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2,450 results for “CD4 T cells”
Supplementary information for: Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity, and neutralization sensitivity
<p>The human immunodeficiency virus (HIV) envelope protein (Env) mediates viral entry into host cells and is the primary target for the humoral immune response. Env is extensively glycosylated, and these glycans shield underlying epitopes from neutralizing antibodies. The glycosylation of Env is influenced by the type of host cell in which the virus is produced. Thus, HIV is distinctly glycosylated by CD4<sup>+</sup> T cells, the major target cells, and macrophages. However, the specific differences in glycosylation between viruses produced in these cell types have not been explored at the molecular level. Moreover, it remains unclear whether the production of HIV in CD4<sup>+</sup> T cells or macrophages affects the efficiency of viral spread and resistance to neutralization. To address these questions, we employed the simian immunodeficiency virus (SIV) model. Glycan analysis implied higher relative levels of oligomannose-type <em>N</em>-glycans in SIV from CD4<sup>+</sup> T cells (T-SIV) compared to SIV from macrophages (M-SIV), and the complex-type <em>N</em>-glycans profiles seem to differ between the two viruses. Notably, M-SIV demonstrated greater infectivity than T-SIV, even when accounting for Env incorporation, suggesting that host cell-dependent factors influence infectivity. Further, M-SIV was more efficiently disseminated by HIV-binding cellular lectins. We also evaluated the influence of cell type-dependent differences on SIV's vulnerability to carbohydrate-binding agents (CBAs) and neutralizing antibodies. T-SIV demonstrated greater susceptibility to mannose-specific CBAs, possibly due to its elevated expression of oligomannose-type <em>N</em>-glycans. In contrast, M-SIV exhibited higher susceptibility to neutralizing sera in comparison to T-SIV. These findings underscore the importance of host cell-dependent attributes of SIV, such as glycosylation, in shaping both infectivity and the potential effectiveness of intervention strategies.</p>
CD4+ T cells re-wire granuloma cellularity and regulatory networks, promoting immunomodulation following Mtb reinfection
<p>Here we include the necessary .ipynb, .h5ad, and .rds (used for cell-cell interaction analyses) files used in our work: "Immunomodulatory re-wiring of granuloma cellularity and regulatory networks by CD4 T cells following Mtb reinfection"</p>
MK-0518 Intensification And HDAC Inhibition In Depletion Of Resting CD4+ T Cell HIV Infection
ClinicalTrials.gov study NCT00614458. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of Vorinostat on HIV RNA Expression in the Resting CD4+ T Cells of HIV+ Pts on Stable ART
ClinicalTrials.gov study NCT01319383. IPD Sharing: NO. Countries: 1. Publications: 4.
Adding Maraviroc to Antiretroviral Therapy for Suboptimal CD4 T-Cell Recovery Despite Sustained Virologic Suppression
ClinicalTrials.gov study NCT00709111. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Interleukin-7 (CYT107) Treatment of Idiopathic CD4 Lymphocytopenia: Expansion of CD4 T Cells (ICICLE)
ClinicalTrials.gov study NCT00839436. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Supplementary information for: Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity, and neutralization sensitivity
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Data from: IFN-γ-independent control of M. tuberculosis requires CD4 T cell-derived GM-CSF and activation of HIF-1α
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Data from: Multi-omics analyses on rheumatoid arthritis in CD4+ T cells
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Antigen-specific CD4+ T cells promote monocyte recruitment and differentiation into glycolytic lung macrophages to control Mycobacterium tuberculosis
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Data from: Subsets of tissue CD4 T cells display different susceptibilities to HIV infection and death: Analysis by CyTOF and single cell RNA-seq
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Timing of blood sample processing affects the transcriptomic and epigenomic profiles in CD4+ T-cells of atopic subjects
<p><span>Optimal</span><span> pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4<sup>+</sup> T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, </span><span>CD4<sup>+</sup></span><span> T-cells were isolated from the first blood sample within 2 hours (immediate) or from the second blood sample after 24 hours storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed </span><span>CD4<sup>+</sup></span><span> T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed </span><span>CD4<sup>+</sup></span><span> T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood </span><span>CD4<sup>+</sup></span><span> T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operating procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.</span></p>
