A simulation framework to determine optimal strength training and musculoskeletal geometry for sprinting and distance running
In this study, we developed a novel musculoskeletal simulator that is differentiable with respect to musculoskeletal geometry and muscle volumes. This simulator enabled us to find the optimal body segment dimensions and optimal distribution of added muscle volume for sprinting and marathon running. Our simulation results replicate experimental observations, such as increased muscle mass in sprinters, as well as a mass in the lower end of the healthy BMI range and a higher leg-length-to-height ratio in marathon runners. The simulations also reveal new relationships, for example showing that hip musculature is vital to both ...
Source: PLoS Computational Biology - February 23, 2024 Category: Biology Authors: Tom Van Wouwe Source Type: research
Shared input and recurrency in neural networks for metabolically efficient information transmission
by Tomas Barta, Lubomir Kostal
Shared input to a population of neurons induces noise correlations, which can decrease the information carried by a population activity. Inhibitory feedback in recurrent neural networks can reduce the noise correlations and thus increase the information carried by the population activity. However, the activity of inhibitory neurons is costly. This inhibitory feedback decreases the gain of the population. Thus, depolarization of its neurons requires stronger excitatory synaptic input, which is associated with higher ATP consumption. Given that the goal of neural populations is to transmit as ...
Source: PLoS Computational Biology - February 23, 2024 Category: Biology Authors: Tomas Barta Source Type: research
Age-dependent ventilator-induced lung injury: Mathematical modeling, experimental data, and statistical analysis
by Quintessa Hay, Christopher Grubb, Sarah Minucci, Michael S. Valentine, Jennifer Van Mullekom, Rebecca L. Heise, Angela M. Reynolds
A variety of pulmonary insults can prompt the need for life-saving mechanical ventilation; however, misuse, prolonged use, or an excessive inflammatory response, can result in ventilator-induced lung injury. Past research has observed an increased instance of respiratory distress in older patients and differences in the inflammatory response. To address this, we performed high pressure ventilation on young (2-3 months) and old (20-25 months) mice for 2 hours and collected data for macrophag...
Source: PLoS Computational Biology - February 22, 2024 Category: Biology Authors: Quintessa Hay Source Type: research
Genome scale metabolic network modelling for metabolic profile predictions
In this study, we present SAMBA (SAMpling Biomarker Analysis), an approach which simulates fluxes in exchange reactions following a metabolic perturbation using random sampling, compares the simulated flux distributions between the baseline and modulated conditions, and ranks predicted differentially exchanged metabolites as potential biomarkers for the perturbation. We show that there is a good fit between simulated metabolic exchange profiles and experimental differential metabolites detected in plasma, such as patient data from the disease database OMIM, and metabolic trait-SNP associations found in mGWAS studies. These...
Source: PLoS Computational Biology - February 22, 2024 Category: Biology Authors: Juliette Cooke Source Type: research
Diverse mutant selection windows shape spatial heterogeneity in evolving populations
by Eshan S. King, Dagim S. Tadele, Beck Pierce, Michael Hinczewski, Jacob G. Scott
Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model withN alleles, which maps genotype to fitness, allows comparisons betweenN genotypes simultaneously, but does not encode continuous drug response data. In clinical ...
Source: PLoS Computational Biology - February 22, 2024 Category: Biology Authors: Eshan S. King Source Type: research
A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization
by Lily Monnier, Paul-Henry Courn ède
Single-cell RNA sequencing (scRNA-seq) technology produces an unprecedented resolution at the level of a unique cell, raising great hopes in medicine. Nevertheless, scRNA-seq data suffer from high variations due to the experimental conditions, called batch effects, preventing any aggregated downstream analysis. Adversarial Information Factorization provides a robust batch-effect correction method that does not rely on prior knowledge of the cell types nor a specific normalization strategy while being adapted to any downstream analysis task. It compares to and even outperforms state-o...
Source: PLoS Computational Biology - February 22, 2024 Category: Biology Authors: Lily Monnier Source Type: research
EPINEST, an agent-based model to simulate epidemic dynamics in large-scale poultry production and distribution networks
by Francesco Pinotti, Jos é Lourenço, Sunetra Gupta, Suman Das Gupta, Joerg Henning, Damer Blake, Fiona Tomley, Tony Barnett, Dirk Pfeiffer, Md. Ahasanul Hoque, Guillaume Fournié
The rapid intensification of poultry production raises important concerns about the associated risks of zoonotic infections. Here, we introduce EPINEST (EPIdemic NEtwork Simulation in poultry Transportation systems): an agent-based modelling framework designed to simulate pathogen transmission within realistic poultry production and distribution networks. We provide example applications to broiler production in Bangladesh, but the modular stru...
