Itamar|Cohen, Zahi|Kosa, Gabor|Yovel, Yossi', 'Mechanical Engineering Department, Tel Aviv University, Tel Aviv, Israel.|Mechanical Engineering Department, Tel Aviv University, Tel Aviv, Israel.|Intelligent Medical Micro/Nano Systems Group, University Hospital of Basel, Basel, Switzerland.|Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Switzerland|Israel', 10, 'Acoustics|Algorithms|Animals|Chiroptera|Decision Making|Echolocation|Neural Networks (Computer)|Predatory Behavior|Reproducibility of Results|Robotics|Sound', 'Journal Article', '10.1371/journal.pcbi.1006406', '30188901', 'Echolocating bats rely on active sound emission (echolocation) for mapping novel environments and navigating through them. Many theoretical frameworks have been suggested to explain how they do so, but few attempts have been made to build an actual robot that mimics their abilities. Here, we present the Robat-a fully autonomous bat-like terrestrial robot that relies on echolocation to move through a novel environment while mapping it solely based on sound. Using the echoes reflected from the environment, the Robat delineates the borders of objects it encounters, and classifies them using an artificial neural-network, thus creating a rich map of its environment. Unlike most previous attempts to apply sonar in robotics, we focus on a biological bat-like approach, which relies on a single emitter and two ears, and we apply a biological plausible signal processing approach to extract information about objects position and identity.'),
(89224, 2018, 'plos', 'Co-evolution networks of HIV/HCV are modular with direct association to structure and function', 'Quadeer, Ahmed Abdul|Morales-Jimenez, David|McKay, Matthew R', 'Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Institute of Electronics, Communications and Information Technology, Queens University Belfast, Belfast, United Kingdom.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.', 'China|United Kingdom|China', 3, 'Algorithms|Alleles|Computational Biology|Computer Simulation|DNA Mutational Analysis|DNA, Viral|Disease Progression|Evolution, Molecular|HIV Core Protein p24|HIV Infections|HIV-1|HLA Antigens|Hepacivirus|Hepatitis C|Humans|Immune System|Normal Distribution|Phenotype|Principal Component Analysis|Protein Domains|Structure-Activity Relationship|nef Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1371/journal.pcbi.1006409', '30192744', 'Mutational correlation patterns found in population-level sequence data for the Human Immunodeficiency Virus (HIV) and the Hepatitis C Virus (HCV) have been demonstrated to be informative of viral fitness. Such patterns can be seen as footprints of the intrinsic functional constraints placed on viral evolution under diverse selective pressures. Here, considering multiple HIV and HCV proteins, we demonstrate that these mutational correlations encode a modular co-evolutionary structure that is tightly linked to the structural and functional properties of the respective proteins. Specifically, by introducing a robust statistical method based on sparse principal component analysis, we identify near-disjoint sets of collectively-correlated residues (sectors) having mostly a one-to-one association to largely distinct structural or functional domains. This suggests that the distinct phenotypic properties of HIV/HCV proteins often give rise to quasi-independent modes of evolution, with each mode involving a sparse and localized network of mutational interactions. Moreover, individual inferred sectors of HIV are shown to carry immunological significance, providing insight for guiding targeted vaccine strategies.'),
(89225, 2018, 'plos', 'Comparing two classes of biological distribution systems using network analysis', 'Papadopoulos, Lia|Blinder, Pablo|Ronellenfitsch, Henrik|Klimm, Florian|Katifori, Eleni|Kleinfeld, David|Bassett, Danielle S', 'Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Sagol School of Neuroscience, TelAviv University, Tel Aviv, Israel.|Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Physics, University of California San Diego, La Jolla, California, United States of America.|Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|Israel|United States|United Kingdom|United States|United States|United States', 0, 'Animals|Biological Transport|Brain|Cerebrovascular Circulation|Cluster Analysis|Image Processing, Computer-Assisted|Mice|Models, Biological|Mycelium|Rats', 'Comparative Study', '10.1371/journal.pcbi.1006428', '30192745', 'Distribution networks-from vasculature to urban transportation pathways-are spatially embedded networks that must route resources efficiently in the face of pressures induced by the costs of building and maintaining network infrastructure. Such requirements are thought to constrain the topological and spatial organization of these systems, but at the same time, different kinds of distribution networks may exhibit variable architectural features within those general constraints. In this study, we use methods from network science to compare and contrast two classes of biological transport networks: mycelial fungi and vasculature from the surface of rodent brains. These systems differ in terms of their growth and transport mechanisms, as well as the environments in which they typically exist. Though both types of networks have been studied independently, the goal of this study is to quantify similarities and differences in their network designs. We begin by characterizing the structural backbone of these systems with a collection of measures that assess various kinds of network organization across topological and spatial scales, ranging from measures of loop density, to those that quantify connected pathways between different network regions, and hierarchical organization. Most importantly, we next carry out a network analysis that directly considers the spatial embedding and properties especially relevant to the function of distribution systems. We find that although both the vasculature and mycelia are highly constrained planar networks, there are clear distinctions in how they balance tradeoffs in network measures of wiring length, efficiency, and robustness. While the vasculature appears well organized for low cost, but relatively high efficiency, the mycelia tend to form more expensive but in turn more robust networks. As a whole, this work demonstrates the utility of network-based methods to identify both common features and variations in the network structure of different classes of biological transport systems.'),
(89226, 2018, 'plos', 'Assessment of mutation probabilities of KRAS G12 missense mutants and their long-timescale dynamics by atomistic molecular simulations and Markov state modeling', 'Pantsar, Tatu|Rissanen, Sami|Dauch, Daniel|Laitinen, Tuomo|Vattulainen, Ilpo|Poso, Antti', 'School of Pharmacy, University of Eastern Finland, Kuopio, Finland.|Laboratory of Physics, Tampere University of Technology, Tampere, Finland.|Department of Internal Medicine VIII, University Hospital Tuebingen, Tuebingen, Germany.|School of Pharmacy, University of Eastern Finland, Kuopio, Finland.|Laboratory of Physics, Tampere University of Technology, Tampere, Finland.|School of Pharmacy, University of Eastern Finland, Kuopio, Finland.', 'Finland|Finland|Germany|Finland|Finland|Finland', 14, 'DNA Mutational Analysis|Genes, ras|Guanosine Diphosphate|Guanosine Triphosphate|Humans|Hydrophobic and Hydrophilic Interactions|Ligands|Markov Chains|Molecular Conformation|Molecular Dynamics Simulation|Mutation|Mutation, Missense|Neoplasms|Principal Component Analysis|Probability|Proto-Oncogene Proteins p21(ras)', 'Journal Article', '10.1371/journal.pcbi.1006458', '30199525', 'A mutated KRAS protein is frequently observed in human cancers. Traditionally, the oncogenic properties of KRAS missense mutants at position 12 (G12X) have been considered as equal. Here, by assessing the probabilities of occurrence of all KRAS G12X mutations and KRAS dynamics we show that this assumption does not hold true. Instead, our findings revealed an outstanding mutational bias. We conducted a thorough mutational analysis of KRAS G12X mutations and assessed to what extent the observed mutation frequencies follow a random distribution. Unique tissue-specific frequencies are displayed with specific mutations, especially with G12R, which cannot be explained by random probabilities. To clarify the underlying causes for the nonrandom probabilities, we conducted extensive atomistic molecular dynamics simulations (170 xcexbcs) to study the differences of G12X mutations on a molecular level. The simulations revealed an allosteric hydrophobic signaling network in KRAS, and that protein dynamics is altered among the G12X mutants and as such differs from the wild-type and is mutation-specific. The shift in long-timescale conformational dynamics was confirmed with Markov state modeling. A G12X mutation was found to modify KRAS dynamics in an allosteric way, which is especially manifested in the switch regions that are responsible for the effector protein binding. The findings provide a basis to understand better the oncogenic properties of KRAS G12X mutants and the consequences of the observed nonrandom frequencies of specific G12X mutations.'),
(89227, 2018, 'plos', 'Implications of alternative routes to APC/C inhibition by the mitotic checkpoint complex', 'Gross, Fridolin|Bonaiuti, Paolo|Hauf, Silke|Ciliberto, Andrea', 'Istituto Firc di Oncologia Molecolare, IFOM, Milano, Italy.|Istituto Firc di Oncologia Molecolare, IFOM, Milano, Italy.|Department of Biological Sciences, Virginia Tech, Blacksburg, VA, United States of America.|Istituto Firc di Oncologia Molecolare, IFOM, Milano, Italy.', 'Italy|Italy|United States|Italy', 0, 'Anaphase|Anaphase-Promoting Complex-Cyclosome|Cdc20 Proteins|Cell Cycle Proteins|Cell Nucleus|Chromosome Segregation|Mitosis|Models, Theoretical|Protein Binding|Schizosaccharomyces|Schizosaccharomyces pombe Proteins|Signal Transduction|Spindle Apparatus', 'Journal Article', '10.1371/journal.pcbi.1006449', '30199529', 'The mitotic checkpoint (also called spindle assembly checkpoint) is a signaling pathway that ensures faithful chromosome segregation. Mitotic checkpoint proteins inhibit the anaphase-promoting complex (APC/C) and its activator Cdc20 to prevent precocious anaphase. Checkpoint signaling leads to a complex of APC/C, Cdc20, and checkpoint proteins, in which the APC/C is inactive. In principle, this final product of the mitotic checkpoint can be obtained via different pathways, whose relevance still needs to be fully ascertained experimentally. Here, we use mathematical models to compare the implications on checkpoint response of the possible pathways leading to APC/C inhibition. We identify a previously unrecognized funneling effect for Cdc20, which favors Cdc20 incorporation into the inhibitory complex and therefore promotes checkpoint activity. Furthermore, we find that the presence or absence of one specific assembly reaction determines whether the checkpoint remains functional at elevated levels of Cdc20, which can occur in cancer cells. Our results reveal the inhibitory logics behind checkpoint activity, predict checkpoint efficiency in perturbed situations, and could inform molecular strategies to treat malignancies that exhibit Cdc20 overexpression.'),