TCRb sequencing of CD4+ and CD8+ T cells from hematological patients (part 2)
<p>This dataset contains TCRb sequencing of 177 samples from patients with aplastic anemia, myelodysplastic syndrome, immune thrombocytopenia, immunodeficiency or graft-versus-host disease and healthy controls. Samples are separated CD4+ or CD8+ cells from peripheral blood or bone marrow. The data has been produced with immunoSEQ platform (Adaptive Biotechnologies). The details regarding sample processing, sequencing and metadata can be found from the publication <em>Somatic mutations associate with clonal expansion of CD8+ T cells</em> (Lundgren et al, Science Advances, in press).</p> <p>The dataset is divided in 2 parts containing 91 (part 1) and 86 (part 2) files. Data is in immunoSEQ format (v2).</p>
Data and Scripts for "Timing matters in Macrophage / CD4+ T cell interactions: An agent-based model comparing Mycobacterium tuberculosis host-pathogen interactions between latently infected and naïve individuals"
<p>This contains the data and graphing scripts necessary to recreate all figures in the paper "Timing matters in Macrophage / CD4+ T cell interactions: An agent-based model comparing Mycobacterium tuberculosis host-pathogen interactions between latently infected and naïve individuals". Supplemental Material for the paper is also provided here. Please refer to the README.md for instructions on how to use. The model can be found at: https://github.itap.purdue.edu/ElsjePienaarGroup/LTBINaiveinvitroModel/ along with the uncalibrated parameter files and scripts to run on HPCs.</p>
Activation markers plotted against nutrient sensors in CD4+ and CD8+ T-cells.
<p>Activation markers (CD69, CD25, CD71, and CD38) plotted against nutrient sensors (GLUT1, GLUT4, HK1, HK2, and CD36) in CD4+ T-cells.</p>
Potential clinical implications of CD4+CD26high T cells for nivolumab treated melanoma patients
<table> <tbody> <tr> <td> <p>Background Nivolumab is an anti-PD1 antibody that has dramatically improved metastatic melanoma patients’ outcomes. Nevertheless, many patients are resistant to PD-1 inhibition, occasionally experiencing severe off-target immune toxicity. In addition, no robust and reproducible biomarkers have yet been validated to identify the correct selection of patients who will benefit from anti-PD-1 treatment avoiding unwanted side effects. However, the strength of CD26 expression on CD4+ T lymphocytes permits the characterization of three subtypes with variable degrees of responsiveness to tumors, suggesting that the presence of CD26-expressing T cells in patients might be a marker of responsiveness to PD-1-based therapies. </p> <p>Methods The frequency distribution of peripheral blood CD26-expressing cells was investigated employing multi-parametric flow cytometry in 69 metastatic melanoma patients along with clinical characteristics and blood count parameters at baseline (W0) and compared to 20 age- and sex-matched healthy controls. Percentages of baseline CD4+CD26high T cells were correlated with the outcome after nivolumab treatment. In addition, the frequency of CD4+CD26high T cells at W0 was compared with those obtained after 12 weeks (W1) of therapy in a sub-cohort of 33 patients.</p> <p>Results Circulating CD4+CD26high T cells were significantly reduced in melanoma patients compared to healthy subjects (p<0.001). In addition, a significant association was observed between a low baseline percentage of CD4+CD26high T cells (<7.3%) and clinical outcomes, measured as overall survival (p=0.010) and progression-free survival (p=0.014). Moreover, patients with clinical benefit from nivolumab therapy had significantly higher frequencies of circulating CD4+CD26high T cells than patients with non-clinical benefit (p=0.004) at 12 months. Also, a higher pre-treatment proportion of circulating CD4+CD26high T cells was correlated with Disease Control Rate (p=0.014) and best Overall Response Rate (p=0.009) at 12 months. Interestingly, after 12 weeks (W1) of nivolumab treatment, percentages of CD4+CD26 high T cells were significantly higher in comparison with the frequencies measured at W0 (p < 0.0001), aligning the cell counts with the ranges seen in the blood of healthy subjects.</p> <p>Conclusions Our study firstly demonstrates that peripheral blood circulating CD4+CD26high T lymphocytes represent potential biomarkers whose perturbations are associated with reduced survival and worse clinical outcomes in melanoma patients.</p> <p> </p> </td> </tr> </tbody> </table>
Gene expression of CD4+ T cells in the liver of SIV-infected macaques.
