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306 results for “mechanical modeling”
Antagonism of CGRP Receptor: Central and Peripheral Mechanisms and Mediators in an Animal Model of Chronic Migraine
<p>This dataset includes the findings obtained in the study aimed at investigating in more depth the interplay between the neuropeptide CGRP and the inflammatory mediators within the mechanisms of neuronal sensitization in an animal model of chronic migraine, using olcegepant as a pharmacological probe. Male Sprague-Dawley rats were exposed to nitroglycerin (NTG, 10 mg/kg, i.p.) or NTG vehicle and treated with the CGRP receptor antagonist olcegepant (1 or 2 mg/kg, i.p.) or vehicle (1 ml/kg, i.p.) 1h before the orofacial formalin test. Additionally, sets of rats received NTG (5 mg/kg, i.p.) or vehicle (equivalent volume) co-administered with olcegepant (2 mg/kg i.p.) or its vehicle every other day over a 9-day period. Twenty-four hours after the last injection of NTG (or vehicle), a first set of rats underwent the orofacial formalin test. In a second set, we evaluated the gene expression of CGRP and gene and protein expression of pro-inflammatory cytokines in specific areas involved in migraine pain. We also assessed the CGRP and cytokine levels in serum.</p> <p>The in vivo and ex vivo assessments were:</p> <p>1) Pain-related behavior in the orofacial formalin test: the face rubbing was measured counting the seconds the animal spent grooming the injected area (upper lip, lateral to the nose) with the ipsilateral forepaw or hindpaw 0–6 min (Phase I) or 12–45 min (Phase II) after formalin injection (50 µl, s.c.). The observation time was divided into 15 blocks of 3 min each.</p> <p>2) mRNA expression levels: CGRP, tumor necrosis factor-alpha (TNF-alpha), interleukin-1beta (IL-1beta), transient receptor potential ankyrin 1 (TRPA1) in cervical spinal cord (CSC), medulla-pons and trigeminal ganglia (TGs). mRNA levels were measured by rt-PCR. The same RNA was used for miRNAs (Mir-34a-5p, Mir-382-5p, Mir-155-5p) extraction in the same areas. All samples were assayed in triplicate and gene expression levels were calculated according to 2−∆∆Ct = 2− (∆Ct gene − ∆Ct housekeeping gene) formula by using Ct (cycle threshold) values.</p> <p>3) Pro-inflammatory cytokines in medulla-pons, CSC and TGs were evaluated using ELISA procedure. CGRP, TNF-alpha and IL-1beta serum levels were measured using commercial ELISA kits.</p> <p>Results in brief</p> <p>Olcegepant attenuated nitroglycerin-induced trigeminal hyperalgesia in the second phase of the orofacial formalin test. Interestingly, it also reduced gene expression and protein levels of CGRP, pro-inflammatory cytokines, inflammatory-associated miRNAs (miR-155-5p, miR-382-5p and miR-34a-5p) and TRPA1 channels in medulla-pons area, cervical spinal cord and trigeminal ganglia. Similarly, olcegepant reduced the NTG-induced increase of CGRP and inflammatory.</p>
The weaken-fill-repair model for cell budding: Linking cell wall biosynthesis with mechanics
<p>The interplay between cellular mechanics and other biochemical processes leading to the cell cycle is poorly understood. Here, we propose a quantitative model of the mechanism of cell budding, particularly for Saccharomyces cerevisiae, as a ''weaken-fill-repair'' process. This model links Newtonian mechanics over the cell wall with biochemical processes that change the mechanical properties of the wall. Our model shows that: (1) The oscillatory behavior in the size of the mother compartment during cell division, as observed experimentally, is an inevitable consequence of the budding mechanism; (2) The asymmetry of cell division is necessary for the daughter cell to maintain mechanical stiffness; (3) Although different aspects of a cell are strictly constrained and intricately interconnected, the budding process is governed by a single reduced parameter that, when at an appropriate value, can automatically achieve homeostasis. Our quantitative model of the evolution of cell walls and their impact on cell division could provide valuable insights into cell morphology from a system perspective. This knowledge could be instrumental in developing effective antimicrobial treatments against microorganisms with cell walls and even in building synthetic cells.</p>
Quantum mechanical modeling of the on-grain formation of acetaldehyde on H2O:CO dirty ice surfaces
<p>This Supporting Material contains:</p> <ul> <li>Cartesian coordinates of HF-3c optimized minima and transition state for the reaction in gas phase, in .xyz format, computed using <a href="https://gaussian.com/">Gaussian16</a> code;</li> <li>Fractional coordinates of HF-3c optimized minima and trasition state structures for crystalline periodic models in <a href="https://www.moldraw.unito.it/_sgg/m1m1s43_1.htm">.mol</a> format, editable with <a href="http://www.moldraw.unito.it/">MOLDRAW</a>, computed using <a href="http://www.crystal.unito.it/">CRYSTAL17</a> computer code.</li> </ul>
Mechanisms of Pain Hypersensitivity in a Human Skin Inflammation Model
ClinicalTrials.gov study NCT07092215. IPD Sharing: YES. Countries: 1. Publications: 12.
