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5,412 results for “Cell differentiation”
Co-exposure of uranyl acetate and sodium arsenite differentially alters gene expression in CD3/CD28 activated CD4+ T-cells.
Communities in the western region of the United States experience environmental exposure to metal mixtures from living in proximity to numerous unremediated abandoned uranium mines. Metals including arsenic and uranium co-occur in and around these sites at levels higher than the United States Environmental Protection Agency maximum contaminant levels. To address the potential effect of these metals on the activation of CD4+ T-cells, we used RNA sequencing methods to determine the effect of exposure to uranyl acetate, sodium arsenite or a mixture of uranyl acetate and sodium arsenite. Oxidative stress is a mechanism proposed for metal toxicity, but findings for uranium differ across cell models. No significant changes in oxidative stress genes were detected for uranyl acetate, in contrast to sodium arsenite. Sodium arsenite induced a dose dependent effect on activation associated gene expression, targeting immune response genes at the lower dose. While uranyl acetate alone did not significantly alter activation associated gene expression, the mixture demonstrated a combined effect relative to sodium arsenite alone. The results demonstrate the need to investigate uranium alone and in metalloid mixtures at environmentally relevant concentrations to better understand the toxicological impact of these mixtures on T-cell activation, function and immune dysregulation.
Dataset related to article "CXCR3 Identifies Human Naive CD8+ T Cells with Enhanced Effector Differentiation Potential."
<p>In mice, the ability of naive T (T<sub>N</sub>) cells to mount an effector response correlates with TCR sensitivity for self-derived Ags, which can be quantified indirectly by measuring surface expression levels of CD5. Equivalent findings have not been reported previously in humans. We identified two discrete subsets of human CD8<sup>+</sup> T<sub>N</sub> cells, defined by the absence or presence of the chemokine receptor CXCR3. The more abundant CXCR3<sup>+</sup> T<sub>N</sub> cell subset displayed an effector-like transcriptional profile and expressed TCRs with physicochemical characteristics indicative of enhanced interactions with peptide-HLA class I Ags. Moreover, CXCR3<sup>+</sup> T<sub>N</sub> cells frequently produced IL-2 and TNF in response to nonspecific activation directly ex vivo and differentiated readily into Ag-specific effector cells in vitro. Comparative analyses further revealed that human CXCR3<sup>+</sup> T<sub>N</sub> cells were transcriptionally equivalent to murine CXCR3<sup>+</sup> T<sub>N</sub> cells, which expressed high levels of CD5. These findings provide support for the notion that effector differentiation is shaped by heterogeneity in the preimmune repertoire of human CD8<sup>+</sup> T cells.</p>
Data from: Intrinsic growth heterogeneity of mouse leukemia cells underlies differential susceptibility to a growth-inhibiting anticancer drug
<p>Cancer cell populations consist of phenotypically heterogeneous cells. Growing evidence suggests that pre-existing phenotypic differences among cancer cells correlate with differential susceptibility to anticancer drugs and eventually lead to a relapse. Such phenotypic differences can arise not only externally driven by the environmental heterogeneity around individual cells but also internally by the intrinsic fluctuation of cells. However, the quantitative characteristics of intrinsic phenotypic heterogeneity emerging even under constant environments and their relevance to drug susceptibility remain elusive. Here we employed a microfluidic device, mammalian mother machine, for studying the intrinsic heterogeneity of growth dynamics of mouse lymphocytic leukemia cells (L1210) across tens of generations. The generation time of this cancer cell line had a distribution with a long tail and a heritability across generations. We determined that a minority of cell lineages exist in a slow-cycling state for multiple generations. These slow-cycling cell lineages had a higher chance of survival than the fast-cycling lineages under continuous exposure to the anticancer drug Mitomycin C. This result suggests that heritable heterogeneity in cancer cells' growth in a population influences their susceptibility to anticancer drugs.</p>
