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12,799 results for “Immunization”
Immunocto: a massive immune cell database auto-generated for histopathology
<p>As a first step towards building models that can recognise immune cells in WSIs, we introduce Immunocto, a high-resolution (40 x magnification) massive database of 2,282,818 immune cells distributed across 4 immune cell subtypes (CD4 T-cells, CD8+ T-cells, B-cells, and macrophages). To our knowledge, Immunocto is the largest available dataset of immune cells extracted from H\&E WSIs by an order of magnitude. All models trained with this database can be tried at www.octopath.ai</p>
Clinical course of neurologic adverse events associated with immune checkpoint inhibitors
<p>In the present dataset we collected clinical, demographic and outcome data of a large cohort of patients with neurological immune-related adverse events associated with immune check-point inhibitors. </p>
Quantification and Clustering of Immune States in Lymphocyte Populations of Hepatitis B Cirrhosis
<p><span>Quantification and Clustering of Immune States in Hepatitis B Cirrhosis</span></p>
Flow cytometry data of intestinal immune cells related to Seumetry toolkit for analysis of high-dimensional flow and mass cytometry data
Open the record for dataset details and reuse information.
Mass cytometry data of immune cells in mice that had experienced explosions.
<p>Mass cytometry was used to assess the expression of immune markers and intracellular proteins in immune cells collected from mice that had experienced explosions. Following mass cytometry detection, .fcs files were generated. The raw data were packaged and uploaded.</p>
Crystal structure of the LRR ectodomain from the plant immune receptor kinase SOBIR1 from Arabidopsis thaliana - sulphur SAD datasets
<p>This dataset includes the raw X-ray diffraction images collected on 06.11.2017 at beam line PXIII of the Swiss Light Source (SLS) Villigen, Switzerland. Native (dts_xxx, λ=1.033201 Å, 1 360° wedge at 0.1° oscillation) and redundant sulphur single-wavelength anomalous dispersion (SAD) data (ssad_xxx, λ= 2.078524 Å, 3 360° wedges at 0.1° oscillation) were collected to 1.75 Å and 3.12 Å resolution. The dataset includes a .bz2 archive of the XDS processing for native and sulphur SAD data, data were scaled together in xscale, the resulting xscale.hkl and nat1.hkl contain the integrated intensities and crystallographic structure factors. The corresponding coordinates have been deposited with the Protein Data Bank (http://rcsb.org) with ID 6R1H.</p>
Adaptive immune responses to Omicron BA.4/BA.5-containing bivalent mRNA booster vaccination
<p>This repository contains the immunoSEQ T-cell receptor (TCR) and B-cell receptor (BCR) repertoire data used in the manuscript titled "Adaptive immune responses to Omicron BA.4/BA.5-containing bivalent mRNA booster vaccination". This data set is composed of the TCR/BCR repertoire clonotype sequences and abundances derived from human peripheral blood mononuclear cell (PBMC) samples sorted for CD4, CD8 and CD19 before and after bivalent COVID mRNA booster vaccination. In total, 84 TCR samples (CD4+/CD8+ T cell populations at pre-/post-vaccination from 21 subjects) and 42 BCR samples (CD19+ populations at at pre-/post-vaccination from 21 subjects) are present in the data set.</p> <ul> <li><em><strong>Delmonte_TCR_data_84samples.rds</strong></em><br>R object with the amino acid and nucleotide sequences, VDJ gene calls, and abundances of the TCR clonotypes.</li> <li><strong><em>Delmonte_BCR_data_42samples.rds </em></strong> <br>R object with the amino acid and nucleotide sequences, VDJ gene calls, and abundances of the BCR clonotypes.</li> <li><em><strong>Delmonte_TCR_data_compact_84samples.rds</strong></em><br>R object with the amino acid sequences, VDJ gene calls, and abundances of the TCR clonotypes.</li> <li><em><strong>Delmonte_BCR_data_compact_42samples.rds </strong></em><br>R object with the amino acid sequences, VDJ gene calls, and abundances of the BCR clonotypes.</li> <li><em><strong>sampleExport_TCR.zip</strong></em><br>Compressed folder that includes the individual sample level TCR repertoire files in .tsv format.</li> <li><em><strong>sampleExport_BCR.zip</strong></em><br>Compressed folder that includes the individual sample level BCR repertoire files in .tsv format.</li> </ul> <p><br><em>Funding statement: This work was supported by the Division of Intramural Research Programs of the National Institute of Allergy and Infectious Diseases and of the National Institute of Dental and Craniofacial Research, National Institutes of Health (grant AI001270).</em><br><br></p> <p> </p>
