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1,104 results for “blood flow”
The Impact of Blood Flow Restriction (BFR) on Exercise and Hemodynamic Responses
ClinicalTrials.gov study NCT03540147. IPD Sharing: YES. Countries: 1. Publications: 7.
Blood Flow Restriction Training For The Treatment Of Lateral Epicondylopathy
ClinicalTrials.gov study NCT07172568. IPD Sharing: NO. Countries: 1. Publications: 1.
Multi-Center Evaluation of Feasibility of SPECT Measurement of Myocardial Blood Flow and Reserve
ClinicalTrials.gov study NCT03427749. IPD Sharing: NO. Countries: 6. Publications: 1.
Blood Flow and Vascular Function in Cystic Fibrosis
ClinicalTrials.gov study NCT02057458. IPD Sharing: YES. Countries: 1. Publications: 1.
Blood Flow Restriction Training for The Shoulder
ClinicalTrials.gov study NCT04540367. IPD Sharing: NO. Countries: 1. Publications: 33.
Blood Flow Index as an Indicator of Successful Peripheral Nerve Block
ClinicalTrials.gov study NCT03169517. IPD Sharing: NO. Countries: 1. Publications: 1.
Effect of Blood Flow Restriction Resistance Exercises in COPDAE In-patient Rehabilitation
ClinicalTrials.gov study NCT04448236. IPD Sharing: NO. Countries: 1. Publications: 19.
The Efficacy of Low-load Blood Flow Restricted Resistance Before TKR
ClinicalTrials.gov study NCT04081493. IPD Sharing: YES. Countries: 1. Publications: 3.
Anemia Study in Chronic Kidney Disease (CKD) : Erythropoiesis Via a Novel Prolyl Hydroxylase Inhibitor (PHI) Daprodustat -Forearm Blood Flow (ASCEND-FBF)
ClinicalTrials.gov study NCT03446612. IPD Sharing: YES. Countries: 1. Publications: 1.
Exploration of Blood Flow Regulation to Bone in Humans
ClinicalTrials.gov study NCT04083794. IPD Sharing: NO. Countries: 1. Publications: 12.
Effect of C21 on Forearm Blood Flow
ClinicalTrials.gov study NCT05277922. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Neuronal migration depends on blood flow in the adult mammalian brain
Open the record for dataset details and reuse information.
Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow
<p>This repository contains the the simulation data, preprocessed in vivo data, and analysis code used in the NeuroImage article titled 'Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow' (<a href="https://doi.org/10.1016/j.neuroimage.2020.117246">https://doi.org/10.1016/j.neuroimage.2020.117246</a>). Please cite this article if you use this code or data in your work.</p>
Data from: Plane wave Doppler determination of blood flow in retinopathy of prematurity
<p>Retinopathy of prematurity (ROP) is a disorder affecting low birthweight, preterm neonates. In the preterm eye, the retina is not fully developed and neovascularization may occur at the margin between the developed vascular retina and undeveloped avascular retina. Without timely treatment by laser or intravitreal anti-vascular endothelial growth factor (VEGF) therapy, this can lead to tractional retinal detachment and blindness. Visualization of the retina in regular examinations by indirect ophthalmoscopy is hence the current standard of care, but the exams are stressful and interpretation of images is subjective.</p> <p>The upregulation of VEGF in ROP would suggest an increase in ocular blood flow. In this report, we evaluate the potential of ultrafast plane-wave Doppler ultrasound (PWU) to detect increased flow velocities in the orbital vessels supplying the eye in a gentle exam with objective findings.</p> <p>We imaged both eyes of 50 low-birthweight preterm neonates using 18 MHz PWU. Flow velocity in the central retinal artery (CRA) and vein (CRV), and the short posterior ciliary arteries were determined and values at each ROP Stage compared.</p> <p>We found significantly increased velocities in the CRA and CRV in Stage 3 ROP eyes, where intervention would be considered. We compared multivariate models for identifying Stage 3 eyes comprised solely of clinical factors, solely of Doppler parameters, and clinical plus Doppler parameters. The respective models provided areas under their respective ROC curves of 0.760, 0.812, and 0.904. </p> <p>PWU Doppler represents a gentle, objective means for identifying neonates at risk for ROP that could complement ophthalmoscopy.</p>
Modulation of Arterial Intima Stiffness by Disturbed Blood Flow
<p>Atomic Force Microscopy (AFM) measurements of arterial stiffness (carotids) in mice. </p>
Blood Flow in PH
<p>Data Set</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>
Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression
Open the record for dataset details and reuse information.
Our simulated cerebral blood flow changed from pretreatment to posttreatment status between rehabilitation (see video 1, supplemental data) and ILIB groups (see video 2, supplemental data).
<p>Our simulated cerebral blood flow changed from pretreatment to posttreatment status between rehabilitation (see video 1, supplemental data) and ILIB groups (see video 2, supplemental data).</p> <p>Video S1 demonstrates that the cerebral blood flow changed from pretreatment to posttreatment status in one participant of rehabilitation.</p> <p>Video S2 demonstrates that the cerebral blood flow changed from pretreatment to posttreatment status in one participant of ILIB.</p>
Aberrations in Carnitine Homeostasis in Congenital Heart Disease With Increased Pulmonary Blood Flow
ClinicalTrials.gov study NCT01825369. IPD Sharing: Not stated. Countries: 1. Publications: 15.
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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)
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.