(89228, 2018, 'plos', 'A Markov chain for numerical chromosomal instability in clonally expanding populations', 'Elizalde, Sergi|Laughney, Ashley M|Bakhoum, Samuel F', 'Department of Mathematics, Dartmouth College, Hanover, New Hampshire, United States of America.|Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States', 1, 'Algorithms|Cell Survival|Cells, Cultured|Chromosomal Instability|Chromosomes|DNA Mutational Analysis|Humans|Karyotyping|Markov Chains|Mitosis|Models, Statistical|Mutation|Neoplasms|Probability|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006447', '30204765', 'Cancer cells frequently undergo chromosome missegregation events during mitosis, whereby the copies of a given chromosome are not distributed evenly among the two daughter cells, thus creating cells with heterogeneous karyotypes. A stochastic model tracing cellular karyotypes derived from clonal populations over hundreds of generations was recently developed and experimentally validated, and it was capable of predicting favorable karyotypes frequently observed in cancer. Here, we construct and study a Markov chain that precisely describes karyotypic evolution during clonally expanding cancer cell populations. The Markov chain allows us to directly predict the distribution of karyotypes and the expected size of the tumor after many cell divisions without resorting to computationally expensive simulations. We determine the limiting karyotype distribution of an evolving tumor population, and quantify its dependency on several key parameters including the initial karyotype of the founder cell, the rate of whole chromosome missegregation, and chromosome-specific cell viability. Using this model, we confirm the existence of an optimal rate of chromosome missegregation probabilities that maximizes karyotypic heterogeneity, while minimizing the occurrence of nullisomy. Interestingly, karyotypic heterogeneity is significantly more dependent on chromosome missegregation probabilities rather than the number of cell divisions, so that maximal heterogeneity can be reached rapidly (within a few hundred generations of cell division) at chromosome missegregation rates commonly observed in cancer cell lines. Conversely, at low missegregation rates, heterogeneity is constrained even after thousands of cell division events. This leads us to conclude that chromosome copy number heterogeneity is primarily constrained by chromosome missegregation rates and the risk for nullisomy and less so by the age of the tumor. This model enables direct integration of karyotype information into existing models of tumor evolution based on somatic mutations.'),
(89229, 2018, 'plos', 'Selective ion permeation involves complexation with carboxylates and lysine in a model human sodium channel', 'Flood, Emelie|Boiteux, Cxc3xa9line|Allen, Toby W', 'School of Science, RMIT University, Melbourne, Vic, Australia.|School of Science, RMIT University, Melbourne, Vic, Australia.|School of Science, RMIT University, Melbourne, Vic, Australia.', 'Australia|Australia|Australia', 4, 'Amines|Bacterial Proteins|Carboxylic Acids|Humans|Ions|Lysine|Membrane Potentials|Mutation|NAV1.2 Voltage-Gated Sodium Channel|Potassium|Protein Binding|Protein Domains|Protein Transport|Sodium|Static Electricity|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006398', '30208027', 'Bacterial and human voltage-gated sodium channels (Navs) exhibit similar cation selectivity, despite their distinct EEEE and DEKA selectivity filter signature sequences. Recent high-resolution structures for bacterial Navs have allowed us to learn about ion conduction mechanisms in these simpler homo-tetrameric channels, but our understanding of the function of their mammalian counterparts remains limited. To probe these conduction mechanisms, a model of the human Nav1.2 channel has been constructed by grafting residues of its selectivity filter and external vestibular region onto the bacterial NavRh channel with atomic-resolution structure. Multi-xcexbcs fully atomistic simulations capture long time-scale ion and protein movements associated with the permeation of Na+ and K+ ions, and their differences. We observe a Na+ ion knock-on conduction mechanism facilitated by low energy multi-carboxylate/multi-Na+ complexes, akin to the bacterial channels. These complexes involve both the DEKA and vestibular EEDD rings, acting to draw multiple Na+ into the selectivity filter and promote permeation. When the DEKA ring lysine is protonated, we observe that its ammonium group is actively participating in Na+ permeation, presuming the role of another ion. It participates in the formation of a stable complex involving carboxylates that collectively bind both Na+ and the Lys ammonium group in a high-field strength site, permitting pass-by translocation of Na+. In contrast, multiple K+ ion complexes with the DEKA and EEDD rings are disfavored by up to 8.3 kcal/mol, with the K+-lysine-carboxylate complex non-existent. As a result, lysine acts as an electrostatic plug that partially blocks the flow of K+ ions, which must instead wait for isomerization of lysine downward to clear the path for K+ passage. These distinct mechanisms give us insight into the nature of ion conduction and selectivity in human Nav channels, while uncovering high field strength carboxylate binding complexes that define the more general phenomenon of Na+-selective ion transport in nature.'),
(89230, 2018, 'plos', 'Informational structures: A dynamical system approach for integrated information', 'Esteban, Francisco J|Galadí, Javier A|Langa, José A|Portillo, José R|Soler-Toscano, Fernando', 'Department of Experimental Biology, University of Jaén, Jaén, Spain.|Department of Differential Equations and Numerical Analysis, University of Seville, Seville, Spain.|Department of Differential Equations and Numerical Analysis, University of Seville, Seville, Spain.|Department of Applied Mathematic I, University of Seville, Seville, Spain.|Department of Philosophy, Logic and Philosophy of Science, University of Seville, Seville, Spain.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Animals|Brain|Consciousness|Humans|Information Theory|Models, Neurological|Models, Theoretical|Nonlinear Dynamics', 'Journal Article', '10.1371/journal.pcbi.1006154', '30212467', 'Integrated Information Theory (IIT) has become nowadays the most sensible general theory of consciousness. In addition to very important statements, it opens the door for an abstract (mathematical) formulation of the theory. Given a mechanism in a particular state, IIT identifies a conscious experience with a conceptual structure, an informational object which exists, is composed of identified parts, is informative, integrated and maximally irreducible. This paper introduces a space-time continuous version of the concept of integrated information. To this aim, a graph and a dynamical systems treatment is used to define, for a given mechanism in a state for which a dynamics is settled, an Informational Structure, which is associated to the global attractor at each time of the system. By definition, the informational structure determines all the past and future behavior of the system, possesses an informational nature and, moreover, enriches all the points of the phase space with cause-effect power by means of its associated Informational Field. A detailed description of its inner structure by invariants and connections between them allows to associate a transition probability matrix to each informational structure and to develop a measure for the level of integrated information of the system.'),
(89231, 2018, 'plos', 'The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh', 'Hill, Edward M|House, Thomas|Dhingra, Madhur S|Kalpravidh, Wantanee|Morzaria, Subhash|Osmani, Muzaffar G|Brum, Eric|Yamage, Mat|Kalam, Md A|Prosser, Diann J|Takekawa, John Y|Xiao, Xiangming|Gilbert, Marius|Tildesley, Michael J', 'Zeeman Institute: Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom.|School of Mathematics, The University of Manchester, Manchester, United Kingdom.|Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.|Food and Agricultural Organization of the United Nations Regional Office for Asia and the Pacific, Bangkok, Thailand.|Food and Agricultural Organization of the United Nations, Rome, Italy.|Department of Livestock Services, Dhaka, Bangladesh.|Emergency Centre for Transboundary Animal Diseases (ECTAD), Food and Agriculture Organization of the United Nations, Dhaka, Bangladesh.|Emergency Centre for Transboundary Animal Diseases (ECTAD), Food and Agriculture Organization of the United Nations, Dhaka, Bangladesh.|Institute of Epidemiology, Disease Control & Research (IEDCR), Dhaka, Bangladesh.|USGS Patuxent Wildlife Research Center, Laurel, Maryland, United States of America.|U.S. Geological Survey, Western Ecological Research Center, San Francisco Bay Estuary Field Station, Vallejo, California, United States of America.|Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, Oklahoma, United States of America.|Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.|Zeeman Institute: Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|Belgium|Thailand|Italy|Bangladesh|Bangladesh|Bangladesh|Bangladesh|Uni', 0, 'Animals|Bangladesh|Chickens|Communicable Disease Control|Computer Simulation|Disease Outbreaks|Geography|Health Policy|Influenza A Virus, H5N1 Subtype|Influenza in Birds|Models, Theoretical|Poultry', 'Journal Article', '10.1371/journal.pcbi.1006439', '30212472', 'In Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89232, 2018, 'plos', 'Patient-specific pulse wave propagation model identifies cardiovascular risk characteristics in hemodialysis patients', 'Poleszczuk, Jan|Debowska, Malgorzata|Dabrowski, Wojciech|Wojcik-Zaluska, Alicja|Zaluska, Wojciech|Waniewski, Jacek', 'Department for Mathematical Modeling of Physiological Processes, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland.|Department for Mathematical Modeling of Physiological Processes, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland.|Department of Anesthesiology and Intensive Therapy, Medical University of Lublin, Lublin, Poland.|Department of Physical Therapy and Rehabilitation, Medical University of Lublin, Lublin, Poland.|Department of Nephrology, Medical University of Lublin, Lublin, Poland.|Department for Mathematical Modeling of Physiological Processes, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland', 2, 'Adult|Aged|Arteriovenous Fistula|Biomarkers|Cardiovascular Diseases|Female|Healthy Volunteers|Heart Rate|Humans|Male|Middle Aged|Pulse Wave Analysis|Renal Dialysis|Risk Factors|Software|Vascular Stiffness', 'Journal Article', '10.1371/journal.pcbi.1006417', '30216341', 'Risk of cardiovascular associated death in dialysis patients is the highest among all other co-morbidities. Improving the identification of patients with the highest cardiovascular risk to design an adequate treatment is, therefore, of utmost importance. There are several non-invasive cardiovascular state biomarkers based on the pulse (pressure) wave propagation properties, but their major determinants are not fully understood. In the current study we aimed to provide a framework to precisely dissect the information available in non-invasively recorded pulse wave in hemodialysis patients. Radial pressure wave profiles were recorded before, during and after two independent hemodialysis sessions in 35 anuric prevalent hemodialysis patients and once in a group of 32 healthy volunteers. Each recording was used to estimate six subject-specific parameters of pulse wave propagation model. Pressure profiles were also analyzed using SphygmoCor software (AtCor Medical, Australia) to derive values of already established biomarkers, i.e. augmentation index and sub-endocardial viability ratio (SEVR). Data preprocessing using propensity score matching allowed to compare hemodialysis and healthy groups. Augmentation index remained on average stable at 142 ± 28% during dialysis and had similar values in both considered groups. SEVR, whose pre-dialytic value was on average lower by 12% compared to healthy participants, was improved by hemodialysis, with post-dialytic values indistinguishable from those in healthy population (p-value > 0.2). The model, however, identified that the patients on hemodialysis had significantly increased stiffness of both large and small arteries compared to healthy counterparts (> 60% before dialysis with p-value < 0.05 or borderline) and that it was only transiently decreased during hemodialysis session. Additionally, correlation-based clustering revealed that augmentation index reflects the shape of heart ejection profile and SEVR is associated with stiffness of larger arteries. Patient-specific pulse wave propagation modeling coupled with radial pressure profile recording correctly identified increased arterial stiffness in hemodialysis patients, while regular pulse wave analysis based biomarkers failed to show significant differences. Further model testing in larger populations and investigating other biomarkers are needed to confirm these findings.'),
