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174 results for “pericytes”
Research data supporting "Pericyte seeded dual peptide scaffold with improved endothelialization for vascular graft tissue engineering"
<p>Raw research data supporting the paper:</p> <p>Campagnolo, P. <em>et al</em>., Pericyte seeded dual peptide scaffold with improved endothelialization for vascular graft tissue engineering, 2016, Advanced Healthcare Materials, 5(23), 3046-3055.</p> <p> </p>
Data for: Pericytes' Circadian Clock Affects Endothelial Cells' Synchronization and Angiogenesis in a 3D Tissue Engineered Scaffold
<p>Raw data set and analysis files for Mastrullo et al., Frontiers in Pharmacology, 2022 <strong>DOI:</strong> 10.3389/fphar.2022.867070 </p>
Time-averaged simulations results for bi-phasic blood flow simulations in realistic microvascular networks for multi-capillary dilation scenarios mimicking pericyte ablation
<p>Documentation to reproduce in silico analyses related to the manuscript<br> <strong>Pericyte remodelling is deficient in the aged brain and contributes to impaired capillary flow and structure</strong></p> <p>by</p> <p>Andrée-Anne Berthiaume, Franca Schmid, Stefan Stamenkovic, Vanessa Coelho-Santos, Cara D. Nielson, Bruno Weber, Mark W. Majesky and Andy Y. Shih</p> <p>Published in<br> Nature Communications (doi: 10.1038/s41467-022-33464-w)</p> <p>All simulations are performed based on the in silico blood flow model with discrete red blood cell (RBC) tracking as described in Schmid et al., 2017, PLoS Comp Biol (doi: <a href="https://doi.org/10.1371/journal.pcbi.1005392">10.1371/journal.pcbi.1005392</a>). The bi-phasic blood flow simulations have been performed in two realistic microvascular networks from the somatosensory cortex of the mouse first published in Blinder et al., 2013, Nature Neuroscience (doi: 10.1038/nn.3426). </p> <p>For further information and instructions please contact Franca Schmid (franca.schmid@unibe.ch, orcid.org/0000-0002-0689-9366).</p> <p><br> <strong>Simulation results:</strong></p> <p>All time-averaged simulation results are saved as vascular graphs building on the python library igraph and stored as python pickle files (Python 2.7). For each simulation two files are available: <em>verticesDict.pkl</em> and <em>edgesDict.pkl</em>containing all vertex and edge specific data, respectively. A summary of the vertex and edge attributes is provided below. The folder <em>Baseline</em> contains the simulation results for microvascular network 1 (MVN1) and MVN2 for the reference simulation, i.e. without any dilation. Folder <em>Dilated</em> contains the simulation results mimicking the four pericyte ablation scenarios. Subfolders <em>dc_x.x</em> contain the simulation results for the different diameter changes. Note that, folder <em>dc_0.0</em> contains no new simulation results but is a dummy folder containing the information about the vessels to be dilated for the different dilation scenarios (namely edge attribute: <em>toDilate</em> and <em>base_capillary</em>). </p> <p> </p> <p><strong>Reproducing figure 8:</strong></p> <p>Panels a-c: created by illustrating the simulation results with the open source software Paraview (v5.7.0).<br> Panels d-f & h: can be generated by executing make_all_figures.py in Python 2.7 within the provided folder structure.<br> Panel g: can be generated by executing make_figure_8g.py after installation of the the vgm-framework (further information see below). </p> <p><br> Output: All created Figures are saved in the folder <em>Figures</em>. The associated source data is available in Excel format in the folder <em>SourceData</em>.</p> <p> </p> <p><strong>Edge attributes:</strong></p> <p>diameter: vessel diameter [µm]<br> mainAV: 1 if ascending venule main branch, 0 otherwise<br> connectivity: vertex tuple to define location of edge<br> flow: flow rate [µm<sup>3</sup>/ms]<br> mainDA: 1 if descending arteriole main branch, 0 otherwise<br> nkind: 0: pial artery, 1: pial vein, 2: descending arteriole, 3: ascending venule, 4: capillary<br> htt: tube hematocrit [-]<br> toDilate: 1 if vessel is dilated for the current dilation scenario, 0 otherwise<br> base_capillary: 1 if vessel is the base capillary of the current dilation scenario, 0 otherwise</p> <p> </p> <p><strong>Vertex attributes:</strong></p> <p>index: vertex index<br> pressure: pressure [mmHg]<br> nkind: 0: pial artery, 1: pial vein, 2: descending arteriole, 3: ascending venule, 4: capillary<br> coords: vertex coordinates x,y,z [µm]<br> pBC: pressure boundary conditions at inflow vertices [mmHg], None at internal nodes</p> <p> </p> <p><strong>Obtaining simulation results:</strong><br> General:</p> <ul> <li>Running bi-phasic blood flow simulations requires setting-up the vgm-framework available at: <a href="https://github.com/Franculino/vgm.git">https://github.com/Franculino/vgm.git</a> (v.1.0).