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Risk and predictors of stroke recurrence after ischaemic stroke: a prospective cohort study in a mountainous province of central highlands in Vietnam
<p>Dataset associated with "Risk and predictors of stroke recurrence after ischaemic stroke: a prospective cohort study in a mountainous province of central highlands in Vietnam" manuscript</p>
Topological Overlap Matrices for DNA Methylation data of Gestational Diabetes Cohort with BMI and Exposure Status
<p>DNA methylation in placenta was measured with the Infinium HumanMethylation450 BeadChip (Illumina, Inc) microarray, in a sample of 28 women, 20 of whom had a gestational diabetes (GD)-affected pregnancy and 8 who did not. We used GD status as our exposure variable, assuming that this has widespread effects on DNA methylation and on its correlation patterns. Our response, Y, is the standardized body mass index (BMI) in the offspring at the age of 5. For the 10,000 most variable probes, we provide 3 topological overlap matrices (TOM), which are used in our analysis (note that each of the following TOM matrices are a 10,000 by 10,000 symmetric matrix with row names and column names corresponding to the CpG probe IDs:</p> <ol> <li>TOM_Methylation_All_10k.rds: based on all 28 subjects, </li> <li>TOM_Methylation_E0_10k.rds: based on the 8 subjects without a GD-affected pregnancy</li> <li>TOM_Methylation_E1_10k.rds: based on the 20 subjects with a GD-affected pregnancy </li> </ol> <p>The BMI (phenotype) and GD status (exposure) are given in the following dataset:</p> <ol> <li>BMI_and_Exposure_Status.rds: 28 x 2 matrix of the phenotype and exposure. each row is a subject.</li> </ol> <p>Using our ECLUST method (preprint available at http://sahirbhatnagar.com/slides/manuscript1_SB_v4.pdf), we derive 77 clusters, and here we provide the 1st principal component of each cluster:</p> <ol> <li>Cluster_Summary_1stPC.rds: 28 x 77 matrix, where each row is a subject, in the same order as the BMI_and_Exposure_Status.rds data</li> <li>Cluster_CpGs_names.rds: a list of length 77, where each element of the list contains the list of CpG probe IDs contained in each of the clusters</li> </ol> <p>To read in the data use the readRDS function, e.g.:</p> <p>TOM_All <- readRDS(file = "TOM_Methylation_All_10k.rds")</p>
MDSINE2 Cross-Validation Analysis (Healthy Cohort)
<p>MDSINE2 Inference Analysis files. This archive contains all output files from the cross-validation inference (with comparator analysis included) for Healthy cohort. (Both healthy and dysbiotic cohorts are required to run the Jupyter Notebook (`fig4_semisynthetic_v2_cache.ipynb`) on our MDSINE2_Paper repo. For the Dysbiotic cohort files, refer to <a href="https://zenodo.org/records/16915340" target="_blank" rel="noopener">https://zenodo.org/records/16915340</a>.</p> <p>For the full project/source pipeline, refer to <a href="https://github.com/gerberlab/MDSINE2_Paper">https://github.com/gerberlab/MDSINE2_Paper</a>.</p> <p>The archive here was created using the command `tar --zstd -cvf`, and then split using the unix "split" command. To unpack these files, please use the following command:</p> <pre><code>cat cross_validation_healthy.tar.zst.part* > cross_validation_healthy.tar.zst tar -I zstd -xvf cross_validation_healthy.tar.zst</code></pre> <p>These files should be unpacked and placed in the paper repository directory (wherever you did `git clone`), so that the `datasets` directory is directly inside `MDSINE2_Paper` repository directory. </p> <p>------------</p> <p>Related zenodo records:</p> <p><a href="https://doi.org/10.5281/zenodo.8208502">https://doi.org/10.5281/zenodo.8208502</a> -- Full MDSINE2 inference on Healthy cohort</p> <p><a href="https://doi.org/10.5281/zenodo.16915340">https://doi.org/10.5281/zenodo.16915340</a> -- MDSINE2 Cross-Validation run (Dysbiotic cohort)</p> <p><a href="https://doi.org/10.5281/zenodo.16915311">https://doi.org/10.5281/zenodo.16915311</a> -- MDSINE2 semisynthetic dataset</p>
Clinical and genetic findings in an Italian cohort of individuals with congenital cataract
<p>List of variants and associated clinical phenotypes identified in a cohort of individuals affected by congenital cataract (syndromic and non-syndromic forms) that have been submitted to the public ClinVar repository (https://www.ncbi.nlm.nih.gov/clinvar/) with their corresponding accession numbers.</p>
A cohort-based study of host gene expression: tumor suppressor and innate immune/inflammatory pathways associated with the HIV reservoir size