<p>Analysis of RNA transcripts of CD4+ T cells from the liver of healthy (n=3) and SIV infected (n=3) rhesus macaques using NovaSeq 6000 flowcell S1 at the Next-Generation Sequencing Platform, Genomics Center (CHU de Québec-Université Laval Research Center, Québec City, Canada). Gene symbols and amounts of transcripts per million (TPM) are listed for each condition.</p>
CD4 T cell receptor hierarchies are stable and independent of HIV-mediated dysregulation of immune homeostasis
<p>LT-ART and A5248 folders contain preprocessed CyTOF files (FCS format) from a 31-marker mass cytometry panel to examine all major PBMC lineages and specifically CD4 and CD8 T cell memory dynamics in people with HIV (PWH) who are durably ART suppressed for an average of 6.7 years (LT-ART, n = 10) and PWH in the first 500 days following ART initiation (A5248, n = 10). The panel also includes markers of activation (HLA-DR, CD38, CCR5), activation/exhaustion (PD-1), proliferation (Ki67), survival (Bcl-2) and long-lived memory (CD127).</p> <p>Preprocessed annotated data objects (A5248_subsample.h5ad, LT-ART_subsample.h5ad) for unsupervised analysis can be accessed using the 'read_h5ad' function in Scanpy.</p> <p>CD4_MSI and CD8_MSI folders contain the MSI data for the Gamma fixed-effects regression models. </p> <p>All source code for reproduction of the results can be found in the GitHub repository: <a href="https://github.com/glab-hiv/immune-recovery">https://github.com/glab-hiv/immune-recovery</a></p>
CD4+ and CD8+ T cell responses to peptides covering SARS-CoV-2 Spike in response to mRNA vaccination in persons recovered from SARS-CoV-2 infection
<p>These files contain intracellular cytokine staining flow cytometry data for CD4+ and CD8+ T cells after exposure of serial PBMC to SARS-CoV-2 spike peptides or control antigens. PBMC are from subjects recovered from SARS-CoV-2 infection that subsequently received mRNA vaccination. The data were analyzed and exported from FlowJo version 10 as individual gated events and related Boolean subsets for four functional markers: CD40L, IFN-g, IL-2, and TNF-a. Counts and frequencies are both included.</p> <p> </p> <p><strong>Procedure for obtaining data:</strong></p> <p>Cryopreserved peripheral blood mononuclear cells (PBMC) were thawed and rested overnight. PBMC (1 x 10<sup>6</sup> per well) were stimulated with a SARS-CoV-2 spike overlapping peptide pool (JPT, 1 μg/mL each peptide; 0.4% final DMSO concentration), 0.4% DMSO as a negative control, or PHA-P (Remel; 1.6 μg/mL final concentration) as a positive control, in the presence of anti-CD28 and anti-CD49d (BD Biosciences) antibodies at 37°C for 6 hours. Brefeldin A (Sigma) was added after 2 hours. Cells were stained with Live/Dead Near IR dye (Invitrogen), treated with FACS lyse (BD Biosciences) and frozen at -80<sup>o</sup>C. For staining, the cells were thawed, washed, and permeabilized with Permeabilizing solution 2 (BD Biosciences) then stained with fluorochrome labeled monoclonal antibodies to anti-human CD3 mAb (clone UCHT) conjugated with PE-Texas Red (ECD; Beckman Coulter), anti-human CD4 mAb (clone SK3) conjugated with BV510 (Biolegend), anti-human CD8 mAb (clone SK1) conjugated with PerCP-Cy5.5 (BD Biosciences), and the activation markers anti-human CD40L mAb (clone TRAP1) conjugated with BV421 (BD Biosciences), anti-human IFNγ mAb (clone 4S.B3) conjugated with PE (BD Biosciences), anti-human IL2 mAb (clone MQ1-17H12) conjugated with APC (BD Biosciences), and anti-human TNFα mAb (clone MAb11) conjugated with FITC (BD Biosciences). Events were recorded with BD Fortessa and analyzed with FlowJo (v10 for Mac; BD). </p>
Hematopoietic Stem Cell Mobilization in Idiopathic CD4 Lymphocytopenia Patients and Healthy Controls for the Study of T Cell Maturation and Trafficking in Murine Models
ClinicalTrials.gov study NCT02015013. IPD Sharing: YES. Countries: 1. Publications: 3.
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Allen Brain Atlas
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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.