Confocal microscopy data associated with "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity"
<p><strong>Confocal microscopy data as described in "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity".</strong></p> <p> </p> <p>Data relate to Figure 2 (“Mp10 interacts with AMSH deubiquitinases in yeast and plants”) involving FLIM-FRET imaging data to determine the interaction between eGFP-tagged <em>Myzus persicae </em>Mp10 and mCherry-tagged <em>Nicotiana benthamiana </em>AMSH proteins in plant cells; and Figure 6 (“Mp10 affects the abundance and localisation of cell-surface receptor-like kinases) involving confocal microscopy showing the effect of Mp10-expression on the localisation of the GFP-tagged FLS2 receptor-kinase protein, and it’s colocalization with RFP-tagged markers of the plasma membrane and the tonoplast in plant cells.</p> <p>Constructs encoding fluorescent protein fusions were transformed into <em>Agrobacterium tumefaciens </em>GV3101, and mixed Agrobacterium cultures were infiltrated into mature leaves of <em>N. benthamiana </em>plants to co-express the desired combinations of proteins. All image data was gathered from lower epidermal leaf cells of infiltrated leaves 2-3 days post infiltration.</p> <p> </p> <p><strong>FLIM-FRET assays.</strong></p> <p>eGFP-tagged Mp10, or eGFP-alone, was co-expressed with mCherry-tagged AMSH proteins, or mCherry fused to aquaeorin in <em>N. benthamiana</em> via agroinfiltration as described above. Lower epidermal cells of leaf sections were imaged 2-3 days after infiltration using a Leica Stellaris 8. Images were captured detecting fluorescence from eGFP (WLL laser, ex.488 nm, em 509-534 nm.) mCherry (lWLL aser, ex. 587 nm em 603-625 nm.) and chlorophyll (WLL laser, ex 587 nm. em 687-712 nm.). Regions of cells showing expression of both eGFP- and mCherry- tagged proteins but lacking chlorophyll were selected for FLIM analysis to avoid bleed through of chlorophyll fluorescence into the eGFP chanel. Fluorescence lifetime data of EGFP were collected from these regions in FLIM mode (WLL laser ex. 488nm, em 525-530 nm.), data were collected at 128x128 resolution until 1000 photons per pixel were collected for the most intense regions of the image. Instrument response function was captured using erythrosine on each day of data collection. FLIM data were analysed using Leica LASX FLIM FCS software. Fluorescence lifetime decay curves of free eGFP control samples were modelled as a 2-component exponential function, and all samples from each experimental set were modelled against the fluorescence lifetime from the corresponding control samples to derive values for fluorescent lifetime and %FRET efficiency for each image collected. %FRET efficiency was mapped to the images and phasor plots were generated for regions with the highest and lowest FRET efficiency, showing that the FRET signal was associated with a clockwise shift on the phasor plot consistent with <em>bona-fide </em>FRET. Full experimental metadata for each image set are included within the .lif files.</p> <p> </p> <p><strong>FLS2-GFP localisation experiments.</strong></p> <p>Confocal microscopy analysis was performed on a Leica TCS SP8X confocal DM6 microscope with a 63x water-immersion objective, using Leica Application Suite X (LAS X) software (3.5.7.23225). eGFP and chlorophyll signals were excited by a 488 nm Argon laser with emission, respectively, at 495–545 nm and 690-710 nm. RFP signal was excited by a 590 nm white light laser (WLL) with emission at 605–650 nm. Full experimental metadata for each image set are included within the .lif files.</p> <p> </p> <p>Leica Image Files (.lif) that contain multiple images including metadata associated with image acquisition and processing.</p> <p> </p> <p>FLIM030823.lif</p> <p>FLIM130724.lif</p> <p>FLIM140623.lif</p> <p>FLIM160623.lif</p> <p>FLIM240523.lif</p> <p>FLIM250523.lif</p> <p>Files include FLIM-FRET data as shown in Figure 2 parts D-L.