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862 results for “Capillary”
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>
Capillaries_contour_lines_and_entrance_coordinates
<p>Dataset containing the information on the contour lines and entrance coordinates for the two capillaries (test and control) for each experimental replicate analyzed in the article: <strong>The distinctive chemotactic responses of three marine herbivore protists to DMSP and related compounds.</strong> </p> <p>Nomenclature:</p> <p>pipette_properties + _+ inital letter of the specie + _ + 1 letter identifying the compound + concentration in uM+ _ + experimental replicate number </p> <p>for example: pipette_properties_G_D20_R3 stands for "<em>Gyrodinium dominans</em>, DMSP, 20 uM, third replicate"</p> <p>can be either a .txt or .json file</p>
Data and STL files supporting article: Encoding Quadrupolar Capillary Information into Saddle- Shaped Objects for Self-Assembly
<ul> <li>Data and STL files supporting the article entitled: Encoding Quadrupolar Capillary Information into Saddle-Shaped Objects for Self-Assembly</li> <li>Text files for Figures 3 and 5 are the raw positions and orientations of the particles extracted frame by frame from experimental videos. </li> <li>Text files for Figure 4 are the liquid elevation around objects.</li> <li>Figure_roughness.pdf shows zoomed-in pictures of our typical object, focusing on edge roughness for the readers to evaluate the edge roughness.</li> </ul>
The source code for a new capillary and adsorption‒force model predicting hydraulic conductivity of soil during freeze‒thaw processes
<p>The source code is related to "A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil during Freeze‒thaw Processes" (Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang)</p>
FIGURE 2. Size comparisons. Praxelis capillaris A. flower. B. style branches. C. fruit. P in A new species of the Cerrado in Brazil
FIGURE 2. Size comparisons. Praxelis capillaris A. flower. B. style branches. C. fruit. P. macrocarpa sp. nov. D. flower. E. style branches. F. fruit.
FIGURES 59–61. Divergita capillaris from Grunow 839. 59 in Systematics of araphid diatoms with asymmetric rimoportulae or densely packed virgae, with particular attention to Hyalosynedra (Ulnariaceae, Bacillariophyta)
FIGURES 59–61. Divergita capillaris from Grunow 839. 59. Interior view of broken strongly curved valve. 60. Detail of interior apex from same valve as 59. Note obvious expansion of terminus into a capitate or subcaptitate morphology. 61. Exterior detail of apex showing barely perceptibly sunken pore field and decussating areolar pattern. This specimen had a weakly expanded apex.
FIGURES 54–58. Divergita capillaris from Grunow 839. 54 in Systematics of araphid diatoms with asymmetric rimoportulae or densely packed virgae, with particular attention to Hyalosynedra (Ulnariaceae, Bacillariophyta)
FIGURES 54–58. Divergita capillaris from Grunow 839. 54. LM of whole strongly curved valve from mica. 55. LM of whole strongly curved valve from Naphrax preparation. 56. SEM of broken weakly curved valve (interior view). 57. SEM detail of interior of apex of valve of 56. 58. SEM detail of central area, internal view, of valve of 56.
Pulmonary Capillary Perpetual Switching Demonstration
<p>Videos demonstrating pulmonary capillary flow switching.</p>
Micro computed tomography images of capillary actions in natural sand
<p>The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials. To study this, X-ray micro-computed tomography tests were performed on two types of spherical glass beads (i.e. smooth and rough) and two different sands (i.e. natural and roughened). Each sample was subjected to either drainage or soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were taken at different saturation states ranging from fully brine saturated to air dry conditions. </p>
Micro computed tomography images of capillary actions in rough glass beads
<p>The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials. To study this, X-ray micro-computed tomography tests were performed on two types of spherical glass beads (i.e. smooth and rough) and two different sands (i.e. natural and roughened). Each sample was subjected to either drainage or soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were taken at different saturation states ranging from fully brine saturated to air dry conditions. </p>
Micro computed tomography images of capillary actions in smooth glass beads
<p>The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials. To study this, X-ray micro-computed tomography tests were performed on two types of spherical glass beads (i.e. smooth and rough) and two different sands (i.e. natural and roughened). Each sample was subjected to either drainage or soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were taken at different saturation states ranging from fully brine saturated to air dry conditions. </p>
Micro computed tomography images of capillary actions in rough sand
<p>The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials. To study this, X-ray micro-computed tomography tests were performed on two types of spherical glass beads (i.e. smooth and rough) and two different sands (i.e. natural and roughened). Each sample was subjected to either drainage or soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were taken at different saturation states ranging from fully brine saturated to air dry conditions. </p>
Effects of Change in Blood Pressure on Retinal Capillary Rarefaction in Patients With Arterial Hypertension
ClinicalTrials.gov study NCT06098300. IPD Sharing: Not stated. Countries: 1. Publications: 31.
Heel Warming Before Capillary Blood Sampling
ClinicalTrials.gov study NCT04995393. IPD Sharing: NO. Countries: 1. Publications: 10.
Capillary Refill Index with Rewarming
ClinicalTrials.gov study NCT04366310. IPD Sharing: NO. Countries: 1. Publications: 11.
Usefulness of Capillary Refill Time and Skin Mottling Score to Predict Intensive Care Unit Admission
ClinicalTrials.gov study NCT03831022. IPD Sharing: UNDECIDED. Countries: 1. Publications: 9.
Comparison of Three Lancing Devices Regarding Capillary Blood Volume and Lancing Pain Intensity.
ClinicalTrials.gov study NCT03479619. IPD Sharing: NO. Countries: 1. Publications: 1.
Dynamic Arterial Elastance: an Indirect Marker of the Critical Capillary Pressure at the Microcirculatory Level
ClinicalTrials.gov study NCT03478709. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Cephalic Phase Insulin Secretion and Capillary Recruitment in Healthy Men
ClinicalTrials.gov study NCT01145027. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Lactate Use as Triage Tool in Sepsis : Veinous, Capillary or Arterial?
ClinicalTrials.gov study NCT01964690. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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OpenNeuro
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