Reproducible in-silico omics analyses - GSE37703: Differential analysis of HOXA1 in adult cells dataset
<p>GSE37703: Differential analysis of HOXA1 in adult cells at isoform resolution by RNA-Seq’ for quantification by Kallisto and differential abundance with Sleuth dataset used for the "Reproducible in-silico omics analyses across clouds and clusters" paper.</p>
Datasets associated with the manuscript "Differential detection workflows for multi-sample single-cell RNA-seq data"
<p>In this Zenodo repository, we share the data that is required to reproduce all the analyses from our publication "Differential detection workflows for multi-sample single-cell RNA-seq data".</p> <p>This repository includes all* input data, intermediate results and final outputs that are represented in our manuscript. For a more elaborate description of the data, we refer to the companion GitHub. https://github.com/statOmics/DD_benchmarks for the benchmarks and https://github.com/statOmics/DD_cases for the case studies, respectively.</p>
Neuroblastoma cell lines display heterogeneity in differentiation responses
<p>Underlying and extended data for the manuscript "Neuroblastoma cell lines display heterogeneity in differentiation responses", Ferguson et al (2024). Includes Underlying data for Figures 2A-C and Figures 3A-D, and Extended data - Table S1: qRT-PCR primer sequences, Table S2 - List of genes in clusters identified in [7] (Table S2 added after version 1).</p>
INFLAMeR: a machine learning algorithm based on large-scale perturbation screening identified new lncRNAs regulating differentiation and survival of leukaemia cells
Open the record for dataset details and reuse information.
Data supporting 'Small molecule and cell contact-inducible systems for controlling expression and differentiation in stem cells'
<p>Data supporting Soliman et al. 2024. Manuscript describes data collection practices and experimental design.</p>
Rapid and Accurate Identification of Stem Cell Differentiation Stages via SERS and Convolutional Neural Networks
<p><a name="OLE_LINK2"></a><span>Monitoring the transition of cell states during induced pluripotent stem cell (iPSC) differentiation is crucial for clinical medicine and basic research. However, both identification category and prediction accuracy need further improvement. Here, we propose a method combining Surface-Enhanced Raman spectroscopy (SERS) with convolutional neural networks (CNN) to precisely identify and distinguish cell states during stem cell differentiation. First, mitochondria-targeted probes were synthesized by combining AuNRs and mitochondrial localization signal (MLS) peptides to obtain effective and stable SERS spectra signals at various stages of cell differentiation. Then, the SERS spectra served as input datasets, and their distinctive features were learned and distinguished by CNN. As a result, rapid and accurate identification of six different cell states, including the embryoid body (EB) stage, was successfully achieved throughout the stem cell differentiation process with an impressive prediction accuracy of 98.5%. Furthermore, the impact of different spectral feature peaks on the identification results was investigated, which provides a valuable reference for selecting appropriate spectral bands to identify cell states. This is also beneficial for shortening the spectral acquisition region to enhance spectral acquisition speed. These results suggest the potential for SERS-CNN models in quality monitoring of stem cells, advancing the practical applications of stem cells.</span></p>
Host cell maturation modulates parasite invasion and sexual differentiation in Plasmodium.
