Virtual neural network-guided optimization of non-invasive brain stimulation in Alzheimer ’s disease
by Janne J. Luppi, Cornelis J. Stam, Philip Scheltens, Willem de Haan
Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique with potential for counteracting disrupted brain network activity in Alzheimer ’s disease (AD) to improve cognition. However, the results of tDCS studies in AD have been variable due to different methodological choices such as electrode placement. To address this, a virtual brain network model of AD was used to explore tDCS optimization. We compared a large, representative s et of virtual tDCS intervention setups, to identify the theoretically optimized tDCS e...
Source: PLoS Computational Biology - January 17, 2024 Category: Biology Authors: Janne J. Luppi Source Type: research
Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions
by Paul J. N. Brodersen, Hannah Alfonsa, Lukas B. Krone, Cristina Blanco-Duque, Angus S. Fisk, Sarah J. Flaherty, Mathilde C. C. Guillaumin, Yi-Ge Huang, Martin C. Kahn, Laura E. McKillop, Linus Milinski, Lewis Taylor, Christopher W. Thomas, Tomoko Yamagata, Russell G. Foster, Vladyslav V. Vyazovskiy, Colin J. Akerman
Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awak...
Source: PLoS Computational Biology - January 17, 2024 Category: Biology Authors: Paul J. N. Brodersen Source Type: research
Transcription factor interactions explain the context-dependent activity of CRX binding sites
by Kaiser J. Loell, Ryan Z. Friedman, Connie A. Myers, Joseph C. Corbo, Barak A. Cohen, Michael A. White
The effects of transcription factor binding sites (TFBSs) on the activity of acis-regulatory element (CRE) depend on the local sequence context. In rod photoreceptors, binding sites for the transcription factor (TF) Cone-rod homeobox (CRX) occur in both enhancers and silencers, but the sequence context that determines whether CRX binding sites contribute to activation or repression of transcription is not understood. To investigate the context-dependent activity of CRX sites, we fit neural network-based models to the a...
Source: PLoS Computational Biology - January 16, 2024 Category: Biology Authors: Kaiser J. Loell Source Type: research
Gene expression bias between the subgenomes of allopolyploid hybrids is an emergent property of the kinetics of expression
by Hong An, J. Chris Pires, Gavin C. Conant
Hybridization coupled to polyploidy, or allopolyploidy, has dramatically shaped the evolution of flowering plants, teleost fishes, and other lineages. Studies of recently formed allopolyploid plants have shown that the two subgenomes that merged to form that new allopolyploid do not generally express their genes equally. Instead, one of the two subgenomes expresses its paralogs more highly on average. Meanwhile, older allopolyploidy events tend to show biases in duplicate losses, with one of the two subgenomes retaining more genes than the other. Since reduced expression is a pa...
Source: PLoS Computational Biology - January 16, 2024 Category: Biology Authors: Hong An Source Type: research
Controlling target brain regions by optimal selection of input nodes
by Karan Kabbur Hanumanthappa Manjunatha, Giorgia Baron, Danilo Benozzo, Erica Silvestri, Maurizio Corbetta, Alessandro Chiuso, Alessandra Bertoldo, Samir Suweis, Michele Allegra
The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain. However, the current applicability of the framework is limited by inappropriate modeling of brain dynamics, and an overly ambitious focus on whole-brain activity control. In this work, we leverage recent progress in linear modeling of brain dynamics (effective connectivity) and we exploit the co...
Source: PLoS Computational Biology - January 12, 2024 Category: Biology Authors: Karan Kabbur Hanumanthappa Manjunatha Source Type: research
Tracking conformational transitions of the gonadotropin hormone receptors in a bilayer of (SDPC) poly-unsaturated lipids from all-atom molecular dynamics simulations
In this study, we performed molecular dynamics (MD) simulations to identify the conformational changes of the FSHR and LHCGR. We set up a FSHR structure as predicted by AlphaFold (AF-P23945); for the LHCGR structure we took the cryo-electron microscopy structure for the active state (PDB:7FII) as initial coordinates. Specifically, the flexibility of the HR domain and the correlated motions of the LRR and TM domain were analyzed. From the conformational changes of the LRR, TM domain, and HR we explored the conformational landscape by means of MD trajectories in all-atom approximation, including a membrane of polyunsaturated...
Source: PLoS Computational Biology - January 11, 2024 Category: Biology Authors: Eduardo Jard ón-Valadez Source Type: research
Tissue-adjusted pathway analysis of cancer (TPAC): A novel approach for quantifying tumor-specific gene set dysregulation relative to normal tissue
We describe a novel single sample gene set testing method for cancer transcriptomics data named tissue-adjusted pathway analysis of cancer (TPAC). The TPAC method leverages information about the normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies gene set dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data for 21 solid human cancers from The Cancer Genome Atlas (TCGA) and associated ...
Source: PLoS Computational Biology - January 11, 2024 Category: Biology Authors: H. Robert Frost Source Type: research
Transformations of sensory information in the brain suggest changing criteria for optimality
by Tyler S. Manning, Emma Alexander, Bruce G. Cumming, Gregory C. DeAngelis, Xin Huang, Emily A. Cooper
Neurons throughout the brain modulate their firing rate lawfully in response to sensory input. Theories of neural computation posit that these modulations reflect the outcome of a constrained optimization in which neurons aim to robustly and efficiently represent sensory information. Our understanding of how this optimization varies across different areas in the brain, however, is still in its infancy. Here, we show that neural sensory responses transform along the dorsal stream of the visual system in a manner consiste...
