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30,817 results for “type”
Comparative Analysis: ChatGPT vs. Healthcare Professionals in Addressing Type-1 Diabetes FAQs in English and Arabic
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Hoplogryon ninus Nixon, holotype female, B.M. TYPE HYM. 9.393
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Decoding the Brain Mosaic: Region and Cell Type-Specific Dysregulation Patterns in Stress and Psychiatric Disorders
<p>Supplementary Online Tables for the doctoral thesis "Decoding the Brain Mosaic: Region and Cell Type-Specific Dysregulation Patterns in Stress and Psychiatric Disorders" by Nathalie Gerstner. </p> <p>This repository includes complete lists of differentially expressed and differential hub genes, alongside the results of enrichment analysis for 8 brain regions examined in a mouse model for transcriptomic alterations following glucocorticoid stimulation (Online Tables 1-30). Additionally, the repository encompasses the complete results of differential expression and chromatin accessibility analyses across various cell types examined in postmortem brain tissue of the orbitofrontal cortex (Online Tables 31-37). These findings delineate the transcriptomic and epigenomic changes between psychiatric cases and controls, as well as between donors with high and low genetic risk for psychiatric disorders.</p> <p>The lists of all genes tested in the respective studies, not just the significant ones, can be found in the "GRactivation_MouseBrain_tables.zip" and the "SingleNuc_PostmortemBrain_Tables.zip" archives.</p> <p> </p>
Arctic Sea Ice Type Products Based on Active and Passive Microwave Remote Sensing (2002-2021)
<p>Based on FY-3 MWRI and other microwave radiometer and scatterometer data, this dataset explores the distribution of Arctic sea ice types from 2002 to 2021 using the K-means clustering method. Spatial and temporal resolutions are 12.5 km and 1 day, respectively. The dataset is of integer type, where 0 represents open water, 1 represents first-year ice, 2 represents multi-year ice, 3 represents land, and 4 represents data gaps. The data is stored in .tiff format.</p>
Figs 20–21 in Remarks about type specimens of Cicindela elisae Motschulsky, 1859 and Cicindela amurensis Morawitz, 1862 (Coleoptera: Cicindelidae)
Figs 20–21. Variation in size and proportion of Cylindera (Eugrapha) elisae elisae: 20 — correlation of elytra length and width; 21 — relation of the proportions of pronotum and elytra; circles — males; crosses — females; red cross — lectotype of C. elisae; green crosses and simple green circle — paralectotypes of C. amurensis; double green circle — lectotype of C. amurensis; dotted oval — 95% concentration ellipse. Рис. 20–21. ИЗменчивость раЗмеров и пропорций Cylindera (Eugrapha) elisae elisae: 20 — соотноШение длины и Ширины надкрылий; 21 — соотноШение пропорций переднеспинки и надкрылий; кружки — самцы; кресты — самки; красный крест — лектотип C. elisae; Зелёные кресты и простой Зелёный кружок — паралектотипы C. amurensis; двойной Зелёный кружок — лектотип C. amurensis; пунктирный овал — 95% область Значений.
Figs 9–19 in Remarks about type specimens of Cicindela elisae Motschulsky, 1859 and Cicindela amurensis Morawitz, 1862 (Coleoptera: Cicindelidae)
Figs 9–19. Type specimens of C. amurensis. 9 — habitus; 10, 17 — labrum; 11, 14 — aedeagus; 13, 16 — left elytron; 18 — pronotum; 12, 15, 19 — labels; 9–12 — lectotype; 13–19 — paralectotypes; 9–15 — males; 16–19 — female. Scale bars: 1.0 mm. Рис. 9–19. Типовые ЭкЗемплЯры C. amurensis. 9 — габитус; 10, 17 — верхнЯЯ губа; 11, 14 — Эдеагус; 13, 16 — левое надкрылье; 18 — переднеспинка; 12, 15, 19 — Этикетки; 9–12 — лектотип; 13–19 — паралектотипы; 9–15 — самцы; 16–19 — самка. МасШтаб: 1,0 мм.