</p> <p>FLIM-data-files.xlsx includes a description of the individual image filenames, and the combinations of fluorophore imaged in each.</p> <p> </p> <p>Fig6cSlFLS2-gfp_Mp10-RFP.lif</p> <p>Fig6c-SlFLS2-GFP_EV-RFP.lif</p> <p>Correspond to Figure 6 C showing co-expression of RFP-tagged Mp10 (or free RFP control) co-expressed with GFP-tagged FLS2</p> <p> </p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-1x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-3x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-4-2-3x.lif</p> <p>0230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP4-2-1x.lif</p> <p>Correspond to Figure 6 D showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged plasma membrane marker Remorin</p> <p> </p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1a-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1b-1x.lif</p> <p>Correspond to Figure 6 E showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged tonoplast marker SUC4.</p> <p> </p> <p>We are grateful to the John Innes Centre (JIC) Bioimaging Platform for training and technical support</p> <p>This work was funded by UK Research and Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC) grants to SAH (BB/V008544/1 and BB/N009169/1), Additional Support was provided by the BBSRC Institute Strategy Programmes (BBS/E/J/000PR9797 and BBS/E/JI/230001B) awarded to the John Innes Centre (JIC). The JIC is grant-aided by the John Innes Foundation.</p> <p> </p>
Novel N6-methylandenosine-related long non-coding RNAs as a Prognostic Signature Associated with Tumor Immune Cell Infiltration in Breast Cancer
<p><strong>Supplementary Figure S1</strong>. The correlation between risk score and six types of tumor-infiltration immune cells in TIMER database.</p> <p><strong>Supplementary Figure S2</strong>. Expression levels of m6A-LPS related lncRNAs in 16 breast cancer tissues and paired normal breast tissues.</p>
A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma
<p>This repository contains R Seurat objects associated with our study titled "<strong>A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma</strong>". </p> <p>This repository contains two Seurat objects stored in .rds files containing processed single-cell RNA sequencing data from the original ‘Discovery’ cohort of the MMRF Immune Atlas study, along with an additional ‘Discovery + Validation’ cohort, as described in the original publication. These .rds files contain Seurat v4 objects with basic cell type annotation and qc metadata. Specific file contents will be detailed below.</p> <div> <p>A copy of the ‘Cell Annotation Dictionary’ is also included, which contains additional details on the individual annotated clusters in the Immune Atlas dataset.</p> <p>Information on how to request additional metadata about these samples and accessing the original fastq files will be detailed at the end of this description</p> </div>
Dataset for: Radiation therapy induces innate immune responses in patients treated for prostate cancers
<p><strong>Purpose </strong></p> <p>Radiation therapy (RT) is a curative therapeutic modality used to treat cancers as a single agent or in combination with surgery and chemotherapy. Advanced RT technologies enable treatment with large fraction, highly conformal, radiation doses to effect free-radical damage to cellular DNA leading to cell cycle arrest, cell death, and innate immune response stimulation.</p> <p><strong>Experimental Design </strong></p> <p>To understand systemic clinical responses after radiation exposure, high throughput proteomic and metabolomic analyses were performed on plasma obtained from cancer patients at intervals after prostate stereotactic body radiation therapy. Pathway analysis and multivariate analyses were used to delineate molecular alterations following radiation therapy and its correlation with clinical outcomes.</p> <p><strong>Results</strong></p> <p>DNA Damage Response (DDR) and cell cycle signaling increased within the first hour after treatment and returned to baseline by one month. Innate immune response signaling also increased within one hour of treatment but persisted for up to three months thereafter. Furthermore, robust immune responses and metabolite elevations, consistent with an early proinflammatory M1-mediated innate immune activation, were observed in patients in remission, whereas patients experiencing PSA-determined disease progression demonstrated less robust immune responses and M2-mediated metabolite elevations.