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5,371 results for “Flow”
RNA sequencing of CD8 T cells flow sorted from post-stroke brain
GEO Series GSE155480. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Directional flow-mediated mesenchymal force drives epithelial tube constriction and splitting
GEO Series GSE307539. Gallus gallus. 2 samples. Type: Expression profiling by high throughput sequencing.
Molecular pathways of early CD105-positive erythroid cells as compared to CD34-positive common precursor cells by high-sensitive flow cytometric cell sorting and gene expression profiling
GEO Series GSE40893. Homo sapiens. 24 samples. Type: Expression profiling by array.
The CUT&Tag assay was conducted on protoplasts that had been transiently transformed with OsDOF3-GFP and then sorted using a flow cytometer.
GEO Series GSE310632. Oryza sativa. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Large-eddy simulation of turbulent oscillatory flow over three-dimensional transient vortex ripple geometries in quasi-equilibrium
<p>dataset for figures of 'Large-eddy simulation of turbulent oscillatory flow over three-dimensional transient vortex ripple geometries in quasi-equilibrium'</p>
Dataset related to article "Evaluation of Semen Self-Sampling Yield Predictors and CTC Isolation by Multi-Color Flow Cytometry for Liquid Biopsy of Localized Prostate Cancer"
<p><strong>Abstract</strong></p><p>Liquid biopsy (LB) for prostate cancer (PCa) detection could represent an alternative to biopsy. Seminal fluid (SF) is a source of PCa-specific biomarkers, as 40% of ejaculate derives from the prostate. We tested the feasibility of an SF-based LB by evaluating the yield of semen self-sampling in a cohort of >750 patients with clinically localized PCa. The overall SF collection yield was 18.2% (39% when considering only compliant patients), with about a half of the patients (53.15%) not consenting to SF donation. Independent favorable predictors for SF collection were younger age and lower prostate volume. We implemented a protocol to enrich prostate-derived cells by multi-color flow cytometry and applied it on SF and urine samples from 100 patients. The number of prostate-enriched cells (SYTO-16+ PSMA+ CD45-) was variable, with higher numbers of cells isolated from SF than urine (<i>p</i> value < 0.001). Putative cancer cells (EpCAMhigh) were 2% of isolated cells in both specimens. The fraction of EpCAMhigh cells over prostate-enriched cells (PSMA+) significantly correlated with patient age in both semen and urine, but not with other clinical parameters, such as Gleason Score, ISUP, or TNM stage. Hence, enumeration of prostate-derived cells is not sufficient to guide PCa diagnosis; additional molecular analyses to detect patient-specific cancer lesions will be needed</p>
The Macular Choriocapillaris Flow in Glaucoma and Within-Day Fluctuations: An Optical Coherence Tomography Angiography Study
<p>Raw data of the study, can be available upon request</p>
Bailout From Sinus Jailing: In-Series TAVR-in-TAVR to Avoid Coronary Flow Obstruction
<p>Video from Casenghi M, Oliva OA, Squillace M, Bellamoli M, Poletti E, Popolo Rubbio A, Testa L, Bedogni F, De Marco F. Bailout From Sinus Jailing: In-Series TAVR-in-TAVR to Avoid Coronary Flow Obstruction. JACC Case Rep. 2021 Apr 21;3(4):678-681. doi: 10.1016/j.jaccas.2021.02.022. PMID: 34317602; PMCID: PMC8302790.</p> <p>Abstract</p> <p>Redo transcatheter aortic valve replacement (TAVR) may pose the risk of coronary flow obstruction. We report 2 cases of severe TAVR regurgitation due to different physiopathological mechanisms in which TAVR-in-TAVR could be at high risk for sinus sequestration. Both cases were successfully treated by in-series implantation of a second transcatheter heart valve, thus avoiding sinus sequestration. (<strong>Level of Difficulty: Intermediate.</strong>).</p>
4D flow evaluation of blood non-Newtonian behavior in left ventricle flow analysis
