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394 results for “oligodendrocyte”
Xiao et al, Oligodendrocyte Precursor Cells Sculpt the Visual System by Regulating Axonal Remodeling [Dataset]
<p>Raw data from the behavior and imaging experiments of Xiao et al., Nature Neuroscience 2022. For additional details about the acquisition of each part of the dataset, refer to the methods section of the paper. From this dataset, using the published code, all the figures relative to the imaging in the optic tectum can be generated and all the cumulative statistics for the behavioural assays run with Stytra recomputed.</p> <p> </p> <p><strong>Organisation of the dataset</strong></p> <p>This dataset is organised in the following subdirectories:<br> - <em>freely_swimming</em>: contains the data for the freely swimming experiments quantifying motor activity in the various ablated groups. It contains subfolders of groups, each of which contains the Stytra raw data directories for all fish of that group. Refer to `Stytra` and `bouter` documentation for further details about the files.<br> - <em>OMR</em>: contains the data for the quantification of OMR reflex across different spatial frequencies. It contains subfolders for the control and ablated group, each of which contains the Stytra raw data directories for all fish of that group.<br> - <em>receptive_field_imaging</em>: contains the imaging data for the receptive field estimation. Subfolders contains, for each individual fish (both ablated and controls are pooled in the same directory):<br> - stytra raw output from the experiment<br> - data_from_suite2p_unfiltered.h5: `flammkuchen`-loadable `.h5` file that contains the raw fluorescent trace<br> - anatomy.mask: `flammkuchen`-loadable mask file saved by the `pypra` tool that was used for segmenting the tectum, delimiting the region of the tectum<br> The folder contains an additional file, `manual_alignment_offsets.h5`, where the offsets of the manual morphing across fish were saved.</p>
ROSMAP meQTL Results for Oligodendrocytes with CpGs
<p>This dataset contains methylation quantitative trait loci (meQTL) results for the following study:</p> <p><strong><em>"regionalpcs improve discovery of DNA methylation associations with complex traits"</em></strong></p> <p>Tiffany Eulalio*<sup>1</sup>, Min Woo Sun<sup>1</sup>, Olivier Gevaert<sup>1</sup>, Michael D. Greicius<sup>2</sup>, Thomas J. Montine<sup>3</sup>, Daniel Nachun*‡<sup>3</sup>, Stephen B. Montgomery*‡<sup>1,3</sup></p> <p>‡ These authors contributed equally as senior authors</p> <p>* Corresponding authors: Tiffany Eulalio (<a href="mailto:eulalio@alumn.stanford.edu">eulalio@alumn.stanford.edu</a>), Daniel Nachun (<a href="mailto:dnachun@stanford.edu">dnachun@stanford.edu</a>), Stephen B. Montgomery (<a href="mailto:smontgom@stanford.edu">smontgom@stanford.edu</a>)</p> <p> Author affiliations:</p> <p>1. Department of Biomedical Data Science, Stanford University, Stanford, CA</p> <p>2. Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA</p> <p>3. Department of Pathology, Stanford University, Stanford, CA</p> <p> </p> <p><strong>Dataset description</strong>:</p> <p>This dataset contains QTL results generated from FastQTL, organized by region type (full gene, gene body, preTSS, and promoters) and summary types (averages and regional principal components).</p> <p><strong>Contents:</strong></p> <ul> <li><strong>Parquet tar files</strong>: These compressed archives contain output files in Parquet format from FastQTL, split by chromosome. <code>parquet1</code> includes chromosomes 1-10, and <code>parquet2</code> includes chromosomes 11-22.</li> <li><strong>cis_qtl_summary_stats.csv</strong>: Provides summary statistics for each phenotype-variant pair, including effect sizes, p-values, TSS distances, and additional details.</li> <li><strong>cis_qtl.signif_pairs.csv</strong>: Contains the significant QTL results identified by FastQTL.</li> <li><strong>cis_qtls.time_to_run.txt</strong>: Reports the running time for FastQTL analysis.</li> <li><strong>cis_qtls.cis_qtl.txt.gz</strong>: Contains comprehensive results for all cis QTLs.</li> </ul> <p>This dataset is intended to support replication and further exploration of QTL associations across different genomic regions and summary methods.</p>