<p>Raw expression counts data is provided along with code needed to analyse the scRNA-seq data presented in the publication "Host cell maturation modulates parasite invasion and sexual differentiation in Plasmodium."</p>
Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022
<p>Input data for Differential NicheNet analysis performed in the liver atlas paper Guilliams et al., Cell 2022</p> <p>See https://github.com/saeyslab/NicheNet_LiverCellAtlas and https://www.sciencedirect.com/science/article/pii/S0092867421014811</p>
Supplementary materials of Brain Extract of Subacute Traumatic Brain Injury Promotes Neuronal Differentiation of Human Neural Stem Cells Via Autophagy
<p>Figure S1: Characterization of hNSCs. In proliferate medium, the embryo derived hNSCs could form the neurospheres (A). Markers of NSCs (NES, SOX2, SOX1) were detected (B). The SOX2<sup>+</sup> cells accounted for >95% of all cells (C). Bar scale: 60μm;</p> <p>Figure S2: The proliferation of hNSCs in TBI brain extracts with different phases. Differentiated hNSCs could be labeled with EdU in TBI brain extracts with different phases (A). Ratio of EdU<sup>+</sup> cells was decreased with the progression of days post-injury (B). Bar scale: 75μm; ****: P<0.0001;</p> <p>Figure S3: The GO annotations and KEGG pathway analysis of different expressed pro-teins in acute brain extract and subacute brain extract;</p> <p>Table S1: The protein profiles of brain extract in acute phase and subacute phase after TBI.</p>
Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia
<p>This dataset supports the Cell Reports publication entitled '<em>Optogenetic activation of striatal D1/D2 medium spiny neurons differentially engages downstream connected areas beyond the basal ganglia</em>' (https://doi.org/10.1016/j.celrep.2021.110161). Please refer to this publication for detailed information. </p> <p>The dataset contains functional (GE-BOLD) and anatomical (T1-weighted) scans of a total of 34 subjects (Cre-mouse lines Drd1-Cre, Drd2-Cre, A2A-Cre, and wildtype mice) in NIFTI format, multiplied by 10. The 'StimulationProtocol' text file specifies the precise onset (in seconds) and duration (in seconds) of the optogenetic stimulation during a 480 seconds functional scan. The 'SubjectDetails' file lists the subject IDs, their gender, their genotype, the number of functional scans, and whether they have an associated anatomical scan.</p>
Sequence tracks of Ago2 Neural stem cells and differentiated neurons from single-cells- Related to Fig. 5
<p>Single neural stem cells were isolated from the Hippocampus of newborn mice generated from a hybrid cross. Some of these cells were differentiated In vitro and either the NSC or differentiated neurons were lysed and underwent a reverse transcription. The newly formed cDNA was used as a template to amplify expressed Ago2 transcript which was then sent off for Sanger sequencing. A SNP located within the exon was used to determine whether the transcript from that cell was generated from the maternal or paternal allele.</p>
CD8+ T cell differentiation status correlates with the feasibility of sustained unresponsiveness following oral immunotherapy
<p>While food allergy oral immunotherapy (OIT) can provide safe and effective desensitization (DS), the immune mechanisms underlying development of sustained unresponsiveness (SU) following a period of avoidance are largely unknown. We compared high dimensional immunophenotypes of innate and adaptive immune cell subsets of participants in a phase 2 randomized, controlled, peanut OIT trial who achieved SU vs. DS (no vs. with allergic reactions upon food challenge after a withdrawal period; n=21 vs. 30 respectively among total 120 intent-to-treat participants). Lower frequencies of naïve CD8<sup>+</sup> T cells and terminally differentiated CD57+ CD8<sup>+</sup> T cell subsets at baseline (pre-OIT) were highly associated with SU. Frequency of naïve CD8<sup>+</sup> T cells showed a significant positive correlation with peanut- and Ara h 2-specific IgE at baseline. Higher frequencies of IL-4<sup>+</sup> and IFNg<sup>+</sup> CD8<sup>+</sup> T cells post-OIT were negatively correlated with SU. Our findings provide compelling evidence that an immune signature consisting of certain CD8<sup>+</sup> T cell subset frequencies is predictive of SU following OIT.</p>
Datasets accompanying "Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing"
<p>Datasets include two seurat objects: one with all unfiltered cells and raw expression data (seu_unfiltered.rds) and one dataset with normalised expression and latest annotations (differentiation_object_latest.rds). Additionally, a single-cell object containing post-(py)SCENIC analysis is added (ipsc_scenic.h5ad).</p>
Data from: Drosophila medulla neuroblast termination via apoptosis, differentiation and gliogenic switch is scheduled by the depletion of the neuroepithelial stem cell pool