(89233, 2018, 'plos', 'Modeling and prediction of clinical symptom trajectories in Alzheimers disease using longitudinal data', 'Bhagwat, Nikhil|Viviano, Joseph D|Voineskos, Aristotle N|Chakravarty, M Mallar|Alzheimer’s Disease Neuroimaging Initiative', 'Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.|Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.|Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Aged|Aging|Algorithms|Alzheimer Disease|Area Under Curve|Australia|Biomarkers|Disease Progression|Female|Follow-Up Studies|Humans|Longitudinal Studies|Machine Learning|Magnetic Resonance Imaging|Male|Models, Neurological|Nerve Net|Neuroimaging|Reproducibility of Results|Software|Symptom Assessment', 'Journal Article', '10.1371/journal.pcbi.1006376', '30216352', 'Computational models predicting symptomatic progression at the individual level can be highly beneficial for early intervention and treatment planning for Alzheimers disease (AD). Individual prognosis is complicated by many factors including the definition of the prediction objective itself. In this work, we present a computational framework comprising machine-learning techniques for 1) modeling symptom trajectories and 2) prediction of symptom trajectories using multimodal and longitudinal data. We perform primary analyses on three cohorts from Alzheimers Disease Neuroimaging Initiative (ADNI), and a replication analysis using subjects from Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL). We model the prototypical symptom trajectory classes using clinical assessment scores from mini-mental state exam (MMSE) and Alzheimers Disease Assessment Scale (ADAS-13) at nine timepoints spanned over six years based on a hierarchical clustering approach. Subsequently we predict these trajectory classes for a given subject using magnetic resonance (MR) imaging, genetic, and clinical variables from two timepoints (baseline + follow-up). For prediction, we present a longitudinal Siamese neural-network (LSN) with novel architectural modules for combining multimodal data from two timepoints. The trajectory modeling yields two (stable and decline) and three (stable, slow-decline, fast-decline) trajectory classes for MMSE and ADAS-13 assessments, respectively. For the predictive tasks, LSN offers highly accurate performance with 0.900 accuracy and 0.968 AUC for binary MMSE task and 0.760 accuracy for 3-way ADAS-13 task on ADNI datasets, as well as, 0.724 accuracy and 0.883 AUC for binary MMSE task on replication AIBL dataset.'),
(89234, 2018, 'plos', 'Emergent mechanics of actomyosin drive punctuated contractions and shape network morphology in the cell cortex', 'Miller, Callie J|Harris, Demetrius|Weaver, Robert|Ermentrout, G Bard|Davidson, Lance A', 'Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.|Bioengineering, Pennsylvania State University, State College, PA, United States of America.|Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.|Mathematics, University of Pittsburgh, Pittsburgh, PA, United States of America.|Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Actin Cytoskeleton|Actins|Actomyosin|Adenosine Triphosphate|Animals|Biomechanical Phenomena|Cell Movement|Computer Simulation|Cross-Linking Reagents|Cytoplasm|Drosophila|Hydrolysis|Microfilament Proteins|Molecular Motor Proteins|Muscle Contraction|Myosins|Polymers|Viscosity|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1006344', '30222728', 'Filamentous actin (F-actin) and non-muscle myosin II motors drive cell motility and cell shape changes that guide large scale tissue movements during embryonic morphogenesis. To gain a better understanding of the role of actomyosin in vivo, we have developed a two-dimensional (2D) computational model to study emergent phenomena of dynamic unbranched actomyosin arrays in the cell cortex. These phenomena include actomyosin punctuated contractions, or actin asters that form within quiescent F-actin networks. Punctuated contractions involve both formation of high intensity aster-like structures and disassembly of those same structures. Our 2D model allows us to explore the kinematics of filament polarity sorting, segregation of motors, and morphology of F-actin arrays that emerge as the model structure and biophysical properties are varied. Our model demonstrates the complex, emergent feedback between filament reorganization and motor transport that generate as well as disassemble actin asters. Since intracellular actomyosin dynamics are thought to be controlled by localization of scaffold proteins that bind F-actin or their myosin motors we also apply our 2D model to recapitulate in vitro studies that have revealed complex patterns of actomyosin that assemble from patterning filaments and motor complexes with microcontact printing. Although we use a minimal representation of filament, motor, and cross-linker biophysics, our model establishes a framework for investigating the role of other actin binding proteins, how they might alter actomyosin dynamics, and makes predictions that can be tested experimentally within live cells as well as within in vitro models.'),
(89235, 2018, 'plos', 'Abstract concept learning in a simple neural network inspired by the insect brain', 'Cope, Alex J|Vasilaki, Eleni|Minors, Dorian|Sabo, Chelsea|Marshall, James A R|Barron, Andrew B', 'Department of Computer Science, University of Sheffield, Sheffield, UK.|Department of Computer Science, University of Sheffield, Sheffield, UK.|Department of Biological Sciences, Macquarie University, Sydney, Australia.|Department of Computer Science, University of Sheffield, Sheffield, UK.|Department of Computer Science, University of Sheffield, Sheffield, UK.|Department of Biological Sciences, Macquarie University, Sydney, Australia.', 'United Kingdom|United Kingdom|Australia|United Kingdom|United Kingdom|Australia', 0, 'Animals|Bees|Behavior, Animal|Brain|Cognition|Computer Simulation|Learning|Machine Learning|Models, Neurological|Mushroom Bodies|Neural Networks (Computer)|Odorants|Probability|Software', 'Journal Article', '10.1371/journal.pcbi.1006435', '30222735', 'The capacity to learn abstract concepts such as sameness and difference is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn sameness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of sameness and difference that is compatible with the insect brain, and is not dependent on top-down or executive control processing.'),
(89236, 2018, 'plos', 'The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow', 'Migliore, Rosanna|Lupascu, Carmen A|Bologna, Luca L|Romani, Armando|Courcol, Jean-Denis|Antonel, Stefano|Van Geit, Werner A H|Thomson, Alex M|Mercer, Audrey|Lange, Sigrun|Falck, Joanne|Rössert, Christian A|Shi, Ying|Hagens, Olivier|Pezzoli, Maurizio|Freund, Tamas F|Kali, Szabolcs|Muller, Eilif B|Schürmann, Felix|Markram, Henry|Migliore, Michele', 'Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|University College London, London, United Kingdom.|University College London, London, United Kingdom.|University College London, London, United Kingdom.|University College London, London, United Kingdom.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, EPFL, Lausanne, Switzerland.|Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, EPFL, Lausanne, Switzerland.|Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary.|Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.|Institute of Biophysics, National Research Council, Palermo, Italy.', 'Italy|Italy|Italy|Switzerland|Switzerland|Switzerland|Switzerland|United Kingdom|United Kingdom|Unit', 17, 'Action Potentials|Animals|Electrophysiology|Hippocampus|Interneurons|Male|Models, Neurological|Neurons|Pyramidal Cells|Rats|Rats, Sprague-Dawley|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1006423', '30222740', 'Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neurons lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiments and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other is responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry.'),
(89237, 2018, 'plos', 'Correction: A method to quantify mechanobiologic forces during zebrafish cardiac development using 4-D light sheet imaging and computational modeling', 'Vedula, Vijay|Lee, Juhyun|Xu, Hao|Jay Kuo, C-C|Hsiai, Tzung K|Marsden, Alison L', 'Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.|Institute of Biophysics, National Research Council, Palermo, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006482', '30222742', '[This corrects the article DOI: 10.1371/journal.pcbi.1005828.].'),
(89238, 2018, 'plos', 'Model-based spatial navigation in the hippocampus-ventral striatum circuit: A computational analysis', 'Stoianov, Ivilin Peev|Pennartz, Cyriel M A|Lansink, Carien S|Pezzulo, Giovani', 'Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.|University of Amsterdam, Swammerdam Institute for Life Sciences-Center for Neuroscience Amsterdam, The Netherlands.|University of Amsterdam, Swammerdam Institute for Life Sciences-Center for Neuroscience Amsterdam, The Netherlands.|Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.', 'Italy|Netherlands|Netherlands|Italy', 0, 'Algorithms|Animals|Bayes Theorem|Behavior, Animal|Brain|Brain Mapping|Computer Simulation|Conditioning, Classical|Decision Making|Hippocampus|Humans|Learning|Machine Learning|Maze Learning|Medical Informatics|Mice|Neurobiology|Reinforcement (Psychology)|Software|Spatial Navigation|Ventral Striatum', 'Journal Article', '10.1371/journal.pcbi.1006316', '30222746', 'While the neurobiology of simple and habitual choices is relatively well known, our current understanding of goal-directed choices and planning in the brain is still limited. Theoretical work suggests that goal-directed computations can be productively associated to model-based (reinforcement learning) computations, yet a detailed mapping between computational processes and neuronal circuits remains to be fully established. Here we report a computational analysis that aligns Bayesian nonparametrics and model-based reinforcement learning (MB-RL) to the functioning of the hippocampus (HC) and the ventral striatum (vStr)-a neuronal circuit that increasingly recognized to be an appropriate model system to understand goal-directed (spatial) decisions and planning mechanisms in the brain. We test the MB-RL agent in a contextual conditioning task that depends on intact hippocampus and ventral striatal (shell) function and show that it solves the task while showing key behavioral and neuronal signatures of the HC-vStr circuit. Our simulations also explore the benefits of biological forms of look-ahead prediction (forward sweeps) during both learning and control. This article thus contributes to fill the gap between our current understanding of computational algorithms and biological realizations of (model-based) reinforcement learning.'),
