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3,702
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Dataset results
3,702 results for “healthy adults”
A Study to Evaluate the Safety, Tolerability, Pharmacokinetics (PK) and Pharmacodynamics (PD) of TAK-925 Study in Sleep-Deprived Healthy Adults
ClinicalTrials.gov study NCT03522506. IPD Sharing: YES. Countries: 1. Publications: 1.
COVID-19 Study to Assess Immunogenicity, Safety, and Tolerability of Moderna mRNA-1273 Vaccine Administered With Casirivimab+Imdevimab in Healthy Adult Volunteers
ClinicalTrials.gov study NCT04852978. IPD Sharing: YES. Countries: 1. Publications: 1.
A Trial to Evaluate the Effect of the Proton Pump Inhibitor Esomeprazole on the Single-dose Pharmacokinetics (PK) of Oral TAK-906 in Healthy Adult Participants
ClinicalTrials.gov study NCT03849690. IPD Sharing: YES. Countries: 1. Publications: 1.
A Study of TAK-019 in Healthy Japanese Adults (COVID-19)
ClinicalTrials.gov study NCT04712110. IPD Sharing: YES. Countries: 1. Publications: 1.
Maribavir Food-Effect Study in Healthy Adults Participants
ClinicalTrials.gov study NCT05382104. IPD Sharing: YES. Countries: 1. Publications: 0.
A Study of Maribavir Pediatric Formulation in Healthy Adult Participants
ClinicalTrials.gov study NCT05918822. IPD Sharing: YES. Countries: 1. Publications: 0.
Pharmacodynamics parameters underlying the manuscript: The effect of morning versus evening administration of empagliflozin on its pharmacokinetics and pharmacodynamics characteristics in healthy adults: a two-way crossover, non-randomised trial
<p><b>Background</b>: Empagliflozin is an SGLT2 inhibitor approved for use in patients with Diabetes Mellitus type 2 (DMT2) with- or without other cardiovascular disease. Empagliflozin is taken once daily without rationale on the optimal timing for administration. This study aimed<b> </b>to determine the chronopharmacological effects of morning vs evening administration of empagliflozin 10 mg in Healthy Egyptian adults, by investigating the pharmacokinetics and pharmacodynamics parameters of empagliflozin depending on the intake time. </p> <p><b>Methods: </b>An open label, sequential, two‐way crossover trial comprised two periods with a washout period of 7 days. Pharmacokinetics parameters (t<sub>max</sub> (h), C<sub>max</sub> (ng/ml), AUC <sub>0-t</sub> (ng.h/ml)) as primary endpoints, and (AUC <sub>0 to ∞</sub>(ng.h/ml)) as secondary endpoint were assessed. Method validation was done prior to injection in LC/MS/MS and samples were processed by Liquid-Liquid extraction. The pharmacodynamic profile (UGE <sub>0-24</sub>) was determined after method validation (glucose hexokinase method).</p> <p><b>Results: </b>T<sub>max</sub> increased by (35%) in the evening phase compared to the morning phase, while C<sub>max</sub> decreased by (-6.5%)in the evening dose compared to the morning dose. Besides, AUC<sub>0 to ∞</sub> increased in the evening phase by (8.25%) compared to the morning phase. The mean cumulative amount of glucose excreted; UGE (<sub>0-24</sub>) increased by (43%) in the evening dose compared to the morning dose</p> <p><strong>Conclusion: </strong>Despite there was a significant difference between morning and evening doses, it didn't reach the significant level, thus, it can be concluded that there is no difference between the morning and evening doses.</p>
Data and code from: Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing
<p>This repository contains the Julia code, Jupyter notebook, and data used in the study “Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing” by MacDonald et al.</p> <p><strong>Instructions</strong></p> <p>To run this analysis on your computer, both Julia and Jupyter Notebook must be installed. A version of Julia appropriate for your OS can be downloaded from the <a href="https://julialang.org/downloads/">Julia website</a>, and Jupyter can be installed from within Julia (in the REPL) with</p> <pre><code>] add IJulia</code></pre> <p>Alternate instructions for installing Jupyter can be found on the <a href="https://github.com/JuliaLang/IJulia.jl">IJulia github</a> or the <a href="https://jupyter.org/install">Jupyter homepage</a> (not recommended).</p> <p>From within the main repository directory, start Julia and then start Jupyter in the Julia REPL</p> <pre><code>using IJulia notebook(;dir=pwd())</code></pre> <p>or if using a system Jupyter installation, start Jupyter from your favorite available shell (e.g. Powershell on Windows, bash on any *nix variant, etc.). In Jupyter, open the <code>notebooks/analysis.ipynb</code> notebook. Running all cells will reproduce the results for this paper.