Source: PLoS Computational Biology - February 21, 2024 Category: Biology Authors: Francesco Pinotti Source Type: research
Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus
by Alexander D. Bird, Hermann C.z, Peter Jedlicka
Pattern separation is a valuable computational function performed by neuronal circuits, such as the dentate gyrus, where dissimilarity between inputs is increased, reducing noise and increasing the storage capacity of downstream networks. Pattern separation is studied from bothin vivo experimental and computational perspectives and, a number of different measures (such as orthogonalisation, decorrelation, or spike train distance) have been applied to quantify the process of pattern separation. However, these are known to give conclusions that can differ qualitatively depen...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Alexander D. Bird Source Type: research
Ecological and evolutionary dynamics of cell-virus-virophage systems
by Jose Gabriel Nino Barreat, Aris Katzourakis
Microbial eukaryotes, giant viruses and virophages form a unique hyperparasitic system. Virophages are parasites of the virus transcription machinery and can interfere with virus replication, resulting in a benefit to the eukaryotic host population. Surprisingly, virophages can integrate into the genomes of their cell or virus hosts, and have been shown to reactivate during coinfection. This raises questions about the role of integration in the dynamics of cell-virus-virophage systems. We use mathematical models and computational simulations to understand the effect of viroph...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Jose Gabriel Nino Barreat Source Type: research
The successor representation subserves hierarchical abstraction for goal-directed behavior
by Sven Wientjes, Clay B. Holroyd
Humans have the ability to craft abstract, temporally extended and hierarchically organized plans. For instance, when considering how to make spaghetti for dinner, we typically concern ourselves with useful “subgoals” in the task, such as cutting onions, boiling pasta, and cooking a sauce, rather than particulars such as how many cuts to make to the onion, or exactly which muscles to contract. A core question is how such decomposition of a more abstract task into logical subtasks happens in the fir st place. Previous research has shown that humans are sensitive to a form of higher-ord...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Sven Wientjes Source Type: research
Inference of annealed protein fitness landscapes with AnnealDCA
by Luca Sesta, Andrea Pagnani, Jorge Fernandez-de-Cossio-Diaz, Guido Uguzzoni
The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-throughput screening methods have been developed to systematically evaluate protein activity, but only a small fraction of possible protein variants can be tested using these techniques. Computational models that explore the sequence spacein-silico to identify the fittest molecules for a given function are needed to overcome this limitation. In this article, we propose AnnealDCA, a machine-learning fra...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Luca Sesta Source Type: research
Fast adaptation to rule switching using neuronal surprise
by Martin L. L. R. Barry, Wulfram Gerstner
In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signal is extracted from an increase in neural activity after an imbalance of excitation and inhibition. The surprise signal modulates synaptic plasticity via a three-factor learning rule which increases plasticity at moments of surprise. The surprise signal remains small when transitions between sensory events follow a previously le...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Martin L. L. R. Barry Source Type: research
Intra-ripple frequency accommodation in an inhibitory network model for hippocampal ripple oscillations
by Natalie Schieferstein, Tilo Schwalger, Benjamin Lindner, Richard Kempter
Hippocampal ripple oscillations have been implicated in important cognitive functions such as memory consolidation and planning. Multiple computational models have been proposed to explain the emergence of ripple oscillations, relying either on excitation or inhibition as the main pacemaker. Nevertheless, the generating mechanism of ripples remains unclear. An interesting dynamical feature of experimentally measured ripples, which may advance model selection, is intra-ripple frequency accommodation (IFA): a decay of the instantaneous ripple freque...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Natalie Schieferstein Source Type: research
Denoising diffusion probabilistic models for generation of realistic fully-annotated microscopy image datasets
In this study, we demonstrate that diffusion models can effectively generate fully-annotated microscopy image data sets through an unsupervised and intuitive approach, using rough sketches of desired structures as the starting point. The proposed pipeline helps to reduce the reliance on manual annotations when training deep learning-based segmentation approaches and enables the segmentation of diverse datasets without the need for human annotations. We demonstrate that segmentation models trained with a small set of synthetic image data reach accuracy levels comparable to those of generalist models trained with a large and...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Dennis Eschweiler Source Type: research
Connectivity Matrix Seriation via Relaxation
by Alexander Borst
Volume electron microscopy together with computer-based image analysis are yielding neural circuit diagrams of ever larger regions of the brain. These datasets are usually represented in a cell-to-cell connectivity matrix and contain important information about prevalent circuit motifs allowing to directly test various theories on the computation in that brain structure. Of particular interest are the detection of cell assemblies and the quantification of feedback, which can profoundly change circuit properties. While the ordering of cells along the rows and columns doesn ’t change the connectivity, i...
Source: PLoS Computational Biology - February 20, 2024 Category: Biology Authors: Alexander Borst Source Type: research
