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Dataset results
39 results for “Type defects”
Comparison of Two Types of Shunts in Infants With Single Ventricle Defect Undergoing Staged Reconstruction--Pediatric Heart Network
ClinicalTrials.gov study NCT00115934. IPD Sharing: Not stated. Countries: 2. Publications: 36.
Defective interferon signaling in the circulating monocytes of type 2 diabetic mice
<h1>Data Repository for scRNA-seq and Cell Communication Analysis in T2DM Stroke Model</h1> <p>This repository contains the data and Seurat/CellChat objects generated for analyzing the transcriptomic response of peripheral monocytes to Type 2 Diabetes Mellitus (T2DM) and ischemic stroke in a mouse model. Data were generated using single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and analysis with NicheNet and CellChat. This study aims to reveal molecular and cellular changes in diabetic and ischemic conditions, particularly focusing on interferon signaling and inflammation.</p> <h2>Repository Structure</h2> <h3>Root Files</h3> <ul> <li> <p><code>README.md</code>: This file, describing the repository and data files.</p> </li> <li> <p><code>cellchat_object/</code>: Contains RDA files for CellChat analysis.</p> </li> <li> <p><code>scrna_sequencing_raw/</code>: Raw scRNA-seq data files.</p> </li> <li> <p><code>seurat_object/</code>: Contains Seurat objects for clustering and visualization.</p> </li> <li> <p><code>trajectory_object/</code>: Contains Cell Data Set (CDS) objects for trajectory and pseudotime analysis.</p> </li> </ul> <h3>File Descriptions</h3> <h4><code>cellchat_object/</code></h4> <ul> <li> <p><strong>dbdb_case_cellchat.rda</strong>: CellChat object for the db/db mice with ischemic stroke. Analysis was conducted to identify cell-cell communication patterns altered due to stroke in diabetic conditions.</p> </li> <li> <p><strong>dbdb_control_cellchat.rda</strong>: CellChat object for db/db control (no stroke) mice. Provides baseline data for diabetic conditions.</p> </li> <li> <p><strong>dbp_case_cellchat.rda</strong>: CellChat object for the db/+ (normoglycemic) mice with ischemic stroke, representing the stroke model in non-diabetic conditions.</p> </li> <li> <p><strong>dbp_control_cellchat.rda</strong>: CellChat object for db/+ control (no stroke) mice. Baseline for non-diabetic, non-stroke conditions.</p> </li> </ul> <p><strong>Methods</strong>: CellChat analysis identifies ligand-receptor interactions to reveal cross-talk between monocyte subtypes, focusing on pathways affected by T2DM and stroke. These data provide insights into thromboinflammatory responses, interferon signaling, and immune suppression in diabetic mice.</p> <h4><code>scrna_sequencing_raw/</code></h4> <ul> <li> <p><strong>db_db-DMCAO.zip</strong>: Raw scRNA-seq data for db/db mice post-distal middle cerebral artery occlusion (DMCAO).</p> </li> <li> <p><strong>db_db-Sham.zip</strong>: Raw scRNA-seq data for db/db mice with sham surgery (control).</p> </li> <li> <p><strong>db_pos-Sham.zip</strong>: Raw scRNA-seq data for db/+ mice with sham surgery.</p> </li> <li> <p><strong>db_pos-dMCAO.zip</strong>: Raw scRNA-seq data for db/+ mice post-DMCAO.</p> </li> </ul> <p><strong>Methods</strong>: scRNA-seq was performed using 10X Genomics GemCode Technology. Data were processed with Cell Ranger (v1.3), and differential gene expression analysis was conducted in Seurat with normalization based on UMI counts.</p> <h4><code>seurat_object/</code></h4> <ul> <li> <p><strong>bloodstroke.rda</strong>: Seurat object containing processed scRNA-seq data of peripheral blood mononuclear cells (PBMCs) from both diabetic and normoglycemic mice under stroke and sham conditions. Contains cell clusters annotated using SingleR and the ImmGen database.</p> </li> <li> <p><strong>monocytes.rda</strong>: Seurat object specifically for monocytes, enriched through re-clustering in Seurat. Enables focused analysis of monocyte subsets and their responses to diabetic and ischemic conditions.</p> </li> </ul> <p><strong>Methods</strong>: Filtering was performed for cells with fewer than 500 detected genes, and data were normalized using log-normalization. Clustering was carried out with PCA and visualized with UMAP.</p> <h4><code>trajectory_object/</code></h4> <ul> <li> <p><strong>dbdb_control_cds.rda</strong>: Cell Data Set (CDS) object for db/db control monocytes, representing baseline differentiation trajectory under diabetic conditions.