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298
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ShareScore release 0.9.0
Dataset results
298 results for “Multi-modal”
High Intensity Multi-Modal Exercise Training in Postmenopausal Women
ClinicalTrials.gov study NCT04653350. IPD Sharing: NO. Countries: 1. Publications: 7.
Safety and Efficacy of Low-Flow ECMO in a Multi-modal Cohort of Adults in Respiratory Failure
ClinicalTrials.gov study NCT06938217. IPD Sharing: NO. Countries: 1. Publications: 22.
Multi-modality Imaging in Peritoneal Carcinomatosis of Colorectal Origin
ClinicalTrials.gov study NCT03699332. IPD Sharing: NO. Countries: 1. Publications: 1.
Multi-modality MRI Study on Prediction for Mild Cognitive Impairment Conversion
ClinicalTrials.gov study NCT02353884. IPD Sharing: Not stated. Countries: 1. Publications: 2.
The Role of Multi-Modality Therapy for the Treatment of High-Grade Soft Tissue Sarcomas of the Extremities
ClinicalTrials.gov study NCT00001188. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Systematically Assessing Effects of Colored Light on Humans With a Multi-modal Approach (Substudy 3 of 7)
ClinicalTrials.gov study NCT02882542. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Effectiveness of a Community-based Multi-modal Tai Chi Rehabilitation Program for Patients After Total Knee Arthroplasty
ClinicalTrials.gov study NCT03565380. IPD Sharing: NO. Countries: 1. Publications: 1.
Multi-modality Imaging & Immunophenotyping of COVID-19 Related Myocardial Injury
ClinicalTrials.gov study NCT04412369. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Longitudinal (Weekly) Follow-up of Active Plaques in Multiple Sclerosis With 3 Teslas Multi-modality MRI Using Diffusion, Perfusion, Venography and Proton Spectroscopy
ClinicalTrials.gov study NCT00861172. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Multi-modality Imaging of Ischemia With 18F-FDG PET and CTA
ClinicalTrials.gov study NCT01520025. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Specificity of multi-modal aphid defenses against two rival parasitoids
Open the record for dataset details and reuse information.
Supporting data for: Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
Open the record for dataset details and reuse information.
Data from: Creating a multi-track classical music performance dataset for multi-modal music analysis: challenges, insights, and applications
Open the record for dataset details and reuse information.
Dataset for Event-based architecture for enabling multi-modal reasoning on loosely coupled Linked Data services
<p>Dataset with the raw UNIX timestamps for start/stop time points for each sample of each evaluated configuration as well as produced plots.</p>
Cell Volume (3D) Correlative Microscopy Facilitated by Intra-Cellular Fluorescent Nanodiamonds as Multi-Modal Probes
<p>RAW files</p>
Sex-driven modifiers of Alzheimer's risk: a multi-modality brain imaging study
<p><span><b>Objective:</b> To investigate sex differences in late-onset Alzheimer's disease (AD) risks by means of multi-modality brain biomarkers <span>[β-amyloid load via </span><sup>11</sup>C-PiB<span> PET, and neurodegeneration via </span><sup>18</sup>F-FDG <span>PET and structural MRI]</span>.</span></p> <p><span><b>Methods:</b> We examined 121 cognitively normal participants [85 women and 36 men] ages 40-65, with clinical, laboratory, neuropsychological, lifestyle exams, and MRI, FDG- and PiB-PET exams. Several clinical (e.g. age, education, APOE status, family history), medical (e.g., depression, diabetes, hyperlipidemia), hormonal (e.g. thyroid disease, menopause), and lifestyle AD risk factors (e.g., smoking, diet, exercise, intellectual activity) were assessed. Statistical parametric mapping and LASSO regressions were used to compare AD-biomarkers between men and women, and to identify the risk factors associated with sex-related differences. </span></p> <p><b><span>Results:</span></b> Groups were comparable on clinical and cognitive measures. Adjusting for each modality-specific confounders, the female group showed higher PiB <span>β-amyloid </span>deposition, lower FDG glucose metabolism, and lower MRI gray and white matter volumes compared to the male group (p<0.05, FWE-corrected for multiple comparisons). The male group did not show biomarker abnormalities compared to the female group. Results were independent of age and remained significant using age-matched groups. Second to female sex, menopausal status was the predictor most consistently and strongly associated with the observed brain biomarker differences, followed by hormone therapy, hysterectomy status, and thyroid disease.</p> <p><span><b><span>Conclusion:</span></b><span> Hormonal risk factors, in particular menopause, predict AD-endophenotype in middle-aged women. These findings suggest that the window of opportunity for AD-preventative interventions in women is early in the endocrine aging process.</span></span></p>
Integrative single-cell multi-modal analyses reveal detailed spatial cellular organization directing human heart morphogenesis