</p> <p><strong>Description of data</strong></p> <p>The <code>data</code> directory contains all the data used in the production of the results which were statistically tested.</p> <p>Each <code>.mat</code> file contains events and data generated in Visual3D:</p> <ul> <li>Events <ul> <li><code>LTO</code>/<code>RTO</code> (Left/right toe-off)</li> <li><code>LHS</code>/<code>RHS</code> (Left/right heel-strike)</li> <li><code>HIST</code>/<code>HIEN</code> (Hilly start/end)</li> <li><code>ROST</code>/<code>ROEN</code> (Rocky start/end)</li> <li><code>MLST</code>/<code>MLEN</code> (ML translation start/end)</li> </ul> </li> <li>Data <ul> <li><code>LFootPos</code>/<code>RFootPos</code> (Left/right foot COM position)</li> <li><code>TrunkPos/TrunkVel</code>/<code>TrunkAcc</code> (Trunk COM position, velocity, and acceleration)</li> <li><code>HeadPos/HeadVel</code>/<code>HeadAcc</code> (Head COM position, velocity, and acceleration)</li> <li><code>COG</code> (Whole-body COM/COG)</li> </ul> </li> </ul> <p>The <code>.csv</code> files contain system state of the CAREN system produced by D-Flow software, which includes various system and software settings, most pertinent of which is the treadmill speed.</p> <p>The <code>.c3d</code> files contain the raw motion capture data from Vicon Nexus.</p> <ul> </ul> <p>The results of the <code>notebooks/analysis.ipynb</code> notebook are found in the <code>results</code> folder. Please see the paper for a list of the dependent variables and statistical analyses.</p>
Muscle activity, ground reaction forces and pointing performance during postural control tasks in healthy adults
<p>To investigate the muscle coordination during postural control, we recorded muscle activity and postural dynamics in healthy human adults. Fourteen participants performed postural tasks in which postural stability and pointing behaviour was varied. The data set contains electromyography of 36 muscles distributed across the body and ground reaction forces recorded during postural control tasks. A full factorial design was used. Stability was either not challenged or challenged in the anterior-posterior or medial-lateral direction. In addition, participants were asked to either relax their arms or to perform an unimanual or a bimanual pointing task. In the pointing task, participants held a laser pointer and pointed it on a target in front of them. Pointing performance was recorded using a video recording of the laser beam on the target area.</p> <p>InformationData.pdf – Description of data acquisition and file structure<br> EMG.zip – EMG data<br> FP.zip – Force plate data<br> Video.zip – Video feed</p>
Pulse Wave Database (PWDB): A database of arterial pulse waves representative of healthy adults
<p><strong>Overview</strong></p> <p>This database of simulated arterial pulse waves is designed to be representative of a sample of pulse waves measured from healthy adults. It contains pulse waves for 4,374 virtual subjects, aged from 25-75 years old (in 10 year increments). The database contains a baseline set of pulse waves for each of the six age groups, created using cardiovascular properties (such as heart rate and arterial stiffness) which are representative of healthy subjects at each age group. It also contains 728 further virtual subjects at each age group, in which each of the cardiovascular properties are varied within normal ranges. This allows for extensive <em>in silico</em> analyses of haemodynamics and the performance of pulse wave analysis algorithms.</p> <p><strong>Data Description</strong></p> <p>The database contains the following waves:</p> <ul> <li>arterial flow velocity (U),</li> <li>luminal area (A),</li> <li>pressure (P), and</li> <li>photoplethysmogram (PPG).</li> </ul> <p>These pulse waves are provided at a range of measurement sites, including:</p> <ul> <li>aorta (ascending and descending)</li> <li>carotid artery</li> <li>brachial artery</li> <li>radial artery</li> <li>finger</li> <li>femoral artery</li> </ul> <p>The data are available in three formats: Matlab, CSV and WaveForm Database (WFDB) format. Further details of the formatting and contents of each file are available at: <a href="https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database">https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database</a></p> <p><strong>Accompanying Publication</strong></p> <p>The database is described in the following publication:</p> <p><a href="https://peterhcharlton.github.io/pwdb/pwdb_article.html">Charlton P.H., Mariscal Harana, J., Vennin, S., Li, Y., Chowienczyk, P. & Alastruey, J., “Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices,”</a> [under review]</p> <p>Please cite this publication when using the database.