<p>The major barrier to an HIV cure is the HIV reservoir: latently-infected cells that persist despite effective antiretroviral therapy (ART). Most prior studies of host genetic predictors of HIV control have focused on "elite controllers," rare individuals able to control virus in the absence of ART. However, there have been few genetic studies among ART-suppressed non-controllers, who make up the majority of people living with HIV (PLWH). We performed host RNA sequencing and HIV reservoir quantification (total DNA [tDNA], unspliced RNA [usRNA], intact DNA) from peripheral CD4+ T cells from 191 HIV+ ART-suppressed non-controllers. After adjusting for nadir CD4+ count, timing of ART initiation, and genetic ancestry, we identified two host genes for which higher expression was significantly associated with smaller total DNA viral reservoir size, <em>P3H3</em> and <em>NBL1</em>, both known tumor suppressor genes. We then identified 17 host genes for which lower expression was associated with higher residual transcription (HIV usRNA). These included novel associations with membrane channel (<em>KCNJ2</em>, <em>GJB2</em>), inflammasome (<em>IL1A, CSF3, TNFAIP5, TNFAIP6, TNFAIP9, CXCL3, CXCL10</em>), and innate immunity (TLR7) genes (FDR-adjusted q<0.05). Gene set enrichment analyses further identified significant associations of HIV usRNA with TLR4/microbial translocation (q=0.006), IL-1/NRLP3 inflammasome (q=0.008), and IL-10 (q=0.037) signaling. Protein validation assays using ELISA and multiplex cytokine assays supported these observed inverse host gene correlations, with P3H3, IL-10, and TNF-a protein associations achieving statistical significance (p<0.05). Of note, plasma IL-10 was also significantly inversely associated with HIV DNA (p=0.016). HIV intact DNA was not associated with differential host gene expression, although this may have been due to a large number of undetectable values in our study. Further data are needed to validate these findings, including functional genomic studies, larger cohorts including underrepresented PLWH in research, and those including dedicated assays to measure the replication-competent HIV reservoir.</p>
Male-female disparity in clinical features and significance of mild vertebral fractures in community-dwelling residents aged 50 and over: A Japanese cohort survey randomly sampled from a basic resident registry
Open the record for dataset details and reuse information.
A bovine molQTL cohort for three reproductive tissues
<p>Transcriptome and whole-genome sequence variant data for a cohort of 118 post-pubertal bulls, as well as GWAS summary statistics for a cohort of 3736 bulls.</p><p>This dataset contains gene abundance (in TPM, both raw and normalized estimates), splicing variation (from LeafCutter), and whole-genome sequence variants (raw, unfiltered) for 118 bulls. Gene abundance and splicing variation is available for three reproductive tissues (testis, epididymis, vas deferens). Autosomal, X-chromosomal, and MT genes are included.</p><p>All sample-IDs refer to ENA accession numbers. A cross-table (cohort_accession_numbers.xlsx) allows to assign transcriptome to genotype data.</p><p>The bovine ARS-UCD1.2 assembly and the corresponding Ensembl annotation (ftp://ftp.ensembl.org/pub/release-104/gtf/bos_taurus/Bos_taurus.ARS-UCD1.2.104.chr.gtf.gz) was used</p>
Data from: the characteristics and treatment for severe postpartum hemorrhage in different midwifery hospitals in one district of Beijing in China: an institution-based, retrospective cohort study
<p><span><strong>Objective:</strong> </span><span>To identify the characteristics and treatment approaches for Severe Postpartum Hemorrhage (SPPH) patients in various midwifery institutions in one district in Beijing, especially those without identifiable antenatal PPH risk factors, to improve regional SPPH rescue capacity.</span></p> <p><strong><span>Design:</span></strong><span> Retrospective cohort study</span></p> <p><span><strong>Setting:</strong> </span><span>This study was conducted at n</span><span>ine tertiary-level hospitals and ten secondary-level hospitals</span><span> in Haidian district of Beijing from January 2019 to December 2022. </span></p> <p><strong><span>Participants:</span></strong> <span>The major inclusion criterion was SPPH cases with blood loss </span>≥<span>1500 ml or needing a packed blood product transfusion </span>≥<span>1000 ml within 24 h after birth</span><span>.