Plant root growth against a mechanical obstacle: The early growth response of a maize root facing an axial resistance is consistent with the Lockhart model
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Finite element models from: Mechanical compensation in the evolution of the early hominin feeding apparatus
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Data from: Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection
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Using demographic model selection to untangle allopatric divergence and diversification mechanisms in the Rheum palmatum complex in the Eastern Asiatic Region
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Universality in the mechanical behavior of vertex models for biological tissues
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The weaken-fill-repair model for cell budding: Linking cell wall biosynthesis with mechanics
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Data from : In vivo mechanical characterisation of an arterial wall using an inverse analysis procedure: application on an animal model of intracranial aneurysm
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Matlab applications for: A mechanical model to interpret distributed fiber optic strain measurement at displacement discontinuities
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The dataset for Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling
<p>All data of model results for the paper <em>Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling</em>.</p> <p>Contents of this dataset includes:</p> <p>A list for models and data of model results are provided in the zip file. </p> <p>The files suffixed *.grd are grid datas that can be draw by GMT.</p> <p>The files suffixed *.info are datas of the evolution of volume of the continental crust and TTGs in the model.</p> <p>The files suffixed *.prn are datas of P-T condtions of continental crust generation by partial melting.</p> <p>The files suffixed *.py are python codes for visualization of the volume of continental crust and P-T datas.</p>
Data from: A statistical mechanics framework for constructing non-equilibrium thermodynamic models
<p><span>Far-from-equilibrium phenomena are critical to all natural and engi</span><span>neered systems, and essential to biological processes responsible </span><span>for life. For over a century and a half, since Carnot, Clausius, Maxwell, </span><span>Boltzmann, and Gibbs, among many others, laid the foundation for </span><span>our understanding of equilibrium processes, scientists and engineers </span><span>have dreamed of an analogous treatment of non-equilibrium systems. </span><span>But despite tremendous efforts, a universal theory of non-equilibrium </span><span>behavior akin to equilibrium statistical mechanics and thermodynam</span><span>ics has evaded description. Several methodologies have proved their </span><span>ability to accurately describe complex non-equilibrium systems at </span><span>the macroscopic scale, but their accuracy and predictive capacity is </span><span>predicated on either phenomenological kinetic equations fit to mi</span><span>croscopic data, or on running concurrent simulations at the particle </span><span>level. Instead, we provide a framework for deriving stand-alone macro</span><span>scopic thermodynamics models directly from microscopic physics </span><span>without fitting in overdamped Langevin systems.</span> <span>The only neces</span><span>sary ingredient is a functional form for a parameterized, approximate </span><span>density of states, in analogy to the assumption of a uniform density </span><span>of states in the equilibrium microcanonical ensemble. We highlight </span><span>this framework's effectiveness by deriving analytical approximations </span><span>for evolving mechanical and thermodynamic quantities in a model of </span><span>coiled-coil proteins and double stranded DNA, thus producing, to the </span><span>authors' knowledge, the first derivation of the governing equations for </span><span>a phase propagating system under general loading conditions without </span><span>appeal to phenomenology. The generality of our treatment allows </span><span>for application to any system described by Langevin dynamics with </span><span>arbitrary interaction energies and external driving, including colloidal </span><span>macromolecules, hydrogels, and biopolymers.</span></p>
Structural insights into distinct mechanisms of RNA polymerase II and III recruitment to snRNA promoters - segmented EM density used in integrative modeling
<p>segmented cryoEM map and derived gaussian mixture model used in the integrative modeling of the human SNAPc complex </p>
Source data and codes for the paper "Inviting atomic mechanics to macro-continua: A study on monocrystalline Si using a spatial multilevel coarsening model"