<p>Dataset from Riva A, Sturla F, Caimi A, Pica S, Giese D, Milani P, Palladini G, Lombardi M, Redaelli A, Votta E. 4D flow evaluation of blood non-Newtonian behavior in left ventricle flow analysis. J Biomech. 2021 Apr 15;119:110308. doi: 10.1016/j.jbiomech.2021.110308. Epub 2021 Feb 8. PMID: 33631666.</p> <p>Abstract</p> <p>Blood is generally modeled as a Newtonian fluid, assuming a standard and constant viscosity; however, this assumption may not hold for the highly pulsatile and recirculating intracavitary flow in the left ventricle (LV), hampering the quantification of fluid dynamic indices of potential clinical relevance. Herein, we investigated the effect of three viscosity models on the patient-specific quantification of LV blood energetics, namely on viscous energy loss (EL), from 4D Flow magnetic resonance imaging: I) Newtonian with standard viscosity (3.7 cP), II) Newtonian with subject-specific hematocrit-dependent viscosity, III) non-Newtonian accounting for the effect of hematocrit and shear rate. Analyses were performed on 5 controls and 5 patients with cardiac light-chain amyloidosis. In Model II, viscosity ranged between 3.0 (-19%) and 4.3 cP (+16%), mildly deviating from the standard value. In the non-Newtonian model, this effect was emphasized: viscosity ranged from 3.2 to 6.0 cP, deviating maximally from the standard value in low shear rate (i.e., <100 s<sup>-1</sup>) regions. This effect reflected on EL quantifications: in particular, as compared to Model I, Model III yielded markedly higher EL values (up to +40%) or markedly lower (down to -21%) for subjects with hematocrit higher than 39.5% and lower than 30%, respectively. Accounting for non-Newtonian blood behavior on a patient-specific basis may enhance the accuracy of intracardiac energetics assessment by 4D Flow, which may be explored as non-invasive index to discriminate between healthy and pathologic LV.</p>
Carotid Phase-Contrast Magnetic Resonance before Treatment: 4D-Flow versus Standard 2D Imaging
<p>Secchi F, Monti CB, Capra D, Vitale R, Mazzaccaro D, Conti M, Jin N, Giese D, Nano G, Sardanelli F, Marrocco-Trischitta MM. Carotid Phase-Contrast Magnetic Resonance before Treatment: 4D-Flow versus Standard 2D Imaging. Tomography. 2021 Sep 28;7(4):513-522. doi: 10.3390/tomography7040044. PMID: 34698250; PMCID: PMC8544659.</p> <p>Abstract</p> <p>The purpose of this study was to evaluate the level of agreement between flow/velocity data obtained from 2D-phase-contrast (PC) and 4D-flow in patients scheduled for treatment of carotid artery stenosis. Image acquisition was performed using a 1.5 T scanner. We compared mean flow rates, vessel areas, and peak velocities obtained during the acquisition with both techniques in 20 consecutive patients, 15 males and 5 females aged 69 ± 5 years (mean ± standard deviation). There was a good correlation between both techniques for the CCA flow (<em>r</em> = 0.65, <em>p</em> < 0.001), whereas for the ICA flow and ECA flow the correlation was only moderate (<em>r</em> = 0.4, <em>p</em> = 0.011 and <em>r</em> = 0.45, <em>p</em> = 0.003, respectively). Correlations of peak velocities between methods were good for CCA (<em>r</em> = 0.56, <em>p</em> < 0.001) and moderate for ECA (<em>r</em> = 0.41, <em>p</em> = 0.008). There was no correlation for ICA (<em>r</em> = 0.04, <em>p</em> = 0.805). Cross-sectional area values between methods showed no significant correlations for CCA (<em>r</em> = 0.18, <em>p</em> = 0.269), ICA (<em>r</em> = 0.1, <em>p</em> = 0.543), and ECA (<em>r</em> = 0.05, <em>p</em> = 0.767). Conclusion: the 4D-flow imaging provided a good correlation of CCA and a moderate correlation of ICA flow rates against 2D-PC, underestimating peak velocities and overestimating cross-sectional areas in all carotid segments.</p>
Data for the manuscript "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning"
<p>The excel file contains hydrological and sediment data. Also included are dimensional analysis data in our dataset.<br> The rar file contains the codes and data for SVM classification work.</p>
Redox flow batteries for renewable energy storage (Video)
<p>Lecture: <strong>Redox flow batteries for renewable energy storage</strong></p> <p><em>International Summer School on Energy Storage Systems: New Developments and Directions</em></p> <p>Zaragoza, 18-20 July 2022</p> <p><a href="https://www.youtube.com/watch?v=gzY5RrliPLY">https://www.youtube.com/watch?v=gzY5RrliPLY</a></p>
Natural turbulent (Re_tau=300) channel flow DNS simulation.