(89239, 2018, 'plos', 'Evolutionary footprint of epistasis', 'Pedruzzi, Gabriele|Barlukova, Ayuna|Rouzine, Igor M', 'Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationelle et Quantitative, Paris, France.|Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationelle et Quantitative, Paris, France.|Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationelle et Quantitative, Paris, France.', 'France|France|France', 2, 'Biological Evolution|Cluster Analysis|Computer Simulation|DNA Mutational Analysis|Epistasis, Genetic|Genetic Drift|Genetic Fitness|Genome|Haplotypes|Humans|Immune System|Models, Genetic|Monte Carlo Method|Mutation|Phenotype|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1006426', '30222748', 'Variation of an inherited trait across a population cannot be explained by additive contributions of relevant genes, due to epigenetic effects and biochemical interactions (epistasis). Detecting epistasis in genomic data still represents a significant challenge that requires a better understanding of epistasis from the mechanistic point of view. Using a standard Wright-Fisher model of bi-allelic asexual population, we study how compensatory epistasis affects the process of adaptation. The main result is a universal relationship between four haplotype frequencies of a single site pair in a genome, which depends only on the epistasis strength of the pair defined regarding Darwinian fitness. We demonstrate the existence, at any time point, of a quasi-equilibrium between epistasis and disorder (entropy) caused by random genetic drift and mutation. We verify the accuracy of these analytic results by Monte-Carlo simulation over a broad range of parameters, including the topology of the interacting network. Thus, epistasis assists the evolutionary transit through evolutionary hurdles leaving marks at the level of haplotype disequilibrium. The method allows determining selection coefficient for each site and the epistasis strength of each pair from a sequence set. The resulting ability to detect clusters of deleterious mutation close to full compensation is essential for biomedical applications. These findings help to understand the role of epistasis in multiple compensatory mutations in viral resistance to antivirals and immune response.'),
(89240, 2018, 'plos', 'Robust spatial memory maps encoded by networks with transient connections', 'Babichev, Andrey|Morozov, Dmitriy|Dabaghian, Yuri', 'Department of Computational and Applied Mathematics, Rice University, Houston, Texas, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Department of Neurology, The University of Texas McGovern Medical School, Houston, Texas, United States of America.', 'United States|United States|United States', 3, 'Action Potentials|Animals|Brain|Brain Mapping|Cognition|Computer Simulation|Hippocampus|Models, Neurological|Neurons|Poisson Distribution|Spatial Memory|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1006433', '30226836', 'The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space-a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long period. However, the neuronal substrate that produces this map is transient: the synaptic connections in the hippocampus and in the downstream neuronal networks never cease to form and to deteriorate at a rapid rate. How can the brain maintain a robust, reliable representation of space using a network that constantly changes its architecture? We address this question using a computational framework that allows evaluating the effect produced by the decaying connections between simulated hippocampal neurons on the properties of the cognitive map. Using novel Algebraic Topology techniques, we demonstrate that emergence of stable cognitive maps produced by networks with transient architectures is a generic phenomenon. The model also points out that deterioration of the cognitive map caused by weakening or lost connections between neurons may be compensated by simulating the neuronal activity. Lastly, the model explicates the importance of the complementary learning systems for processing spatial information at different levels of spatiotemporal granularity.'),
(89241, 2018, 'plos', 'All-atom normal mode dynamics of HIV-1 capsid', 'Na, Hyuntae|Song, Guang', 'Department of Computer Science, Penn State Harrisburg, Middletown, Pennsylvania, United States of America.|Department of Computer Science, Iowa State University, Ames, Iowa, United States of America.', 'United States|United States', 0, 'Algorithms|Arginine|Capsid|Capsid Proteins|Computer Simulation|Elasticity|HIV-1|Models, Molecular|Models, Statistical|Molecular Dynamics Simulation|Motion|Protein Domains|Virion', 'Journal Article', '10.1371/journal.pcbi.1006456', '30226840', 'Dynamics of biomolecular assemblies offer invaluable insights into their functional mechanisms. For extremely large biomolecular systems, such as HIV-1 capsid that has nearly 5 millions atoms, obtaining its normal mode dynamics using even coarse-grained models can be a challenging task. In this work, we have successfully carried out a normal mode analysis of an entire HIV-1 capsid in full all-atom details. This is made possible through our newly developed BOSE (Block of Selected Elasticity) model that is founded on the principle of resonance discovered in our recent work. The resonance principle makes it possible to most efficiently compute the vibrations of a whole capsid at any given frequency by projecting the motions of component capsomeres into a narrow subspace. We have conducted also assessments of the quality of the BOSE modes by comparing them with benchmark modes obtained directly from the original Hessian matrix. Our all-atom normal mode dynamics study of the HIV-1 capsid reveals the dynamic role of the pentamers in stabilizing the capsid structure and is in agreement with experimental findings that suggest capsid disassembly and uncoating start when the pentamers become destabilized. Our results on the dynamics of hexamer pores suggest that nucleotide transport should take place mostly at hexamers near pentamers, especially at the larger hemispherical end.'),
(89242, 2018, 'plos', 'Transition state characteristics during cell differentiation', 'Brackston, Rowan D|Lakatos, Eszter|Stumpf, Michael P H', 'Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 5, 'Algorithms|Cell Differentiation|Cell Lineage|Epigenesis, Genetic|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Humans|Linear Models|Models, Genetic|Normal Distribution|Probability|Signal Transduction|Stem Cells|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006405', '30235202', 'Models describing the process of stem-cell differentiation are plentiful, and may offer insights into the underlying mechanisms and experimentally observed behaviour. Waddingtons epigenetic landscape has been providing a conceptual framework for differentiation processes since its inception. It also allows, however, for detailed mathematical and quantitative analyses, as the landscape can, at least in principle, be related to mathematical models of dynamical systems. Here we focus on a set of dynamical systems features that are intimately linked to cell differentiation, by considering exemplar dynamical models that capture important aspects of stem cell differentiation dynamics. These models allow us to map the paths that cells take through gene expression space as they move from one fate to another, e.g. from a stem-cell to a more specialized cell type. Our analysis highlights the role of the transition state (TS) that separates distinct cell fates, and how the nature of the TS changes as the underlying landscape changes-change that can be induced by e.g. cellular signaling. We demonstrate that models for stem cell differentiation may be interpreted in terms of either a static or transitory landscape. For the static case the TS represents a particular transcriptional profile that all cells approach during differentiation. Alternatively, the TS may refer to the commonly observed period of heterogeneity as cells undergo stochastic transitions.'),
(89243, 2018, 'plos', 'Maintaining maximal metabolic flux by gene expression control', 'Planqué, Robert|Hulshof, Josephus|Teusink, Bas|Hendriks, Johannes C|Bruggeman, Frank J', 'Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Systems Bioinformatics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Systems Bioinformatics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Systems Bioinformatics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 3, 'Algorithms|Biochemical Phenomena|Escherichia coli|Escherichia coli Proteins|Galactose|Gene Expression|Kinetics|Metabolic Networks and Pathways|Models, Biological|Protein Binding|Systems Biology|Thermodynamics|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006412', '30235207', 'One of the marvels of biology is the phenotypic plasticity of microorganisms. It allows them to maintain high growth rates across conditions. Studies suggest that cells can express metabolic enzymes at tuned concentrations through adjustment of gene expression. The associated transcription factors are often regulated by intracellular metabolites. Here we study metabolite-mediated regulation of metabolic-gene expression that maximises metabolic fluxes across conditions. We developed an adaptive control theory, qORAC (for Specific Flux (q) Optimization by Robust Adaptive Control), and illustrate it with several examples of metabolic pathways. The key feature of the theory is that it does not require knowledge of the regulatory network, only of the metabolic part. We derive that maximal metabolic flux can be maintained in the face of varying N environmental parameters only if the number of transcription-factor binding metabolites is at least equal to N. The controlling circuits appear to require simple biochemical kinetics. We conclude that microorganisms likely can achieve maximal rates in metabolic pathways, in the face of environmental changes.'),
(89244, 2018, 'plos', 'Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network', 'Lyu, Yafei|Xue, Lingzhou|Zhang, Feipeng|Koch, Hillary|Saba, Laura|Kechris, Katerina|Li, Qunhua', 'Bioinformatics and Genomics, the Huck Institute of the Life Science, Pennsylvania State University, State College, Pennsylvania, United States of America.|Department of Statistics, Pennsylvania State University, State College, Pennsylvania, United States of America.|Department of Statistics, Pennsylvania State University, State College, Pennsylvania, United States of America.|Department of Statistics, Pennsylvania State University, State College, Pennsylvania, United States of America.|Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America.|Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America.|Department of Statistics, Pennsylvania State University, State College, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Area Under Curve|Brain|Breast Neoplasms|Computer Graphics|Computer Simulation|Databases, Factual|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Heart|Humans|Male|Myocardium|Neoplasms|Normal Distribution|Rats|Software', 'Journal Article', '10.1371/journal.pcbi.1006436', '30240439', 'Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis. One possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions or execute final biological functions in pathways, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.'),
(89245, 2018, 'plos', 'Proteome-scale relationships between local amino acid composition and protein fates and functions', 'Cascarina, Sean M|Ross, Eric D', 'Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, CO, United States of America.|Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, CO, United States of America.', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Amino Acids|Animals|Caenorhabditis elegans|Cell Membrane|Computational Biology|Evolution, Molecular|Open Reading Frames|Polymers|Protein Domains|Protein Interaction Mapping|Proteins|Proteome|Proteomics|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1006256', '30248088', 'Proteins with low-complexity domains continue to emerge as key players in both normal and pathological cellular processes. Although low-complexity domains are often grouped into a single class, individual low-complexity domains can differ substantially with respect to amino acid composition. These differences may strongly influence the physical properties, cellular regulation, and molecular functions of low-complexity domains. Therefore, we developed a bioinformatic approach to explore relationships between amino acid composition, protein metabolism, and protein function. We find that local compositional enrichment within protein sequences is associated with differences in translation efficiency, abundance, half-life, protein-protein interaction promiscuity, subcellular localization, and molecular functions of proteins on a proteome-wide scale. However, local enrichment of related amino acids is sometimes associated with opposite effects on protein regulation and function, highlighting the importance of distinguishing between different types of low-complexity domains. Furthermore, many of these effects are discernible at amino acid compositions below those required for classification as low-complexity or statistically-biased by traditional methods and in the absence of homopolymeric amino acid repeats, indicating that thresholds employed by classical methods may not reflect biologically relevant criteria. Application of our analyses to composition-driven processes, such as the formation of membraneless organelles, reveals distinct composition profiles even for closely related organelles. Collectively, these results provide a unique perspective and detailed insights into relationships between amino acid composition, protein metabolism, and protein functions.'),