</p> </li> <li> <p><strong>dbdb_stroke_cds.rda</strong>: CDS for db/db stroke monocytes, used to observe pseudotime trajectories and differentiation in diabetic and ischemic states.</p> </li> <li> <p><strong>dbp_control_cds.rda</strong>: CDS for db/+ control monocytes, baseline data for normoglycemic mice.</p> </li> <li> <p><strong>dbp_stroke_cds.rda</strong>: CDS for db/+ stroke monocytes, tracking pseudotime trajectory in response to ischemic stroke.</p> </li> <li> <p><strong>monocytes_cds.rda</strong>: CDS focusing on monocyte trajectory across all experimental conditions, facilitating the comparison of diabetic and normoglycemic trajectories.</p> </li> </ul> <p><strong>Methods</strong>: Trajectory analysis was conducted in Monocle 3 to explore cellular differentiation paths. Trajectories reveal potential maturation stages and highlight changes due to T2DM and ischemic conditions.</p> <h2>Methodology Overview</h2> <ol> <li> <p><strong>scRNA-seq and Bulk RNA-seq</strong>: Mononuclear cells were isolated and sequenced using 10X Genomics protocols, with analysis in Seurat to determine cell clusters, particularly monocytes. Bulk RNA-seq was used for pathway validation in broader cell populations.</p> </li> <li> <p><strong>CellChat Analysis</strong>: Ligand-receptor interactions were identified in CellChat, analyzing how cell communication changes with T2DM and stroke. Pathways of interest include the Anxa1-Fpr2 axis for thromboinflammation and MHCII-CD4 for immune activation.</p> </li> <li> <p><strong>Trajectory Analysis</strong>: Using Monocle 3, we investigated monocyte differentiation paths to uncover the effects of T2DM and stroke on cellular progression. Results demonstrate disrupted monocyte differentiation and increased proinflammatory markers in diabetic stroke conditions.</p> </li> <li> <p><strong>NicheNet Analysis</strong>: Identified key ligands affecting monocyte gene expression in diabetic versus non-diabetic conditions, highlighting interferon signaling and inflammatory markers such as Ccl6, Ccl9, and Ifng.</p> </li> </ol> <h2>Notes</h2> <ul> <li> <p>Ensure all analyses respect data filtering thresholds as set in Seurat and Monocle.</p> </li> <li> <p>Refer to the manuscript for further details on experimental setup, animal models, and additional context.</p> </li> </ul> <h2>License</h2> <p>Data and scripts are available for non-commercial use under a Creative Commons License.</p>
Sporadic pseudohypoparathyroidism type 1B in monozygotic twins: insights into the pathogenesis of methylation defects
<p>Context: Sporadic pseudohypoparathyroidism type 1B (sporPHP1B) is an imprinting disease without a defined genetic cause, characterized by broad methylation changes in differentially methylated regions (DMRs) of the <i>GNAS</i> gene.</p> <p>Objective: This work aims to provide insights into the causative event leading to the <i>GNAS</i> methylation defects through comprehensive molecular genetic analyses of a pair of female monozygotic twins concordant for sporPHP1B who were conceived naturally i.e., without assisted reproductive techniques.</p> <p>Methods: Using the leukocyte genome of the twins and family members, we performed targeted bisulfite sequencing, methylation-sensitive restriction enzyme (MSRE)-qPCR, whole-genome sequencing (WGS), high-density SNP array, and Sanger sequencing.</p> <p>Results: Methylation analyses by targeted bisulfite sequencing and MSRE-qPCR revealed almost complete loss of methylation at the <i>GNAS</i> AS, XL, and A/B DMRs and gain of methylation at the NESP55 DMR in the twins, but not in other family members. Except for the <i>GNAS</i> locus, we did not find apparent methylation defects at other imprinted genome loci of the twins. WGS, SNP array, and Sanger sequencing did not detect the previously described genetic defects associated with familial PHP1B. Sanger sequencing also ruled out any novel genetic alterations in the entire NESP55/AS region. However, the analysis of 28 consecutive SNPs could not exclude the possibility of paternal heterodisomy in a span of 22 kb comprising exon NESP55 and AS exon 5.</p> <p>Conclusion: Our comprehensive analysis of a pair of monozygotic twins with sporPHP1B ruled out all previously described genetic causes. Twin concordance indicates that the causative event was an imprinting error earlier than the timing of monozygotic twinning.</p>
Data and Code for [Localization of Mechanical and Electrical Defects in Dry-Type Transformers Using an Optimized Acoustic Imaging Approach]
Open the record for dataset details and reuse information.