</p> <p><strong>Conclusion/Discussion</strong></p> <p>To our knowledge, these data are the first report of longitudinal proteomic and metabolomic molecular responses in patients after radiation therapy for cancers. The data supports innate immune activation as a critical clinical response of patients receiving radiation therapy for prostate cancer. Furthermore, we propose that the observed innate immune responses may be generalized to the treatment of other cancer types, potentially informing multidisciplinary therapeutic strategies for cancer treatment.</p>
3D reconstruction of skin and spatial mapping of immune cell density, vascular distance and effects of sun exposure and aging
<p>Mapping the human body at single cell resolution in three dimensions (3D) is an important step toward a “digital twin” model that digitizes organ structure and the dynamics of cell-cell interactions. Current approaches for 3D reconstruction of multiplexed serial sections are relatively cumbersome and not automated. We present a novel 3D reconstruction workflow for multiplexed sequential tissue sections: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis). This combines a reproducible and streamlined method for two-dimensional (2D) cell segmentation and cell type classification, followed by 3D volume reconstruction. We also provide novel tools for 3D visualization of immune cell cluster density, cell-to-vasculature distance, and distance maps for cellular markers of UV damage/repair and proliferation to the skin surface. We used MATRICS-A to reconstruct 26 serial sections of fixed skin from 12 donors aged between 32-72 years. Samples were collected from six distinct anatomical regions with mild to marked sun exposure effects. Each tissue section was multiplexed with 18 fluorescently labeled antibodies covering 14 cell types in the epidermis and dermis. We demonstrate several new findings that are only possible in 3D, We present novel visualization of immune cell clusters and show that there are 10-70% more T cells (total) within 30 µm of a T helper cell in 3D vs 2D. Distances of cell markers of DNA damage (p53), DNA repair (DDB2) and proliferation (Ki67) to the skin surface were consistent across all ages/sun exposure. MATRICS-A provides a new powerful integrated open access approach to quantify 3D spatial cell relationships in healthy and aging organs and could be further extended to diseased organs. </p>
Readout of quantum devices with a sideband microwave interferometer immune to systematic noise
<p>supporting data from paper 'Readout of quantum devices with a sideband microwave interferometer immune to systematic noise' by N. Crescini, E.G. Kelly, G. Salis and A. Fuhrer</p>
The Effects of Perioperative Dexmedetomidine Administration on Immune Suppression and Outcomes in Patients With Uterine Cancer Undergoing Radical Resection
ClinicalTrials.gov study NCT02896413. IPD Sharing: NO. Countries: 1. Publications: 0.
GCWB1176 Evaluates the Effectiveness and Safety of Immune Function
ClinicalTrials.gov study NCT05632341. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Assessment of Vitamin D Supplementation and Immune Function
ClinicalTrials.gov study NCT01399151. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Immune Response Against the Strain of Neisseria Meningitidis B: 14, P1-7, 16 in Patients Having to be Vaccinated MenBVac® (Extension EFFIVAC)
ClinicalTrials.gov study NCT01621945. IPD Sharing: Not stated. Countries: 1. Publications: 0.
An Immunity Persistence Study of Live Attenuated Varicella Vaccine
ClinicalTrials.gov study NCT05095701. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact of Neoadjuvant Chemotherapy on the Peripheral Blood Immune Phenotype in Operable Breast Cancer
ClinicalTrials.gov study NCT04897009. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study on the Safety, Reactogenicity, and Immune Response to the GVGH iNTS-GMMA Vaccine Against Invasive Nontyphoidal Salmonella in Adults, Children, and Infants
ClinicalTrials.gov study NCT06213506. IPD Sharing: YES. Countries: 1. Publications: 0.
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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.