<p>The brain is consisted of diverse neurons arising from a limited number of neural stem cells. <em>Drosophila</em> neural stem cells called neuroblasts (NBs) produces specific neural lineages of various lineage sizes depending on their location in the brain. In the <em>Drosophila</em> visual processing centre - the optic lobes (OLs), medulla NBs derived from the neuroepithelium (NE) give rise to neurons and glia cells of the medulla cortex. The timing and the mechanisms responsible for the cessation of medulla NBs are so far not known. In this study, we show that the termination of medulla NBs during early pupal development is determined by the exhaustion of the NE stem cell pool. Hence, altering NE-NB transition during larval neurogenesis disrupts the timely termination of medulla NBs. Medulla NBs terminate neurogenesis via a combination of apoptosis, terminal symmetric division via Prospero, and a switch to gliogenesis via Glial Cell Missing (Gcm), however, these processes occur independently of each other. We also show that temporal progression of the medulla NBs is mostly not required for their termination. As the <em>Drosophila</em> OL shares a similar mode of division with mammalian neurogenesis, understanding when and how these progenitors cease proliferation during development can have important implications for mammalian brain size determination and regulation of its overall function.</p>
Single cell multiomic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients
<p>Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omic approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.</p>
Differential interference contrast (DIC) image of unstained living HepG2 human liver cancer cells
<p><strong>Introduction</strong></p> <p>This dataset is associated with our submission to Computers in Biology and Medicine, titled "Accurate Detection and Instance Segmentation of Unstained Living Adherent Cells in Differential Interference Contrast Images". The submission number for this manuscript is CIBM-D-23-09623R1.</p> <p><strong>Authors</strong>: Fei Pan, Yutong Wu, Kangning Cui, Shuxun Chen, Yanfang Li, Yaofang Liu, Adnan Shakoor, Han Zhao, Beijia Lu, Shaohua Zhi, Raymond Hon-Fu Chan, Dong Sun</p> <p><strong>Dataset Description</strong></p> <p>Our dataset comprises 520 differential interference contrast (DIC) images of 12,198 unstained HepG2 human liver cancer cells, each with a corresponding fluorescence image stained with calcein acetoxymethyl (AM), ensuring high-quality ground-truth annotations. Unique in addressing the multi-state nature of adherent cells commonly seen in wet labs, it includes both healthy and unhealthy cells in a single image, providing a valuable resource for studying multi-state cell detection and instance segmentation.<br>Citation</p> <p>We kindly request that researchers who use this dataset cite both our paper and this dataset. This will help acknowledge the work and facilitate further advancements in the field.</p> <p><br><strong>Please cite as follows:</strong></p> <p><strong>Paper:</strong><br>Pan, F., Wu, Y., Cui, K., Chen, S., Li, Y., Liu, Y., Shakoor, A., Zhao, H., Lu, B., Zhi, S., Chan, R. H.-F., & Sun, D. "Accurate detection and instance segmentation of unstained living adherent cells in differential interference contrast images,” <em>Computers in Biology and Medicine</em>, vol. 182, p. 109151, Nov. 2024, doi: 10/g5p9d8.</p> <p><strong>Dataset:</strong><br>Pan, F., Chen, S., Li, Y., Shakoor, A., Zhao, H., & Sun, D. (2024). Differential interference contrast (DIC) image of unstained living HepG2 human liver cancer cells. Zenodo. </p> <p>Thank you for your interest and support in our work. We look forward to seeing the innovative research that this dataset will enable.</p> <p> </p> <p> </p>
Chromatin regulation by Histone H4 acetylation at Lysine 16 during cell death and differentiation in the myeloid compartment
<p>Histone H4 acetylation at Lysine 16 (H4K16ac) is a key epigenetic mark involved in gene regulation, DNA repair and chromatin remodeling, and though it is known to be essential for embryonic development, its role during adult life is still poorly understood. Here we show that this lysine is massively hyperacetylated in peripheral neutrophils. Genome-wide mapping of H4K16ac in terminally differentiated blood cells, along with functional experiments, supported a role for this histone post-translational modification in the regulation of cell differentiation and apoptosis in the hematopoietic system. Furthermore, in neutrophils, H4K16ac was enriched at specific DNA repeats. These DNA regions presented an accessible chromatin conformation and were associated with the cleavage sites that generate the 50 kb DNA fragments during the first stages of programmed cell death. Our results thus suggest that H4K16ac plays a dual role in myeloid cells as it not only regulates differentiation and apoptosis, but it also exhibits a non-canonical structural role in poising chromatin for cleavage at an early stage of neutrophil cell death.</p> <p> </p>
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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.