<p>Natural turbulent (Re_tau=300) channel flow DNS simulation.</p>
Data for "Uncovering the global plastics flows, stock and end-of-life fates for a pragmatic resolution to end plastic pollution"
Open the record for dataset details and reuse information.
[under peer review] Dataset - Permeability and viscoelastic fracture of a model tumor under interstitial flow
<p>This includes all the experimental data which are presented in the paper titled "Permeability and viscoelastic fracture of a model tumor under interstitial flow" by Quang D. Tran, Marcos and David Gonzalez-Rodriguez.</p> <p>In each data folder, we have attached a Readme file to instruct readers how to analyze or compute our data.</p> <p>This dataset is not fully open at the moment as the paper is currently under review process.</p>
Supplementary material from "Seasonality of salmonid parasites from flow-through aquaculture in northern Germany: Emphasis on pathogenicity of Diplostomum spp. metacercaria "
<p>Supplementary material from "Seasonality of salmonid parasites from flow-through aquaculture in northern Germany: Emphasis on pathogenicity of Diplostomum spp. metacercaria "</p>
Dataset related to article: "Smart Flow for the evaluation of the hemodialysis arteriovenous fistula"
<p>We provide the raw data used for the following article:</p> <ul> <li>Colucci M, Torreggiani M, Bernardi I, Stangalino S, Catucci D, Esposito V, Sileno G, Esposito C.<br> <em>Smart Flow for the evaluation of the hemodialysis arteriovenous fistula</em>. "J Vasc Access". 2020 Sep;21(5):652-657.<br> doi: 10.1177/1129729819897171. Epub 2020 Jan 2. PMID: 31894718.</li> </ul> <p><br> <strong>Background: </strong>Smart Flow is an innovative tool available on the Carestream Touch Prime Ultrasound machines, which provides automated blood flow measurement and shows the vectors that form the blood flow in the vessel. We compared the use of Smart Flow with traditional Duplex Doppler Ultrasound to evaluate blood flow of arteriovenous fistulas in prevalent hemodialysis patients. <strong>Methods: </strong>A total of 31 chronic patients on hemodialysis were enrolled. Blood flow was measured on the brachial artery with Smart Flow and duplex Doppler ultrasound. In a subset of 26 patients, a video of the juxta-anastomotic efferent vein was recorded and analyzed to calculate an index of flow turbulence.<br> <strong>Results:</strong> We enrolled 21 males and 10 females aged 68.52±11.64 years at the time of evaluation with an average arteriovenous fistulas vintage of 50.23±47.42 months and followed them up for 18.03±5.18 months. Smart Flow and Duplex Doppler Ultrasound blood flow measurements positively correlated (p<0.0001) in the same patient but Smart Flow gave higher blood flow values (995.0 vs 730.3mL/min, p<0.0001), and the Duplex Doppler Ultrasound blood flow standard deviation was similar to Smart Flow (125.4 vs 114.4mL/min, p<0.0001). The time needed to evaluate arteriovenous fistulas with Smart Flow was significantly shorter than Duplex Doppler Ultrasound (67.58±19.89 vs 146.3±26.35 s, p<0.0001). No correlation was found between blood flow turbulence and the subsequent access failure.<br> <strong>Conclusion:</strong> Smart Flow is reliable, reproducible, and faster than traditional duplex ultrasound. However, the additional information given by the Smart Flow technique does not seem to add any further benefits in terms of prediction of the access failure</p>
Agile in Academia Presents Finding your Flow: What's the Locus of your Focus? [Video]
<p>Workshop recorded on Friday, October 28th, 2022</p> <p> </p> <p><strong>Agile in Academia presenters: </strong></p> <p><strong>Doug Salcedo, MBA</strong>, Enterprise Agile DevOps Coach, Technology Consultant, SAFe Program Consultant SPC5, BSIT (35+ years of Project Management)</p> <p><strong>Mary Salcedo, Ph.D.,</strong> USDA Postdoctoral Fellow, Cornell University (10 years in academia)</p> <p>This video was recorded during a sponsored workshop from the Society of Integrative and Comparative Biology workshop to provide academics with professional development. </p> <p>Workshop focus:</p> <p><strong>Finding your flow: What’s the locus of your focus?