Source: PLoS Computational Biology - January 11, 2024 Category: Biology Authors: Tyler S. Manning Source Type: research
Systems approach for congruence and selection of cancer models towards precision medicine
by Jian Zou, Osama Shah, Yu-Chiao Chiu, Tianzhou Ma, Jennifer M. Atkinson, Steffi Oesterreich, Adrian V. Lee, George C. Tseng
Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selecti...
Source: PLoS Computational Biology - January 10, 2024 Category: Biology Authors: Jian Zou Source Type: research
Joint representation of molecular networks from multiple species improves gene classification
by Christopher A. Mancuso, Kayla A. Johnson, Renming Liu, Arjun Krishnan
Network-based machine learning (ML) has the potential for predicting novel genes associated with nearly any health and disease context. However, this approach often uses network information from only the single species under consideration even though networks for most species are noisy and incomplete. While some recent methods have begun addressing this shortcoming by using networks from more than one species, they lack one or more key desirable properties: handling networks from more than two species simultaneously, incorporating many-to-many orthol...
Source: PLoS Computational Biology - January 10, 2024 Category: Biology Authors: Christopher A. Mancuso Source Type: research
High-performing neural network models of visual cortex benefit from high latent dimensionality
by Eric Elmoznino, Michael F. Bonner
Geometric descriptions of deep neural networks (DNNs) have the potential to uncover core representational principles of computational models in neuroscience. Here we examined the geometry of DNN models of visual cortex by quantifying the latent dimensionality of their natural image representations. A popular view holds that optimal DNNs compress their representations onto low-dimensional subspaces to achieve invariance and robustness, which suggests that better models of visual cortex should have lower dimensional geometries. Surprisingly, we found a strong trend in the opposite direct...
Source: PLoS Computational Biology - January 10, 2024 Category: Biology Authors: Eric Elmoznino Source Type: research
Adaptive foraging of pollinators fosters gradual tipping under resource competition and rapid environmental change
by Sjoerd Terpstra, Fl ávia M. D. Marquitti, Vítor V. Vasconcelos
Plant and pollinator communities are vital for transnational food chains. Like many natural systems, they are affected by global change: rapidly deteriorating conditions threaten their numbers. Previous theoretical studies identified the potential for community-wide collapse above critical levels of environmental stressors —so-called bifurcation-induced tipping points. Fortunately, even as conditions deteriorate, individuals have some adaptive capacity, potentially increasing the boundary for a safe operating space where changes in ecological processes ...
Source: PLoS Computational Biology - January 9, 2024 Category: Biology Authors: Sjoerd Terpstra Source Type: research
Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells
by Paul F. Lang, David R. Penas, Julio R. Banga, Daniel Weindl, Bela Novak
The mammalian cell cycle is regulated by a well-studied but complex biochemical reaction system. Computational models provide a particularly systematic and systemic description of the mechanisms governing mammalian cell cycle control. By combining both state-of-the-art multiplexed experimental methods and powerful computational tools, this work aims at improving on these models along four dimensions: model structure, validation data, validation methodology and model reusability.
We developed a comprehensive model structure of the full cell cycle th...
Source: PLoS Computational Biology - January 8, 2024 Category: Biology Authors: Paul F. Lang Source Type: research
Plasticity of growth laws tunes resource allocation strategies in bacteria
by Avik Mukherjee, Yu-Fang Chang, Yanqing Huang, Nina Catherine Benites, Leander Ammar, Jade Ealy, Mark Polk, Markus Basan
Bacteria likeE.coli grow at vastly different rates on different substrates, however, the precise reason for this variability is poorly understood. Different growth rates have been attributed to ‘nutrient quality’, a key parameter in bacterial growth laws. However, it remains unclear to what extent nutrient quality is rooted in fundamental biochemical constraints like the energy content of nutrients, the protein cost required for their uptake and catabolism, or the capacity of the plasm a membrane ...
Source: PLoS Computational Biology - January 8, 2024 Category: Biology Authors: Avik Mukherjee Source Type: research
MEDUSA: A cloud-based tool for the analysis of X-ray diffuse scattering to obtain the bending modulus from oriented membrane stacks
by Sebastian Himbert, Dorian Gaboo, Emre Brookes, John F. Nagle, Maikel C. Rheinst ädter
An important mechanical property of cells is their membrane bending modulus,κ. Here, we introduce MEDUSA (MEmbrane DiffUse Scattering Analysis), a cloud-based analysis tool to determine the bending modulus,κ, from the analysis of X-ray diffuse scattering. MEDUSA uses GPU (graphics processing unit) accelerated hardware and a parallelized algorithm to run the calculations efficiently in a few seconds. MEDUSA ’s graphical user interface allows the user to upload 2-dimensional data collected from different sources, perform background...
Source: PLoS Computational Biology - January 8, 2024 Category: Biology Authors: Sebastian Himbert Source Type: research