<p>Source data and codes for the paper "Inviting atomic mechanics to macro-continua: A study on monocrystalline Si using a spatial multilevel coarsening model"</p> <p>This file includes </p> <p>- Source data for Figs 1-5 and Supplementary Materials</p> <p>- LAMMPS codes and raw log files used to produce the results of this study</p> <p> </p>
Dataset S4-6: Leveraging co-evolutionary insights and AI-based structural modeling to unravel receptor-peptide ligand-binding mechanisms
<h3>Significance statement:</h3> <p>This study presents proof-of-concept for a rapid and inexpensive alternative to classical structure-based approaches for resolving ligand-receptor binding mechanisms. It relies on a multilayered bioinformatic approach that leverages genomic data across diverse species in combination with AI-based structural modeling to identify true ligand and receptor homologues, and subsequently predict their binding mechanisms. <em>In silico </em>findings were validated by multiple experimental approaches, which investigated the effect of amino acid changes in the proposed binding pockets on ligand-binding, complex formation with a co-receptor essential for downstream signaling, and activation of downstream signaling. Our analysis combining evolutionary insights, <em>in silico</em> modeling and functional validation provides a framework for structure-function analysis of other peptide-receptor pairs, which could be easily implemented by most laboratories.</p> <h3><span>Zip file contains:</span></h3> <p><span>Dataset S4:</span><span> </span><strong><span>Plasmid maps of constructs used in this study.</span></strong></p> <p><span>Dataset S5:</span><span> </span><strong><span>AFM and AF3 predicted structures (.pdb) and AFM confidence metrics (.pae)</span></strong></p> <p><span>Dataset S6:</span><span> </span><strong><span>Unedited files (.tiff) of co-IP and western blotting.</span></strong></p>
Data: Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships
<p>Data and code related to 'Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships' to reproduce figures and analyses.</p>
Dataset for downscaling, used in downscaled Spatiotemporal Precipitation Model Based on a Transformer Attention Mechanism
<p>In this research, we introduce a novel method leveraging the Transformer architecture to generate high-fidelity precipitation model outputs. This technique emulates the statistical characteristics of high-resolution datasets while substantially lowering computational expenses. The core concept involves utilizing a blend of coarse and fine-grained simulated precipitation data, encompassing diverse spatial resolutions and geospatial distributions, to instruct the neural network in the transformation process. We have crafted an innovative ST-Transformer encoder component that dynamically concentrates on various regions, allocating heightened focus to critical spatial zones or sectors. This tailored module is instrumental in enhancing the model's ability to generate outcomes that are not only more true-to-life but also more consistent with physical laws. It adeptly mirrors the temporal and spatial fluctuations in precipitation data and adeptly represents extreme weather events, such as heavy and enduring storms. The efficacy and superiority of our proposed approach are substantiated through a comparative analysis with several cutting-edge forecasting techniques. This evaluation is conducted on two distinct datasets, each derived from simulations run by regional climate models over a period of four months. The datasets vary in their spatial resolutions, with one featuring a 50-kilometer resolution and the other a 12-kilometer resolution, both sourced from the Weather Research and Forecasting (WRF) Model.</p>
Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila
<p></p><p>3D eukaryotic genome organization provides the structural basis for gene regulation. In Drosophila melanogaster, genome folding is characterized by somatic homolog pairing, where homologous chromosomes are intimately paired from end to end; however, how homologs identify one another and pair has remained mysterious. Recently, this process has been proposed to be driven by specifically interacting 'buttons' encoded along chromosomes. Here, we turned this hypothesis into a quantitative biophysical model to demonstrate that a button-based mechanism can lead to chromosome-wide pairing. We tested our model using live-imaging measurements of chromosomal loci tagged with the MS2 and PP7 nascent RNA labeling systems. We show solid agreement between model predictions and experiments in the pairing dynamics of individual homologous loci. Our results strongly support a button-based mechanism of somatic homolog pairing in Drosophila and provide a theoretical framework for revealing the molecular identity and regulation of buttons.</p><p></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.