Tuberosity Versus Palatal Connective Tissue Graft on the Treatment of Single Maxillary Recession-type Defects
ClinicalTrials.gov study NCT06404762. IPD Sharing: NO. Countries: 1. Publications: 4.
Two Types of PRF Membranes in Management of Dehiscence Defect in Posterior Mandible
ClinicalTrials.gov study NCT07164417. IPD Sharing: NO. Countries: 1. Publications: 0.
Impaired Type I IFN Immunity Due to Autoantibodies or a Genetic Defect: a Prospective National Cohort
ClinicalTrials.gov study NCT06762002. IPD Sharing: NO. Countries: 1. Publications: 3.
Sporadic pseudohypoparathyroidism type 1B in monozygotic twins: insights into the pathogenesis of methylation defects
Open the record for dataset details and reuse information.
Safety and Efficacy of Periodontal Surgery in Supra-alveolar-type Defects With or Without Straumann® Emdogain
ClinicalTrials.gov study NCT01614925. IPD Sharing: NO. Countries: 1. Publications: 0.
The Role of Type H Vessel Formation in Induced Membrane of Patients With Critical Size Bone Defect
ClinicalTrials.gov study NCT05792371. IPD Sharing: Not stated. Countries: 0. Publications: 2.
Dietary folic acid prevents peripheral neuropathy in mouse models of neural tube defects and type 2 diabetes
GEO Series GSE275111. Mus musculus. 25 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic dataset of Phaseolus vulgaris leaves in response to the inoculation of pathogenic Xanthomonas citri pv. fuscans and its type 3 secretion system-defective mutant hrcV.
GEO Series GSE271236. Phaseolus vulgaris. 36 samples. Type: Expression profiling by high throughput sequencing.
Gene expression in a Streptomyces coelicolor strain defective in sco1423 encoding a polyprenol phosphate mannose synthase (Ppm1) compared to the complemented mutant and the wild type parent
GEO Series GSE107982. Streptomyces coelicolor A3(2). 9 samples. Type: Expression profiling by high throughput sequencing.
A human mutation in STAT3 promotes type 1 diabetes through a defect in CD8+ T cell tolerance
GEO Series GSE173415. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing; Other.
Defective autophagy in CD4 T cells drives liver fibrosis via type 3 inflammation
GEO Series GSE292735. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
A human mutation in STAT3 promotes type 1 diabetes through a defect in CD8+ T cell tolerance [scATAC]
GEO Series GSE173412. Mus musculus. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Impaired bone fracture healing in type 2 diabetes is caused by defective functions of skeletal progenitor cells
GEO Series GSE180504. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell transcriptomics characterizes cell types in the subventricular zone and uncovers molecular defects impairing adult neurogenesis.
GEO Series GSE111527. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.
Cell-type-specific profiling of defects in translation and neurogenesis in a human iPSC model of fragile X syndrome
GEO Series GSE146339. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
A human mutation in STAT3 promotes type 1 diabetes through a defect in CD8+ T cell tolerance [scRNA, scTCR]
GEO Series GSE173413. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
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.