</span><span> A total of 324 mothers suffering from SPPH were reported to the Regional Obstetric Quality Control Office from 19 midwifery hospitals. </span></p> <p><span><strong>Outcome measures:</strong> </span><span>The pregnancy characteristics collected included: age at delivery, gestational weeks at delivery, height, parity, delivery mode, antenatal PPH risks, etiology of PPH, bleeding amount, PPH complications, transfusion amount, and PPH management. SPPH characteristics were compared between two levels of midwifery hospitals and their association with antenatal PPH high-risk factors was determined.</span></p> <p><span><strong>Results:</strong> </span><span>SPPH was observed in 324 mothers out of 106697 mothers in the four years. There were 74.4% and 23.9% cases of SPPH without detectable antenatal PPH high-risk factors in secondary and tertiary midwifery hospitals, respectively. Primary uterine atony was the leading cause of SPPH in secondary midwifery hospitals, whereas placental-associated disorders were the leading causes in tertiary institutions, accounting for over 50% of cases. In all SPPH cases, the rates of red blood cell transfusion over 10U, </span><span>unscheduled returns to the operating room,</span><span> and adverse PPH complications were higher in patients without antenatal PPH risk factors. Secondary hospitals had significantly higher rates of trauma compared with tertiary institutions.</span></p> <p><span><strong>Conclusion:</strong> </span><span>Examining SPPH cases at various institutional levels offers a more comprehensive view of regional SPPH management and enhances targeted training in this area.</span></p>
Supplementary file for the manuscript entitled: Demographic and genetic impacts of powdery mildew in a young oak cohort
<p>Barres et al 2023 Supplementary material-vf.pdf: supplementary material file for the related article</p>
Establishing a Dual Generational Modality Dataset: Comparing the Ride-Sharing Adoption Trends and Perspectives of Consumers from two Generational Cohorts, Millennials and Gen-Xers - E2
<p>Ride-hailing services such as Uber or Lyft are the latest tool in sustainable transportation strategies to come under scrutiny. Originally thought to be a way to reduce congestion, these services have actually been shown to increase it in some cases. Although the number of individuals driving around urban centers to find parking appears to decrease with the adoption of ride-hailing, Uber or Lyft drivers are instead circling around waiting for riders. Additionally, ride-hailing services have not led to the abandonment of personal vehicles, but rather to the abandonment of public transit in some cases.</p> <p>The purpose of this study is to evaluate the use of ride-hailing services in the two largest age cohorts in the United States: Millennials and Generation X-ers, focusing on the Southeastern states of Florida and North Carolina. This study seeks to determine how each generation has adopted these methods to help planners learn how to incorporate these strategies in transportation planning.</p> <p>The data provides information about the mode of transportation, trip details, and important socio-economic indicators of 1903 respondents from Florida and North Carolina.</p>
Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: validation cohort meta data and parsed TCR repertoire data
<p>Meta data corresponding the the validation cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: </p> <p>(1) SNP genotypes for the two SNPs which overlap with the discovery cohort<br> - (nicaragua_snp_genotypes_ints.tsv) -- SNP genotypes as integers<br> - (nicaragua_snp_genotypes_strings.tsv) -- SNP genotypes as allele strings <br> (2) the ancestry PCs for each individual in the validation cohort (nicaragua_snp_ancestry_PCA.tsv)<br> (3) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (4) a file including IMGT genes used for parsing TCRA repertoire data (human_vj_alleles_alpha.tsv)<br> (5) Parsed TCRA repertoire data (nicaragua_parsed_TCRA.tgz)<br> (6) Parsed TCRB repertoire data (nicaragua_parsed_TCRB.tgz) </p> <p><strong>Corresponding raw validation cohort TCR repertoire data is available here:</strong> https://www. ncbi.nlm.nih.gov/bioproject/PRJNA762269 (The BioProject database, accession number: PRJNA762269)</p> <p><strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas</p>
The indirect impact of COVID-19 on major clinical outcomes of people with Parkinson's disease or atypical parkinsonism: a cohort study. Raw data
<p>Raw dataset of the study "The indirect impact of COVID-19 epidemic on major clinical outcomes of people with Parkinson’s disease (PD) or atypical parkinsonism: a cohort study"</p>
Mental health and alcohol use among patients attending a post-COVID-19 follow-up clinic: A cohort study.