(89246, 2018, 'plos', 'Inferring decoding strategies for multiple correlated neural populations', 'Lakshminarasimhan, Kaushik J|Pouget, Alexandre|DeAngelis, Gregory C|Angelaki, Dora E|Pitkow, Xaq', 'Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States of America.|Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland.|Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States of America.', 'United States|Switzerland|United States|United States|United States', 3, 'Algorithms|Animals|Brain|Choice Behavior|Computer Simulation|Macaca mulatta|Models, Neurological|Motion|Motion Perception|Neurons|Normal Distribution', 'Journal Article', '10.1371/journal.pcbi.1006371', '30248091', 'Studies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional role of brain areas. Theories that focus only on choice-related neuronal activity cannot reconcile those findings without additional experiments involving large-scale recordings to measure interneuronal correlations. By expanding current theories of neural coding and incorporating results from inactivation experiments, we demonstrate here that it is possible to infer decoding weights of different brain areas at a coarse scale without precise knowledge of the correlation structure. We apply this technique to neural data collected from two different cortical areas in macaque monkeys trained to perform a heading discrimination task. We identify two opposing decoding schemes, each consistent with data depending on the nature of correlated noise. Our theory makes specific testable predictions to distinguish these scenarios experimentally without requiring measurement of the underlying noise correlations.'),
(89247, 2018, 'plos', 'OptMDFpathway: Identification of metabolic pathways with maximal thermodynamic driving force and its application for analyzing the endogenous CO2 fixation potential of Escherichia coli', 'Hädicke, Oliver|von Kamp, Axel|Aydogan, Timur|Klamt, Steffen', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Adenosine Triphosphate|Algorithms|Biomass|Carbon|Carbon Dioxide|Citric Acid Cycle|Escherichia coli|Genome, Bacterial|Glucose|Glycerol|Hydrogen-Ion Concentration|Linear Models|Metabolic Networks and Pathways|Models, Biological|Pyruvate Synthase|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006492', '30248096', 'Constraint-based modeling techniques have become a standard tool for the in silico analysis of metabolic networks. To further improve their accuracy, recent methodological developments focused on integration of thermodynamic information in metabolic models to assess the feasibility of flux distributions by thermodynamic driving forces. Here we present OptMDFpathway, a method that extends the recently proposed framework of Max-min Driving Force (MDF) for thermodynamic pathway analysis. Given a metabolic network model, OptMDFpathway identifies both the optimal MDF for a desired phenotypic behavior as well as the respective pathway itself that supports the optimal driving force. OptMDFpathway is formulated as a mixed-integer linear program and is applicable to genome-scale metabolic networks. As an important theoretical result, we also show that there exists always at least one elementary mode in the network that reaches the maximal MDF. We employed our new approach to systematically identify all substrate-product combinations in Escherichia coli where product synthesis allows for concomitant net CO2 assimilation via thermodynamically feasible pathways. Although biomass synthesis cannot be coupled to net CO2 fixation in E. coli we found that as many as 145 of the 949 cytosolic carbon metabolites contained in the genome-scale model iJO1366 enable net CO2 incorporation along thermodynamically feasible pathways with glycerol as substrate and 34 with glucose. The most promising products in terms of carbon assimilation yield and thermodynamic driving forces are orotate, aspartate and the C4-metabolites of the tricarboxylic acid cycle. We also identified thermodynamic bottlenecks frequently limiting the maximal driving force of the CO2-fixing pathways. Our results indicate that heterotrophic organisms like E. coli hold a possibly underestimated potential for CO2 assimilation which may complement existing biotechnological approaches for capturing CO2. Furthermore, we envision that the developed OptMDFpathway approach can be used for many other applications within the framework of constrained-based modeling and for rational design of metabolic networks.'),
(89248, 2018, 'plos', 'Comparison of fluctuations in global network topology of modeled and empirical brain functional connectivity', 'Fukushima, Makoto|Sporns, Olaf', 'Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Osaka, Japan.|Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.', 'Japan|India', 4, 'Adult|Brain|Brain Mapping|Cerebral Cortex|Cognition|Computer Simulation|Databases, Factual|Female|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Models, Statistical|Nerve Net|Neural Pathways|Normal Distribution|Pattern Recognition, Automated|Reproducibility of Results|Time Factors|Young Adult', 'Comparative Study', '10.1371/journal.pcbi.1006497', '30252835', 'Dynamic models of large-scale brain activity have been used for reproducing many empirical findings on human brain functional connectivity. Features that have been shown to be reproducible by comparing modeled to empirical data include functional connectivity measured over several minutes of resting-state functional magnetic resonance imaging, as well as its time-resolved fluctuations on a time scale of tens of seconds. However, comparison of modeled and empirical data has not been conducted yet for fluctuations in global network topology of functional connectivity, such as fluctuations between segregated and integrated topology or between high and low modularity topology. Since these global network-level fluctuations have been shown to be related to human cognition and behavior, there is an emerging need for clarifying their reproducibility with computational models. To address this problem, we directly compared fluctuations in global network topology of functional connectivity between modeled and empirical data, and clarified the degree to which a stationary model of spontaneous brain dynamics can reproduce the empirically observed fluctuations. Modeled fluctuations were simulated using a system of coupled phase oscillators wired according to brain structural connectivity. By performing model parameter search, we found that modeled fluctuations in global metrics quantifying network integration and modularity had more than 80% of magnitudes of those observed in the empirical data. Temporal properties of network states determined based on fluctuations in these metrics were also found to be reproducible, although their spatial patterns in functional connectivity did not perfectly matched. These results suggest that stationary models simulating resting-state activity can reproduce the magnitude of empirical fluctuations in segregation and integration, whereas additional factors, such as active mechanisms controlling non-stationary dynamics and/or greater accuracy of mapping brain structural connectivity, would be necessary for fully reproducing the spatial patterning associated with these fluctuations.'),
(89249, 2018, 'plos', 'Individualised aspiration dynamics: Calculation by proofs', 'Wu, Bin|Zhou, Lei', 'School of Sciences, Beijing University of Posts and Telecommunications, Beijing, China.|Center for Systems and Control, College of Engineering, Peking University, Beijing, China.', 'China|China', 6, 'Algorithms|Aspirations (Psychology)|Biological Evolution|Computational Biology|Computer Simulation|Cooperative Behavior|Decision Making|Game Theory|Humans|Interpersonal Relations|Markov Chains|Models, Statistical|Models, Theoretical|Probability|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006035', '30252850', 'Cooperation is key for the evolution of biological systems ranging from bacteria communities to human societies. Evolutionary processes can dramatically alter the cooperation level. Evolutionary processes are typically of two classes: comparison based and self-evaluation based. The fate of cooperation is extremely sensitive to the details of comparison based processes. For self-evaluation processes, however, it is still unclear whether the sensitivity remains. We concentrate on a class of self-evaluation processes based on aspiration, where all the individuals adjust behaviors based on their own aspirations. We prove that the evolutionary outcome with heterogeneous aspirations is the same as that of the homogeneous one for regular networks under weak selection limit. Simulation results further suggest that it is also valid for general networks across various distributions of personalised aspirations. Our result clearly indicates that self-evaluation processes are robust in contrast with comparison based rules. In addition, our result greatly simplifies the calculation of the aspiration dynamics, which is computationally expensive.'),
(89250, 2018, 'plos', 'An information theoretic treatment of sequence-to-expression modeling', 'Khajouei, Farzaneh|Sinha, Saurabh', 'Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States', 0, 'Animals|Binding Sites|Computational Biology|Computer Simulation|Drosophila melanogaster|Enhancer Elements, Genetic|Gene Expression Profiling|Gene Expression Regulation|Information Theory|Models, Biological|Models, Genetic|Mutagenesis, Site-Directed|Normal Distribution|Probability|Regulatory Sequences, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006459', '30256780', 'Studying a genes regulatory mechanisms is a tedious process that involves identification of candidate regulators by transcription factor (TF) knockout or over-expression experiments, delineation of enhancers by reporter assays, and demonstration of direct TF influence by site mutagenesis, among other approaches. Such experiments are often chosen based on the biologists intuition, from several testable hypotheses. We pursue the goal of making this process systematic by using ideas from information theory to reason about experiments in gene regulation, in the hope of ultimately enabling rigorous experiment design strategies. For this, we make use of a state-of-the-art mathematical model of gene expression, which provides a way to formalize our current knowledge of cis- as well as trans- regulatory mechanisms of a gene. Ambiguities in such knowledge can be expressed as uncertainties in the model, which we capture formally by building an ensemble of plausible models that fit the existing data and defining a probability distribution over the ensemble. We then characterize the impact of a new experiment on our understanding of the genes regulation based on how the ensemble of plausible models and its probability distribution changes when challenged with results from that experiment. This allows us to assess the value of the experiment retroactively as the reduction in entropy of the distribution (information gain) resulting from the experiments results. We fully formalize this novel approach to reasoning about gene regulation experiments and use it to evaluate a variety of perturbation experiments on two developmental genes of D. melanogaster. We also provide objective and biologist-friendly descriptions of the information gained from each such experiment. The rigorously defined information theoretic approaches presented here can be used in the future to formulate systematic strategies for experiment design pertaining to studies of gene regulatory mechanisms.