Figs 1–8 in Remarks about type specimens of Cicindela elisae Motschulsky, 1859 and Cicindela amurensis Morawitz, 1862 (Coleoptera: Cicindelidae)
Figs 1–8. Type specimens of C. elisae: 1, 4, 6 — habitus; 2 — labrum, 7 — aedeagus; 3, 5, 8 — labels; 1–3 — lectotype; 4–8 — paralectotypes; 1–5 — females; 6–8 — male. Scale bars: 1.0 mm. Рис. 1–8. Типовые ЭкЗемплЯры C. elisae: 1, 4, 6 — габитус; 2 — верхнЯЯ губа, 7 — Эдеагус; 3, 5, 8 — Этикетки; 1–3 — лектотип; 4–8 — паралектотипы; 1–5 — самки; 6–8 — самец. МасШтаб: 1,0 мм.
Types of competencies and skills for Industry 4.0
<p><strong>Types of competencies and skills for Industry 4.0</strong></p>
R Script and files for the Virtual reconstruction of Canis arnensis type from UVB (Italy, Early Pleistocene)
<p>Dataset for the paper: Bartolini-Lucenti, S., Cirilli, O., Melchionna, M., Raia, P., Tseng, Z.J., Flynn, J.J. and Rook, L., 2024. Virtual reconstruction of the Canis arnensis type (Canidae, Mammalia) from the Upper Valdarno Basin (Italy, Early Pleistocene). <em>Scientific Reports</em>, <em>14</em>. doi:10.1038/s41598-024-53073-5 <a href="https://www.nature.com/articles/s41598-024-53073-5">https://www.nature.com/articles/s41598-024-53073-5</a></p>
Automated cell type annotation and exploration of single cell signalling dynamics using mass cytometry and machine learning
<p>In this repository we share processed data that were generated using the bioinformatics framework we developed in publication "Automated cell type annotation and exploration of single cell signalling dynamics using mass cytometry and machine learning".</p> <p>These datasets accompany the source codes provided in our GitHub page https://github.com/dkleftogi/singleCellClassification. </p> <p>The datasets are as follows:</p> <ol> <li>cofactors_v2.RDa : antibody-specific co-factors used to harmonise fcs files from different batches</li> <li>ctrl_annotated.RDa : the annotated cohort of seven healthy donors</li> <li>data_umap.RDa : UMAP representation of the data used to generate the figures in our paper</li> <li>DREMI_feature_matrix.RDa : the DREMI feature matrix used for ML-based modelling presented in our paper</li> <li>median_feature_matrix.RDa : the baseline feature matrix based on medians used for ML-bases modelling in the paper</li> <li>patient_annotated.RDa : the annotated cohort of leukemia patients (n=43)</li> </ol> <p>We note that the raw files of the leukemia cohort can be found in http://flowrepository.org/id/RvFr0LLv9McDJ89jgK50G4lwnfDFRTrcMelxYgnSIcE2Cymrpf2qh2NaWybtWDNH</p> <p> </p>
Relationship between the Type of Media Consumption and Political Trust in the EU: Evidence from the 94th Eurobarometer 2020/2021 Survey
<p>This is a list of supplementary materials for the article titled "Relationship between the Type of Media Consumption and Political Trust in the EU: Evidence from the 94th Eurobarometer 2020/2021 Survey". It contains the following objects:</p> <p>1) R Script (as a markdown file).</p> <p>2) Raw dataset (copyright belongs to the European Union; the original source is the Eurobarometer website; https://europa.eu/eurobarometer/).</p>
A Lung Nodule Dataset with Histopathology-based Cancer Type Annotation (DICOM VERSION)
<p>We constructed a groundbreaking lung CT dataset, which includes 330 annotated nodules from 95 patients. It is worth noting that we have integrated the results of patient clinical diagnosis, frozen diagnosis, and pathological diagnosis, supplementing this with labeled lung cancer types on 308 samples containing nodules.</p>
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>
Data from: Arthropod abundance is most strongly driven by crop and semi-natural habitat type rather than management in an intensive agricultural landscape in the Netherlands
<p>The dataset supporting the publication "Arthropod abundance is most strongly driven by crop and semi-natural habitat type rather than management in an intensive agricultural landscape in the Netherlands" is provided. Methods of data collection can be found in the respective publication.</p>
Association of Disseminated Cutaneous Herpes Zoster and uncontrolled Diabetes Mellitus type II: A Case Report
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Transcriptomic neuron types vary topographically in function and morphology. Shainer*, Kappel* et al.