</li> <li>vgm is written in Python 2.7 and builds on standard python libraries.</li> <li>vgm has been used on macOS, Ubuntu and Windows Systems.</li> <li>Installation time < 5min. Further details available within the vgm README.</li> <li>Runtime depends on the network size, the chosen blood flow model and the initial conditions (e.g. ~8hrs for a Restart simulation of MVN1 with the bi-phasic blood flow model, see Restarty.py).</li> <li>scripts/Test.py provides an example how a simulation can be initiated. A Demo case is provided (details see below).</li> <li>Output: sampledict_BackUp_xx.pkl</li> <li>The bi-phasic blood flow model can be applied on all kind of microvascular graphs.</li> </ul> <p>Specific for current application:</p> <ul> <li>Simulations are a restart on the statistical steady state of the baseline cases.</li> <li>All relevant pre-processing functions for the current study are available in scripts/find_stroke_locations.py. Further details are available from the definition of the different functions.</li> <li>The simulations are initiated with scripts/Restart.py.</li> <li>To obtain the time-averaged simulation results scripts/01_put_together_sampledicts.py and scripts/02_convergenceDiscrete.py need to be executed. This results in the file G_averaged.pkl that is used for further analyses.</li> </ul> <p>Demo:</p> <ul> <li>Contains a small hexagonal microvascular network to test the code.</li> <li>1) Run Test.py to start the simulation</li> <li>2) Run 01_put_together_sampledicts.py</li> <li>3) Run 02_convergenceDiscrete.py to obtain time-averaged results (<em>G_averaged.pkl</em>)</li> </ul>
Supplementary Video 4 Matrigel HUVEC with pericytes
<p>Supplementary Video 4 Matrigel HUVEC with pericytes.</p> <p>Mixed endothelial (green)/pericyte (red) cultures plated on Matrigel.</p>
Supplementary Video 2 HUVEC with pericytes
<p>Supplementary Video 2 HUVEC with pericytes</p>
Environmental Enrichment Induces Pericyte and IgA-Dependent Wound Repair and Lifespan Extension in a Colon Tumor Model [Microbiome]
GEO Series GSE90801. mouse gut metagenome. 41 samples. Type: Other.
Pericyte-like cells generated from human pluripotent stem cells support hematopoietic stem and progenitors ex vivo
GEO Series GSE83443. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
Cardiac pericytes contribute to myofibroblast expansion and vascular maturation following myocardial infarction
GEO Series GSE222417. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
Human cardiac pericytes are susceptible to SARS-CoV-2 infection
GEO Series GSE183850. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Contribution of brain pericytes in blood-brain barrier formation and maintenance: A transcriptomic study of cocultured human endothelial cells derived from hematopoietic stem cells
GEO Series GSE144474. Homo sapiens. 27 samples. Type: Expression profiling by high throughput sequencing.
Brain pericytes and Wnt/β-catenin signaling induce functional blood-brain barrier phenotype in human iPSC-derived model
GEO Series GSE305015. Homo sapiens. 40 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional profiling of human fibroblasts cells from normal, PD patient, and PD patient treatment with mouse cavernous pericyte-derived extracellular vesicles-mimetic nanovesicles (PC-NVs)
GEO Series GSE146500. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Modulation of inflammatory responses in mouse models of pericyte-depletion retinopathy
GEO Series GSE296651. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Determine the role of ALK5 signaling in murine brain pericytes at embryonic day E13.5
GEO Series GSE268575. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Effect of iron exposure on the gene expression profile of human brain vascular pericytes.
GEO Series GSE230184. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Development of a Pericyte-Based Cell-Free Strategy to Recover Aged Skeletal Muscle After Disuse
GEO Series GSE185560. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Programmed genomic instability regulates neural transdifferentiation of human brain microvascular pericytes [DRIP-Seq]
GEO Series GSE187018. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Single cell-resolved study of advanced murine MASH reveals a homeostatic pericyte signaling module
GEO Series GSE218299. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
miRNA profiling of human saphenous vein pericyte exosomes
GEO Series GSE118855. Homo sapiens. 3 samples. Type: Other.
Transcriptomic characterization of lung pericytes in systemic sclerosis associated interstitial lung disease (SSc-ILD)
GEO Series GSE222552. Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
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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)
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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.