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89251, 2018, 'plos', 'Quantitative single cell analysis uncovers the life/death decision in CD95 network', 'Buchbinder, Jxc3xb6rn H|Pischel, Dennis|Sundmacher, Kai|Flassig, Robert J|Lavrik, Inna N', 'Translational Inflammation Research, Otto von Guericke University, Magdeburg, Germany.|Process Systems Engineering, Otto von Guericke University, Magdeburg, Germany.|Process Systems Engineering, Otto von Guericke University, Magdeburg, Germany.|Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Translational Inflammation Research, Otto von Guericke University, Magdeburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Apoptosis|Caspase 3|Caspases|Cell Lineage|Computer Simulation|Flow Cytometry|HeLa Cells|Humans|Models, Theoretical|NF-kappa B|Signal Transduction|Single-Cell Analysis|fas Receptor', 'Journal Article', '10.1371/journal.pcbi.1006368', '30256782', 'CD95/Fas/APO-1 is a member of the death receptor family that triggers apoptotic and anti-apoptotic responses in particular, NF-xcexbaB. These responses are characterized by a strong heterogeneity within a population of cells. To determine how the cell decides between life and death we developed a computational model supported by imaging flow cytometry analysis of CD95 signaling. Here we show that CD95 stimulation leads to the induction of caspase and NF-xcexbaB pathways simultaneously in one cell. The related life/death decision strictly depends on cell-to-cell variability in the formation of the death-inducing complex (DISC) on one side (extrinsic noise) vs. stochastic gene expression of the NF-xcexbaB pathway on the other side (intrinsic noise). Moreover, our analysis has uncovered that the stochasticity in apoptosis and NF-kB pathways leads not only to survival or death of a cell, but also causes a third type of response to CD95 stimulation that we termed ambivalent response. Cells in the ambivalent state can undergo cell death or survive which was subsequently validated by experiments. Taken together, we have uncovered how these two competing pathways control the fate of a cell, which in turn plays an important role for development of anti-cancer therapies.'),
(89252, 2018, 'plos', 'Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community', 'Hunt, Kristopher A|Jennings, Ryan M|Inskeep, William P|Carlson, Ross P', 'Thermal Biology Institute, Montana State University, Bozeman, Montana, United States of America.|Thermal Biology Institute, Montana State University, Bozeman, Montana, United States of America.|Thermal Biology Institute, Montana State University, Bozeman, Montana, United States of America.|Thermal Biology Institute, Montana State University, Bozeman, Montana, United States of America.', 'United States|United States|United States|United States', 0, 'Autotrophic Processes|Biomass|Carbon|Computer Simulation|Electron Transport|Electrons|Ferric Compounds|Genome, Archaeal|Heterotrophic Processes|Hot Temperature|Iron|Metagenomics|Microbiota|Oxygen|Phylogeny|Sulfides|Sulfolobaceae|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1006431', '30260956', 'Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2-4), high-temperature (> 65 °C) springs of Yellowstone National Park contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from the studied Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.'),
(89253, 2018, 'plos', 'Multivariate classification of neuroimaging data with nested subclasses: Biased accuracy and implications for hypothesis testing', 'Jamalabadi, Hamidreza|Alizadeh, Sarah|Schönauer, Monika|Leibold, Christian|Gais, Steffen', 'Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.|Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.|Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.|Bernstein Center for Computational Neuroscience, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.|Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 1, 'Bias|Computational Biology|Computer Simulation|Electroencephalography|Evoked Potentials|Humans|Linear Models|Multivariate Analysis|Neuroimaging|Normal Distribution|Pattern Recognition, Automated|Reproducibility of Results|Research Design|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1006486', '30260958', 'Biological data sets are typically characterized by high dimensionality and low effect sizes. A powerful method for detecting systematic differences between experimental conditions in such multivariate data sets is multivariate pattern analysis (MVPA), particularly pattern classification. However, in virtually all applications, data from the classes that correspond to the conditions of interest are not homogeneous but contain subclasses. Such subclasses can for example arise from individual subjects that contribute multiple data points, or from correlations of items within classes. We show here that in multivariate data that have subclasses nested within its class structure, these subclasses introduce systematic information that improves classifiability beyond what is expected by the size of the class difference. We analytically prove that this subclass bias systematically inflates correct classification rates (CCRs) of linear classifiers depending on the number of subclasses as well as on the portion of variance induced by the subclasses. In simulations, we demonstrate that subclass bias is highest when between-class effect size is low and subclass variance high. This bias can be reduced by increasing the total number of subclasses. However, we can account for the subclass bias by using permutation tests that explicitly consider the subclass structure of the data. We illustrate our result in several experiments that recorded human EEG activity, demonstrating that parametric statistical tests as well as typical trial-wise permutation fail to determine significance of classification outcomes correctly.'),
(89254, 2018, 'plos', 'Emergence of spontaneous assembly activity in developing neural networks without afferent input', 'Triplett, Marcus A|Avitan, Lilach|Goodhill, Geoffrey J', 'Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.|Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.|Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia.', 'Australia|Australia|Australia', 0, 'Animals|Calcium|Female|Male|Models, Neurological|Models, Statistical|Neural Networks (Computer)|Neurogenesis|Neuronal Plasticity|Retina|Sensory Receptor Cells|Software|Stochastic Processes|Superior Colliculi|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1006421', '30265665', 'Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in the zebrafish optic tectum after bilateral enucleation early in life. While the development of neural assemblies based on structured afferent input has been theoretically well-studied, it is less clear how they could arise in systems without afferent input. Here we show that a recurrent network of binary threshold neurons with initially random weights can form neural assemblies based on a simple Hebbian learning rule. Over development the network becomes increasingly modular while being driven by initially unstructured spontaneous activity, leading to the emergence of neural assemblies. Surprisingly, the set of neurons making up each assembly then continues to evolve, despite the number of assemblies remaining roughly constant. In the mature network assembly activity builds over several timesteps before the activation of the full assembly, as recently observed in calcium-imaging experiments. Our results show that Hebbian learning is sufficient to explain the emergence of highly structured patterns of neural activity in the absence of structured input.'),
(89255, 2018, 'plos', 'Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a whole-cell vaccine', 'Cai, Francisco Y|Fussell, Thomas|Cobey, Sarah|Lipsitch, Marc', 'Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America.|Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 5, 'Carrier State|Computational Biology|Host-Pathogen Interactions|Humans|Incidence|Models, Immunological|Pneumococcal Infections|Pneumococcal Vaccines|Prevalence|Randomized Controlled Trials as Topic|Streptococcus pneumoniae', 'Journal Article', '10.1371/journal.pcbi.1006333', '30273332', 'For encapsulated bacteria such as Streptococcus pneumoniae, asymptomatic carriage is more common and longer in duration than disease, and hence is often a more convenient endpoint for clinical trials of vaccines against these bacteria. However, using a carriage endpoint entails specific challenges. Carriage is almost always measured as prevalence, whereas the vaccine may act by reducing incidence or duration. Thus, to determine sample size requirements, its impact on prevalence must first be estimated. The relationship between incidence and prevalence (or duration and prevalence) is convex, saturating at 100% prevalence. For this reason, the proportional effect of a vaccine on prevalence is typically less than its proportional effect on incidence or duration. This relationship is further complicated in the presence of multiple pathogen strains. In addition, host immunity to carriage accumulates rapidly with frequent exposures in early years of life, creating potentially complex interactions with the vaccines effect. We conducted a simulation study to predict the impact of an inactivated whole cell pneumococcal vaccine-believed to reduce carriage duration-on carriage prevalence in different age groups and trial settings. We used an individual-based model of pneumococcal carriage that incorporates relevant immunological processes, both vaccine-induced and naturally acquired. Our simulations showed that for a wide range of vaccine efficacies, sampling time and age at vaccination are important determinants of sample size. There is a window of favorable sampling times during which the required sample size is relatively low, and this window is prolonged with a younger age at vaccination, and in a trial setting with lower transmission intensity. These results illustrate the ability of simulation studies to inform the planning of vaccine trials with carriage endpoints, and the methods we present here can be applied to trials evaluating other pneumococcal vaccine candidates or comparing alternative dosing schedules for the existing conjugate vaccines.'),
(89256, 2018, 'plos', 'Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design', 'Handel, Andreas|Li, Yan|McKay, Brian|Pawelek, Kasia A|Zarnitsyna, Veronika|Antia, Rustom', 'Department of Epidemiology and Biostatistics and Health Informatics Institute and Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America.|Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America.|Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States of America.|Department of Mathematics and Computational Science, University of South Carolina Beaufort, Bluffton, South Carolina, United States of America.|Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America.|Department of Biology, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|Georgia|United States|Georgia|Georgia', 3, 'Animals|Computational Biology|Dose-Response Relationship, Immunologic|Drug Design|Host-Pathogen Interactions|Humans|Mice|Models, Immunological|Rats|Vaccines|Viral Load', 'Journal Article', '10.1371/journal.pcbi.1006505', '30273336', 'Vaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose. We illustrate the concept of using data and models to inform inoculum dose determination for vaccines, wby fitting a mathematical model to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) infection of cotton rats at different inoculum doses. We use the model to map inoculum dose to the level of immune protection and morbidity and to explore how such a framework might be used to determine an optimal inoculum dose. We show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. Our findings illustrate that the impact of inoculum dose on immune protection and morbidity can depend on the specific pathogen and that both protection and morbidity do not necessarily increase monotonically with increasing inoculum dose. Once vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework can help in the rational design of vaccines and determination of the optimal amount of inoculum.'),