<p>Data files and analysis code for Shainer, Kappel et al. are provided. Each zip file includes the relevant data, R or Python code, and session/environment information necessary to reproduce the manuscript's results and figures.</p>
RNA sequencing data from the prefrontal cortex and hippocampus of male (12 weeks old) hemizyguous CAG-HERV-W-env mice and wild-type controls
<p>RNA sequencing data from the prefrontal cortex (PFC) and hippocampus (HIPP) of male (12 weeks old) hemizyguous CAG<sup>HERV-Wenv </sup>mice ( C57BL6/J;129P2/Ola-Hprt mice; <em>n</em> = 3) relative to wild-type ( <em>n</em> = 3) littermates. Total RNA was extracted from prefrontal and hippocampal samples using the SPLIT RNA extraction kit (Lexogen, Austria) following the manufacturer’s recommendations and was sent to the Functional Genomics Center in Zurich (FGCZ) for quality control and RNA sequencing. The quality of the isolated RNA was determined with a Fragment Analyzer (Agilent, Santa Clara, California, USA). Only those samples with a 260 nm/280 nm ratio between 1.8–2.1, a 28S/18S ratio within 1.5–2, and RIN (>8) values qualified for a Poly-A enrichment strategy in order to generate the sequencing libraries applying the TruSeq mRNA Stranded Library Prep Kit (Illumina, Inc, California, USA). After Poly-A selection using Oligo-dT beads the mRNA was reverse-transcribed into cDNA. The cDNA was fragmented, end-repaired and poly-adenylated before ligation of TruSeq UD Indices (IDT, Coralville, Iowa, USA). The quality and quantity of the amplified sequencing libraries were validated using a Fragment Analyzer SS NGS Fragment Kit (1–6000 bp) (Agilent, Waldbronn, Germany). The equimolar pool of the samples was spiked into a NovaSeq6000 run targeting ~15M reads per sample on a S1 FlowCell (Novaseq S1 Reagent Kit, 100 cycles, Illumina, Inc, California, USA). Reads were quality-checked with FastQC. Sequencing adapters were removed with Trimmomatic and aligned to the reference genome and transcriptome of Mus Musculus (GENCODE, GRCm38,p5) with STAR v2.7.3. Distribution of the reads across genomic isoform expression was quantified using the R package GenomicRanges from Bioconductor Version 3.10. Minimum mapping quality, as well as minimum feature overlaps, was set to 10. Multi-overlaps were allowed. Differentially expressed genes (DEGs) were identified using the R package edgeR from Bioconductor Version 3.10, using a generalized linear model (glm) regression, a quasi-likelihood (QL) differential expression test and the trimmed means of M-values (TMM) normalization.</p>
Supplementary data for: Identification of genes, cell types, and phenotypes under selective pressure across primate evolution
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Self-oscillations of the tube-like astrosphere: new type of instability
<p>Video files complement the main paper, which discusses the instability of astrospheric jets around stars with strong intrinsic magnetic fields.</p> <p><br>"Video-1.avi" corresponds to the 2D flow shown in Figure 2 (Panel A), where the interstellar medium is at rest, $M_A$ = 8, $\chi$ = 4.</p> <p><br>"Video-2.avi" corresponds to the 3D flow shown in Figure 4, with the interstellar medium also at rest and $M_A$ = 3, $\chi$ = 4.</p>
Multi-LES code output of Flower-type organized convection on 02 February, 2020 - 0-1D Files
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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.