</p> <p><strong>Further Information</strong></p> <p>Further information on the Pulse Wave Database project can be found at: <a href="https://peterhcharlton.github.io/pwdb/"><em>https://peterhcharlton.github.io/pwdb/</em></a></p> <p><strong>Version History</strong></p> <p> </p> <p><strong>Version 0.1.0 : provided for peer review of "Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices"</strong></p> <p><strong>Version 0.2.0 : provided for peer review of "Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices"</strong></p>
Peak power and body mass as indices of bone loading in a healthy adult population
<p><strong>Objective</strong>: The purpose of this study was to examine whether a common, non-invasive, muscular fitness field test was a better predictor of bone strength compared to body mass. </p> <p><strong>Methods</strong>: Hierarchical multiple regression analyses were used to determine the amount of variance that peak power explained for bone strength of the tibia compared to body mass. Peak power was estimated from maximal vertical jump height using Sayer's equation. Peripheral quantitative computed tomography scans were used to assess bone strength measures. </p> <p><strong>Results</strong>: Peak power (ꞵ=0.541, p<0.001) contributed more to the unique variance in bone strength index for compression compared to body mass (ꞵ=-0.102, p=0.332). For polar strength strain index, the beta coefficient for body mass remained significant (ꞵ=0.257, p<0.006), however, peak power's contribution was similar (ꞵ=0.213, p= 0.051).</p> <p><strong>Conclusion</strong>: Compared to body mass, peak power was a better predictor for trabecular bone strength but similar to body mass for cortical bone strength. These data provide additional support for the development of a vertical jump test as a simple, objective, valid and reliable measure to monitor bone strength among youth and adult populations.</p>
Dataset for "Excellent test-retest reliability of the six-minute walking distance measured by FeetMe insoles during tests conducted with a one-week interval by completely unassisted healthy adults in their homes."
<p>This is the dataset used in the scientific article "Excellent test-retest reliability of the six-minute walking distance measured by FeetMe insoles during tests conducted with a one-week interval by completely unassisted healthy adults in their homes." Participants (n=21) performed two 6MWTs at home while wearing the FeetMe<sup> </sup>insoles, and two 6MWTs at hospital while wearing FeetMe<sup> </sup>insoles and being assessed by a rater. All assessments were performed with a one-week interval between tests, no assistance was provided to the participants at home. Each column represents the 6MWD for each participant at one of the visits and using one of the measurement methods. Columns' headers provide clear description of the corresponding condition.</p>
Phase I Study to Evaluate a Human Monoclonal Antibody (MAb) 10E8VLS Administered Alone or Concurrently With MAb VRC07-523LS Via Subcutaneous Injection in Healthy Adults
ClinicalTrials.gov study NCT03565315. IPD Sharing: NO. Countries: 1. Publications: 3.
A Trial Investigating the Safety and Effects of Four BNT162 Vaccines Against COVID-19 in Healthy and Immunocompromised Adults
ClinicalTrials.gov study NCT04380701. IPD Sharing: NO. Countries: 1. Publications: 10.
Oral Nitrite and Nitrate in Healthy Normal Volunteer Adults
ClinicalTrials.gov study NCT01681836. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Induction of Dreaming With EEG and Anesthesia in Healthy Adults
ClinicalTrials.gov study NCT07198711. IPD Sharing: YES. Countries: 1. Publications: 2.
Evaluating the Safety and Immunogenicity of Stabilized CH505 TF chTrimer in Healthy, HIV-uninfected Adult Participants.
ClinicalTrials.gov study NCT04915768. IPD Sharing: NO. Countries: 1. Publications: 0.
Ascending Single Doses of Erenumab (AMG 334) in Healthy Adults and Migraine Patients
ClinicalTrials.gov study NCT01688739. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Trial to Evaluate L9LS in Healthy Adults
ClinicalTrials.gov study NCT05019729. IPD Sharing: NO. Countries: 1. Publications: 5.
Food Effect on PK of DW-1021 (Pelubiprofen 45 mg / Tramadol 45.9 mg) in Healthy Adults
ClinicalTrials.gov study NCT07060209. IPD Sharing: NO. Countries: 1. Publications: 2.
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.