(89257, 2018, 'plos', 'Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data', 'Soto, Fabian A|Vucovich, Lauren E|Ashby, F Gregory', 'Department of Psychology, Florida International University, Miami, Florida, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States|United States', 2, 'Brain|Face|Facial Expression|Female|Humans|Image Processing, Computer-Assisted|Magnetic Resonance Imaging|Male|Psychophysics|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1006470', '30273337', 'Many research questions in visual perception involve determining whether stimulus properties are represented and processed independently. In visual neuroscience, there is great interest in determining whether important object dimensions are represented independently in the brain. For example, theories of face recognition have proposed either completely or partially independent processing of identity and emotional expression. Unfortunately, most previous research has only vaguely defined what is meant by independence, which hinders its precise quantification and testing. This article develops a new quantitative framework that links signal detection theory from psychophysics and encoding models from computational neuroscience, focusing on a special form of independence defined in the psychophysics literature: perceptual separability. The new theory allowed us, for the first time, to precisely define separability of neural representations and to theoretically link behavioral and brain measures of separability. The framework formally specifies the relation between these different levels of perceptual and brain representation, providing the tools for a truly integrative research approach. In particular, the theory identifies exactly what valid inferences can be made about independent encoding of stimulus dimensions from the results of multivariate analyses of neuroimaging data and psychophysical studies. In addition, commonly used operational tests of independence are re-interpreted within this new theoretical framework, providing insights on their correct use and interpretation. Finally, we apply this new framework to the study of separability of brain representations of face identity and emotional expression (neutral/sad) in a human fMRI study with male and female participants.'),
(89258, 2018, 'plos', 'meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays', 'Gelfman, Sahar|Wang, Quanli|Lu, Yi-Fan|Hall, Diana|Bostick, Christopher D|Dhindsa, Ryan|Halvorsen, Matt|McSweeney, K Melodi|Cotterill, Ellese|Edinburgh, Tom|Beaumont, Michael A|Frankel, Wayne N|Petrovski, Slavé|Allen, Andrew S|Boland, Michael J|Goldstein, David B|Eglen, Stephen J', 'Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Cambridge Computational Biology Institute, University of Cambridge, Cambridge, United Kingdom.|Cambridge Computational Biology Institute, University of Cambridge, Cambridge, United Kingdom.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States of America.|Cambridge Computational Biology Institute, University of Cambridge, Cambridge, United Kingdom.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Action Potentials|Algorithms|Animals|Cells, Cultured|Computational Biology|Electrophysiology|Mice|Mice, Knockout|Microelectrodes|Neurons|Software', 'Journal Article', '10.1371/journal.pcbi.1006506', '30273353', 'Here we present an open-source R package meaRtools that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.'),
(89259, 2018, 'plos', 'Cooperation of dual modes of cell motility promotes epithelial stress relaxation to accelerate wound healing', 'Staddon, Michael F|Bi, Dapeng|Tabatabai, A Pasha|Ajeti, Visar|Murrell, Michael P|Banerjee, Shiladitya', 'Department of Physics and Astronomy, University College London, London, United Kingdom.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Department of Physics and Astronomy, University College London, London, United Kingdom.', 'United Kingdom|United States|United States|United States|United States|United Kingdom', 0, 'Animals|Cell Movement|Computational Biology|Dogs|Elastic Modulus|Epithelial Cells|Focal Adhesions|Madin Darby Canine Kidney Cells|Models, Biological|Wound Healing', 'Journal Article', '10.1371/journal.pcbi.1006502', '30273354', 'Collective cell migration in cohesive units is vital for tissue morphogenesis, wound repair, and immune response. While the fundamental driving forces for collective cell motion stem from contractile and protrusive activities of individual cells, it remains unknown how their balance is optimized to maintain tissue cohesiveness and the fluidity for motion. Here we present a cell-based computational model for collective cell migration during wound healing that incorporates mechanochemical coupling of cell motion and adhesion kinetics with stochastic transformation of active motility forces. We show that a balance of protrusive motility and actomyosin contractility is optimized for accelerating the rate of wound repair, which is robust to variations in cell and substrate mechanical properties. This balance underlies rapid collective cell motion during wound healing, resulting from a tradeoff between tension mediated collective cell guidance and active stress relaxation in the tissue.'),
(89260, 2018, 'plos', 'Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor', 'Erickson, Richard A|Fienen, Michael N|McCalla, S Grace|Weiser, Emily L|Bower, Melvin L|Knudson, Jonathan M|Thain, Greg', 'Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, Wisconsin, United States of America.|Wisconsin Water Science Center, United States Geological Survey, Middelton, Wisconsin, United States of America.|Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, Wisconsin, United States of America.|Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, Wisconsin, United States of America.|Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, Wisconsin, United States of America.|Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, Wisconsin, United States of America.|Department of Computer Science, University of Wisconsin-Madison, Madison, Winconsin, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 3, 'Computational Biology|Computing Methodologies|Ecology|High-Throughput Screening Assays|Humans|Internet|Research|Software', 'Journal Article', '10.1371/journal.pcbi.1006468', '30281592', 'Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not always available nor the most appropriate solution for all computationally intense problems. High-throughput computing (HTC) is one method for handling computationally intense research. In contrast to high-performance computing, which uses a single supercomputer, HTC can distribute tasks over many computers (e.g., idle desktop computers, dedicated servers, or cloud-based resources). HTC facilities exist at many academic and government institutes and are relatively easy to create from commodity hardware. Additionally, consortia such as Open Science Grid facilitate HTC, and commercial entities sell cloud-based solutions for researchers who lack HTC at their institution. We provide an introduction to HTC for biologists and environmental scientists. Our examples from biology and the environmental sciences use HTCondor, an open source HTC system.'),
(89261, 2018, 'plos', 'Ten simple rules for scientists: Improving your writing productivity', 'Peterson, Todd C|Kleppner, Sofie R|Botham, Crystal M', 'Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, United States of America.|Office of Postdoctoral Affairs, Stanford University, Stanford, California, United States of America.|Stanford Biosciences Grant Writing Academy, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States', 1, 'Efficiency|Humans|Mental Competency|Thinking|Writing', 'Editorial', '10.1371/journal.pcbi.1006379', '30286072', '-'),
(89262, 2018, 'plos', 'A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons', 'Solbrå, Andreas|Bergersen, Aslak Wigdahl|van den Brink, Jonas|Malthe-Sørenssen, Anders|Einevoll, Gaute T|Halnes, Geir', 'Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.|Simula Research Laboratory, Fornebu, Norway.|Simula Research Laboratory, Fornebu, Norway.|Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.|Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.', 'Norway|Norway|Norway|Norway|Norway|Norway', 0, 'Brain|Computational Biology|Computer Simulation|Diffusion|Electrophysiological Phenomena|Extracellular Space|Humans|Models, Neurological|Models, Statistical|Neurons', 'Journal Article', '10.1371/journal.pcbi.1006510', '30286073', 'Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.'),
(89263, 2018, 'plos', 'Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties', 'Chen, Ling|Fish, Alexandra E|Capra, John A', 'Department of Biological Sciences, Vanderbilt University, Nashville, TN, United States of America.|Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, United States of America.|Department of Biological Sciences, Vanderbilt University, Nashville, TN, United States of America.', 'United States|United States|United States', 0, 'Animals|Conserved Sequence|Enhancer Elements, Genetic|Evolution, Molecular|Genomics|Humans|Machine Learning|Mammals|Neural Networks (Computer)|Sequence Alignment|Sequence Analysis, DNA|Support Vector Machine', 'Journal Article', '10.1371/journal.pcbi.1006484', '30286077', 'Genomic regions with gene regulatory enhancer activity turnover rapidly across mammals. In contrast, gene expression patterns and transcription factor binding preferences are largely conserved between mammalian species. Based on this conservation, we hypothesized that enhancers active in different mammals would exhibit conserved sequence patterns in spite of their different genomic locations. To investigate this hypothesis, we evaluated the extent to which sequence patterns that are predictive of enhancers in one species are predictive of enhancers in other mammalian species by training and testing two types of machine learning models. We trained support vector machine (SVM) and convolutional neural network (CNN) classifiers to distinguish enhancers defined by histone marks from the genomic background based on DNA sequence patterns in human, macaque, mouse, dog, cow, and opossum. The classifiers accurately identified many adult liver, developing limb, and developing brain enhancers, and the CNNs outperformed the SVMs. Furthermore, classifiers trained in one species and tested in another performed nearly as well as classifiers trained and tested on the same species. We observed similar cross-species conservation when applying the models to human and mouse enhancers validated in transgenic assays. This indicates that many short sequence patterns predictive of enhancers are largely conserved. The sequence patterns most predictive of enhancers in each species matched the binding motifs for a common set of TFs enriched for expression in relevant tissues, supporting the biological relevance of the learned features. Thus, despite the rapid change of active enhancer locations between mammals, cross-species enhancer prediction is often possible. Our results suggest that short sequence patterns encoding enhancer activity have been maintained across more than 180 million years of mammalian evolution.'),
(89264, 2018, 'plos', 'Ten simple rules when considering retirement', 'Bourne, Philip E', 'University of Virginia, Data Science Institute, Charlottesville, Virginia, United States of America.', 'United States', 0, 'Choice Behavior|Employment|Family|Humans|Retirement', 'Editorial', '10.1371/journal.pcbi.1006411', '30286100', '-'),