</strong></p> <p>Often, we encounter periods of time where work seems stagnant. Things aren’t getting done, but deadlines are looming. How do we get ourselves out of the rut? How do you encourage your team, when things are piling up, but production is slowing?</p> <p>After the first Agile in Academia workshop in June, and follow up one-on-one consults, Doug and I saw a need for a flow workshop. We created a shorter “down to brass tacks” workshop to dive into skills and strategies. In this two hour workshop we’ll go over four topics: Defining Your Value Stream, What’s Your Backlog?, Kanban and Managing Tasks, and Standup Meetings and Review Cycles. You will come away with how to establish your own personal work flow, but also how to strategize if you are working or managing groups. Overall attendees will have a better understanding of their value stream what they themselves produce and its value, a working Kanban which will be workshopped in small breakout rooms, and management ideas on how to improve their personal or lab work flow.</p> <p> “Agile for Academics” is an online, hands-on workshop that focuses on bridging the knowledge gap on how to apply agile and related methodologies to managing academics projects and processes. “Agile” is a values and principles-based project management methodology, used widely in the technology industry to effectively manage work in a “lean” and sustainable fashion. Lean a value-driven process methodology focuses on providing the best value in the shortest sustainable lead time. Throughout the workshop we will talk about how to adopting and apply a “Lean-Agile Mindset” to your corner of Academia.</p>
Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning"
<p>Du J. et al., (2022). Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning", Water Resources Research</p> <p>Table S1: Hydrologic Paramteres and Dimensionless Numbers of Debris Flows</p> <p>Table S2: Hydrologic Paramteres and Dimensionless Numbers of Hyperconcentrated Flows</p> <p>Table S3: Hydrologic Paramteres and Dimensionless Numbers of Stream Flows</p> <p>Table S4: Hydrologic Paramteres and Dimensionless Numbers of Lahars</p>
Dataset related to the article "Prediction of myocardial blood flow under stress conditions by means of a computational model"
<p>This record contains raw data related to the article “Prediction of myocardial blood flow under stress conditions by means<br> of a computational model”</p> <p><strong>Purpose. </strong>Quantification of myocardial blood flow (MBF) and functional assessment of coronary artery disease (CAD) can be achieved through stress myocardial computed tomography perfusion (stress-CTP). This requires an additional scan after the resting coronary computed tomography angiography (cCTA) and administration of an intravenous stressor. This complex protocol has limited reproducibility and non-negligible side effects for the patient. We aim to mitigate these drawbacks by proposing a computational model able to reproduce MBF maps.</p> <p><strong>Methods. </strong>A computational perfusion model was used to reproduce MBF maps. The model parameters were estimated by using information from cCTA and MBF measured from stress-CTP (MBF<sub>CTP</sub>) maps. The relative error between the computational MBF under stress conditions (MBF<sub>COMP</sub>) and MBF<sub>CTP</sub> was evaluated to assess the accuracy of the proposed computational model.</p> <p><strong>Results.</strong> Applying our method to 9 patients (4 control subjects without ischemica vs 5 patients with myocardial ischemia), we found an excellent agreement between the values of MBF<sub>COMP</sub> and MBF<sub>CTP</sub>. In all patients, the relative error was below 8% over all the myocardium, with an average-in-space value below 4%.</p> <p><strong>Conclusion. </strong>The results of this pilot work demonstrate the accuracy and reliability of the proposed computational model in reproducing MBF under stress conditions. This consistency test is a preliminary step in the framework of a more ambitious project which is currently under investigation, i.e. the construction of a computational tool able to predict MBF avoiding the stress protocol and potential side effects while reducing radiation exposure.</p>
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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.