<div> <p><span>The heart, which is the first organ to develop, is highly dependent on its form to function. However, how diverse cardiac cell types spatially coordinate to create complex morphological structures critical for heart function remains to be elucidated. Here, we show that integration of single cell RNA-sequencing with high-resolution multiplexed error-robust fluorescent <em>in situ </em>hybridization (MERFISH) not only resolves the identity of cardiac cell types developing the human heart but also provides a spatial mapping of individual cells that enables illumination of their organization into cellular communities forming distinct cardiac structures. We discovered that many of these cardiac cell types further specified into subpopulations exclusive to specific communities, supporting their specialization according to cellular ecosystem and anatomic region. In particular, ventricular cardiomyocyte subpopulations displayed an unexpected complex laminar organization across the ventricular wall and formed, with other cell subpopulations, several cellular communities. Interrogating cell-cell interactions within these communities revealed signaling pathways orchestrating the spatial organization of cardiac cell subpopulations during ventricular wall morphogenesis. <em>In vivo </em>conditional genetic mouse models and in vitro human pluripotent stem cell studies confirmed an intricate multicellular PLXN-SEMA crosstalk among specific ventricular cardiomyocyte, fibroblast and endothelial cell subpopulations that directs the compaction of the ventricular wall layers. Thus, these detailed findings into the cellular social interactions and specialization of cardiac cell types constructing and remodeling the human heart offer new insights into structural heart diseases as well as engineering complex multi-cellular tissues for human heart repair.</span></p> </div>
Data set for displacement-based multi-modal formulation of Koiter's method applied to cylindrical shells
<p>These results complement the results reported in the AIAA SciTech 2022 publication "Displacement-based multi-modal formulation of Koiter's method applied to cylindrical shells", presented in the Special Session in Honor of Prof. Dr. Johann Arbocz.</p> <p>A preprint of is already available as:</p> <blockquote> <p>Castro SGP, Jansen E. Displacement-based multi-modal formulation of Koiter's method applied to cylindrical shells. EngrXiv Preprints, 2021. <a href="https://doi.org/10.31224/osf.io/92xvf">doi:10.31224/osf.io/92xvf</a>.</p> </blockquote> <p>The results are generated using the bfsccylinder module version 0.3.12, see file <a href="https://zenodo.org/record/5667978/files/bfsccylinder-0.3.12.zip">bfsccylinder-0.3.12.zip</a>, also available in PyPi (<a href="https://pypi.org/project/bfsccylinder/">https://pypi.org/project/bfsccylinder/</a>). The composites module is also needed, see file <a href="https://zenodo.org/record/5667978/files/composites-0.4.18.zip">composites-0.4.18.zip</a>, also available in PyPi (<a href="https://pypi.org/project/composites/">https://pypi.org/project/composites/</a>).</p> <p> </p> <p><strong>Main analysis scripts:</strong></p> <p><a href="https://zenodo.org/record/5667978/files/koiter_cylinder_von_Karman.py?download=1">koiter_cylinder_von_Karman.py</a> has the analysis function using Donnell-type or Von Kárman-type shell kinematics.</p> <p><a href="https://zenodo.org/record/5667978/files/koiter_cylinder_Sanders.py">koiter_cylinder_Sanders.py</a> has the analysis function using Sanders-type shell kinematics.</p> <p> </p> <p><strong>Verification case: Water's composite cylindrical shell</strong></p> <p><a href="https://zenodo.org/record/5667978/files/v00_DIANA_Waters_shell.zip">v00_DIANA_Waters_shell.zip</a> reference results obtained with a converged model using DIANA Q40L elements</p> <p><a href="https://zenodo.org/record/5667978/files/v00_Waters_composite_cylindrical_shell_sanders.py">v00_Waters_composite_cylindrical_shell_sanders.py</a> script to run the verification case</p> <p><a href="https://zenodo.org/record/5667978/files/v00_Waters_composite_cylindrical_shell_sanders.results">v00_Waters_composite_cylindrical_shell_sanders.result</a> results saved in an object file saved using Pickle, can be loaded with `pickle.load()`</p> <p><a href="https://zenodo.org/record/5667978/files/v00_Waters_composite_cylindrical_shell_sanders_b_ijkl.txt">v00_Waters_composite_cylindrical_shell_sanders_b_ijkl.txt</a> b_ijkl coefficients for this case, with 10 modes in the Koiter expansion</p> <p><a href="https://zenodo.org/record/5667978/files/v00_Waters_composite_cylindrical_shell_sanders_output.txt">v00_Waters_composite_cylindrical_shell_sanders_output.txt</a> printed output</p> <p> </p> <p> </p> <p> </p>
M3: A Multi-Image Multi-Modal Entity Alignment Dataset
<p><span>M3, an MMEA benchmark equipped with multiple images retrieved from respective search engines, which better mirrors real-life challenges. We utilize the widely used DBP15K dataset as the foundational dataset, which includes three cross-ingual datasets: Chinese-English (ZH-EN), Japanese-English (JA-EN), and French-English (FR-EN).</span></p>
Deepurify: a multi-modal deep language model to remove contamination from metagenome-assembled genomes
<p>The SIM2 testing set.</p>
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.