(89265, 2018, 'plos', 'Functional conservation of sequence determinants at rapidly evolving regulatory regions across mammals', 'Huh, Iksoo|Mendizabal, Isabel|Park, Taesung|Yi, Soojin V', 'School of Biological Sciences, Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, United States of America.|School of Biological Sciences, Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, United States of America.|Department of Statistics, College of Natural Sciences, Seoul National University, Seoul, Korea.|School of Biological Sciences, Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, United States of America.', 'Georgia|Georgia|-|Georgia', 0, 'Animals|Conserved Sequence|Epigenomics|Humans|Machine Learning|Mammals|Models, Statistical|Regulatory Sequences, Nucleic Acid|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006451', '30289877', 'Recent advances in epigenomics have made it possible to map genome-wide regulatory regions using empirical methods. Subsequent comparative epigenomic studies have revealed that regulatory regions diverge rapidly between genome of different species, and that the divergence is more pronounced in enhancers than in promoters. To understand genomic changes underlying these patterns, we investigated if we can identify specific sequence fragments that are over-enriched in regulatory regions, thus potentially contributing to regulatory functions of such regions. Here we report numerous sequence fragments that are statistically over-enriched in enhancers and promoters of different mammals (which we refer to as sequence determinants). Interestingly, the degree of statistical enrichment, which presumably is associated with the degree of regulatory impacts of the specific sequence determinant, was significantly higher for promoter sequence determinants than enhancer sequence determinants. We further used a machine learning method to construct prediction models using sequence determinants. Remarkably, prediction models constructed from one species could be used to predict regulatory regions of other species with high accuracy. This observation indicates that even though the precise locations of regulatory regions diverge rapidly during evolution, the functional potential of sequence determinants underlying regulatory sequences may be conserved between species.'),
(89266, 2018, 'plos', 'Noise propagation in an integrated model of bacterial gene expression and growth', 'Kleijn, Istvan T|Krah, Laurens H J|Hermsen, Rutger', 'Theoretical Biology, Department of Biology, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology, Department of Biology, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology, Department of Biology, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Escherichia coli|Gene Expression Regulation, Bacterial|Genes, Bacterial|Models, Biological|Signal Processing, Computer-Assisted|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006386', '30289879', 'In bacterial cells, gene expression, metabolism, and growth are highly interdependent and tightly coordinated. As a result, stochastic fluctuations in expression levels and instantaneous growth rate show intricate cross-correlations. These correlations are shaped by feedback loops, trade-offs and constraints acting at the cellular level, therefore a quantitative understanding requires an integrated approach. To that end, we here present a mathematical model describing a cell that contains multiple proteins that are each expressed stochastically and jointly limit the growth rate. Conversely, metabolism and growth affect protein synthesis and dilution. Thus, expression noise originating in one gene propagates to metabolism, growth, and the expression of all other genes. Nevertheless, under a small-noise approximation many statistical quantities can be calculated analytically. We identify several routes of noise propagation, illustrate their origins and scaling, and establish important connections between noise propagation and the field of metabolic control analysis. We then present a many-protein model containing >1000 proteins parameterized by previously measured abundance data and demonstrate that the predicted cross-correlations between gene expression and growth rate are in broad agreement with published measurements.'),
(89267, 2018, 'plos', 'In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability', 'Vavourakis, Vasileios|Stylianopoulos, Triantafyllos|Wijeratne, Peter A', 'Department of Medical Physics & Biomedical Engineering, University College London, London, United Kingdom.|Department of Mechanical & Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus.|Department of Computer Science, University College London, London, United Kingdom.', 'United Kingdom|Cyprus|United Kingdom', 0, 'Antineoplastic Agents|Capillary Permeability|Computational Biology|Computer Simulation|Drug Delivery Systems|Endothelium, Vascular|Humans|Models, Biological|Neoplasms|Neovascularization, Pathologic', 'Journal Article', '10.1371/journal.pcbi.1006460', '30296260', 'The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting.'),
(89268, 2018, 'plos', 'Interactive reservoir computing for chunking information streams', 'Asabuki, Toshitake|Hiratani, Naoki|Fukai, Tomoki', 'Department of Complexity Science and Engineering, Univ. of Tokyo, Kashiwa, Chiba, Japan.|Department of Complexity Science and Engineering, Univ. of Tokyo, Kashiwa, Chiba, Japan.|Department of Complexity Science and Engineering, Univ. of Tokyo, Kashiwa, Chiba, Japan.', 'Japan|Japan|Japan', 0, 'Brain|Computational Biology|Humans|Learning|Models, Neurological|Neural Networks (Computer)|Unsupervised Machine Learning', 'Journal Article', '10.1371/journal.pcbi.1006400', '30296262', 'Chunking is the process by which frequently repeated segments of temporal inputs are concatenated into single units that are easy to process. Such a process is fundamental to time-series analysis in biological and artificial information processing systems. The brain efficiently acquires chunks from various information streams in an unsupervised manner, however, the underlying mechanisms of this process remain elusive. A widely-adopted statistical method for chunking consists of predicting frequently repeated contiguous elements in an input sequence based on unequal transition probabilities over sequence elements. However, recent experimental findings suggest that the brain is unlikely to adopt this method, as human subjects can chunk sequences with uniform transition probabilities. In this study, we propose a novel conceptual framework to overcome this limitation. In this process, neural networks learn to predict dynamical response patterns to sequence input rather than to directly learn transition patterns. Using a mutually supervising pair of reservoir computing modules, we demonstrate how this mechanism works in chunking sequences of letters or visual images with variable regularity and complexity. In addition, we demonstrate that background noise plays a crucial role in correctly learning chunks in this model. In particular, the model can successfully chunk sequences that conventional statistical approaches fail to chunk due to uniform transition probabilities. In addition, the neural responses of the model exhibit an interesting similarity to those of the basal ganglia observed after motor habit formation.'),
(89269, 2018, 'plos', 'Rotation of sex combs in Drosophila melanogaster requires precise and coordinated spatio-temporal dynamics from forces generated by epithelial cells', 'Ho, Ernest C Y|Malagón, Juan Nicolas|Ahuja, Abha|Singh, Rama|Larsen, Ellen', 'Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.|Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.|Department of Biology, McMaster University, Hamilton, Ontario, Canada.|Department of Biology, McMaster University, Hamilton, Ontario, Canada.|Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animal Structures|Animals|Computational Biology|Drosophila melanogaster|Epithelial Cells|Male|Morphogenesis', 'Journal Article', '10.1371/journal.pcbi.1006455', '30303951', 'The morphogenesis of sex combs (SCs), a male trait in many species of fruit flies, is an excellent system in which to study the cell biology, genetics and evolution of a trait. In Drosophila melanogaster, where the incipient SC rotates from horizontal to a vertical position, three signal comb properties have been documented: length, final angle and shape (linearity). During SC rotation, in which many cellular processes are occurring both spatially and temporally, it is difficult to distinguish which processes are crucial for which attributes of the comb. We have used a novel approach combining simulations and experiments to uncover the spatio-temporal dynamics underlying SC rotation. Our results indicate that 1) the final SC shape is primarily controlled by the inhomogeneity of initial cell size in cells close to the immature comb, 2) the final angle is primarily controlled by later cell expansion and 3) a temporal sequence of cell expansion mitigates the malformations generally associated with longer rotated SCs. Overall, our work has linked together the morphological diversity of SCs and the cellular dynamics behind such diversity, thus providing important insights on how evolution may affect SC development via the behaviours of surrounding epithelial cells.'),
(89270, 2018, 'plos', 'Modeling effects of voltage dependent properties of the cardiac muscarinic receptor on human sinus node function', 'Moss, Robin|Sachse, Frank B|Moreno-Galindo, Eloy G|Navarro-Polanco, Ricardo A|Tristani-Firouzi, Martin|Seemann, Gunnar', 'Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg/Bad Krozingen, Freiburg, Germany.|Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, Utah, United States of America.|Centro Universitario de Investigaciones Biomédicas, Universidad de Colima, Colima, Mexico.|Centro Universitario de Investigaciones Biomédicas, Universidad de Colima, Colima, Mexico.|Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, Utah, United States of America.|Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg/Bad Krozingen, Freiburg, Germany.', 'Germany|United States|Mexico|Mexico|United States|Germany', 3, 'Acetylcholine|Computational Biology|Humans|Markov Chains|Models, Cardiovascular|Receptor, Muscarinic M2|Sinoatrial Node', 'Journal Article', '10.1371/journal.pcbi.1006438', '30303952', 'The cardiac muscarinic receptor (M2R) regulates heart rate, in part, by modulating the acetylcholine (ACh) activated K+ current IK,ACh through dissociation of G-proteins, that in turn activate KACh channels. Recently, M2Rs were noted to exhibit intrinsic voltage sensitivity, i.e. their affinity for ligands varies in a voltage dependent manner. The voltage sensitivity of M2R implies that the affinity for ACh (and thus the ACh effect) varies throughout the time course of a cardiac electrical cycle. The aim of this study was to investigate the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potentials in physiological and pathophysiological conditions. We developed a Markovian model of the IK,ACh modulation by voltage and integrated it into a computational model of human sinus node. We performed simulations with the integrated model varying ACh concentration and voltage sensitivity. Low ACh exerted a larger effect on IK,ACh at hyperpolarized versus depolarized membrane voltages. This led to a slowing of the pacemaker rate due to an attenuated slope of phase 4 depolarization with only marginal effect on action potential duration and amplitude. We also simulated the theoretical effects of genetic variants that alter the voltage sensitivity of M2R. Modest negative shifts in voltage sensitivity, predicted to increase the affinity of the receptor for ACh, slowed the rate of phase 4 depolarization and slowed heart rate, while modest positive shifts increased heart rate. These simulations support our hypothesis that altered M2R voltage sensitivity contributes to disease and provide a novel mechanistic foundation to study clinical disorders such as atrial fibrillation and inappropriate sinus tachycardia.');