<p>Study dataset</p> <p>Abstract</p> <p><strong>Background:</strong> Ongoing mental health problems following COVID-19 infection warrant greater examination. This study aimed to investigate psychiatric symptoms and problematic alcohol use among Long COVID patients.<br> <br> <strong>Methods: </strong>The study was conducted at the Mater Misericordiae University Hospital’s post-COVID-19 follow-up clinic in Dublin, Ireland. A prospective cohort study design was used encompassing assessment of patients’ outcomes at 2-4 months following an initial clinic visit (Time 1), and 7–14-month follow-up (Time 2). Outcomes regarding participants’ demographics, acute COVID-19 healthcare use, mental health, and alcohol use were examined.<br> <br> <strong>Results: </strong>The baseline sample’s (n = 153) median age = 43.5yrs (females = 105 (68.6%)). Sixty-seven of 153 patients (43.8%) were admitted to hospital with COVID-19, 9/67 (13.4%) were admitted to ICU, and 17/67 (25.4%) were readmitted to hospital following an initial COVID-19 stay. Sixteen of 67 (23.9%) visited a GP within seven days of hospital discharge, and 26/67 (38.8%) did so within 30 days. Seventeen of 153 participants (11.1%) had a pre-existing affective disorder. The prevalence of clinical range depression, anxiety, and PTSD scores at Time 1 and Time 2 (n = 93) ranged from 12.9% (Time 1 anxiety) to 22.6% (Time 1 PTSD). No statistically significant differences were observed between Time 1 and Time 2 depression, anxiety, and PTSD scores. Problematic alcohol use was common at Time 1 (45.5%) and significantly more so at Time 2 (71.8%). Clinical range depression, anxiety, and PTSD scores were significantly more frequent among acute COVID-19 hospital admission and GP attendance (30 days) participants, as well as among participants with lengthy ICU stays, and those with a previous affective disorder diagnosis.<br> <br> <strong>Conclusions: </strong>Ongoing psychiatric symptoms and problematic alcohol use in Long COVID populations are a concern and these issues may be more common among individuals with severe acute COVID-19 infection and /or pre-existing mental illness.</p>
Women's view on shared decision making and autonomy in childbirth: Cohort study of Belgian women.
<p>This is a prospective, non-interventional study to explore the birth experience of Flemish women. A self-assembled questionnaire was used to collect data, including the Pregnancy and Childbirth Questionnaire (PCQ), the Labor Agenty Scale (LAS), the Mothers Autonomy Decision Making Scale (MADM),the 9-item Shared Decision Making Questionnaire (SDM–Q9) and four questions on preparation for childbirth. Women who gave birth two to twelve months ago were recruited by means of social media in the Flemish area (Northern part of Belgium).</p> <p>Linear mixed-effect modelling with backwards variable selection was applied to examine relations with autonomy in decision making.</p> <p>In total, 1029 mothers participated in this study of which 617 filled out the survey completely. Data were saved with IBM® SPSS® (version 25).</p>
Fig. 11 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 11. Response of Gl. domesticus to maxTempColdestMonth.
Fig. 10 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 10. Response of L. destructor to continentality.
Fig. 6 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 6. Response of Gl. domesticus to PETcoldQ.
Fig. 8 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 8. Response of L. destructor to aridityIndexThornthwaite.
Fig. 7 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 7. Response of A. siro to aridityIndexThornthwaite.
Fig. 5 in Modelling The Bioclimatic Niche Of A Cohort Of Selected Mite Species (Acari, Acariformes) Associated With The Infestation Of Stored Products
Fig. 5. Response of L. destructor to PETcoldQ.
ScienceDex guides
Understand access before you commit
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.