ROSMAP meQTL Results for Oligodendrocytes with regionalpcs and averages
<p>This dataset contains methylation quantitative trait loci (meQTL) results for the following study:</p> <p><strong><em>"regionalpcs improve discovery of DNA methylation associations with complex traits"</em></strong></p> <p>Tiffany Eulalio*<sup>1</sup>, Min Woo Sun<sup>1</sup>, Olivier Gevaert<sup>1</sup>, Michael D. Greicius<sup>2</sup>, Thomas J. Montine<sup>3</sup>, Daniel Nachun*‡<sup>3</sup>, Stephen B. Montgomery*‡<sup>1,3</sup></p> <p>‡ These authors contributed equally as senior authors</p> <p>* Corresponding authors: Tiffany Eulalio (<a href="mailto:eulalio@alumn.stanford.edu">eulalio@alumn.stanford.edu</a>), Daniel Nachun (<a href="mailto:dnachun@stanford.edu">dnachun@stanford.edu</a>), Stephen B. Montgomery (<a href="mailto:smontgom@stanford.edu">smontgom@stanford.edu</a>)</p> <p> Author affiliations:</p> <p>1. Department of Biomedical Data Science, Stanford University, Stanford, CA</p> <p>2. Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA</p> <p>3. Department of Pathology, Stanford University, Stanford, CA</p> <p> </p> <p><strong>Dataset description</strong>:</p> <p>This dataset contains QTL results generated from FastQTL, organized by region type (full gene, gene body, preTSS, and promoters) and summary types (averages and regional principal components).</p> <p><strong>Contents:</strong></p> <ul> <li><strong>Parquet tar files</strong>: These compressed archives contain output files in Parquet format from FastQTL, split by chromosome. <code>parquet1</code> includes chromosomes 1-10, and <code>parquet2</code> includes chromosomes 11-22.</li> <li><strong>cis_qtl_summary_stats.csv</strong>: Provides summary statistics for each phenotype-variant pair, including effect sizes, p-values, TSS distances, and additional details.</li> <li><strong>cis_qtl.signif_pairs.csv</strong>: Contains the significant QTL results identified by FastQTL.</li> <li><strong>cis_qtls.time_to_run.txt</strong>: Reports the running time for FastQTL analysis.</li> <li><strong>cis_qtls.cis_qtl.txt.gz</strong>: Contains comprehensive results for all cis QTLs.</li> </ul> <p>This dataset is intended to support replication and further exploration of QTL associations across different genomic regions and summary methods.</p>
Myelin is repaired by constitutive differentiation of oligodendrocyte progenitors
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Parvalbumin expression in oligodendrocyte-like CG4 cells causes a reduction in mitochondrial volume, attenuation in reactive oxygen species production and a decrease in cell processes' length and branching
<p>Forebrain glial cells - ependymal cells and astrocytes -acquire upon injury- a “reactive” phenotype associated with parvalbumin (PV) upregulation. Since free radicals, e.g. reactive oxygen species (ROS) play a role in the pathogenesis of multiple sclerosis, and that PV-upregulation in glial cells is inversely correlated with the level of oxidative stress, we hypothesized that PV-upregulation might also protect oligodendrocytes by decreasing ROS production. Lentiviral transduction techniques allowed for PV overexpression in CG4 oligodendrocyte progenitor cells (OPCs). Depending on the growth medium CG4 cells can be maintained in an OPC-like state, or induced to differentiate into an oligodendrocyte (OLG)-like phenotype. While increased levels of PV had no effect on cell proliferation and invasiveness <em>in vitro</em>, PV decreased the mitochondria volume in CG4 cell bodies, as well as the mitochondrial density in CG4 processes in both OPC-like and OLG-like states. In line with the PV-induced global decrease in mitochondrial volume, elevated PV levels reduced transcript levels of mitochondrial transcription factors involved in mitochondria biogenesis. In differentiated PV-overexpressing CG4 cells with a decreased mitochondrial volume, UV-induced ROS production was lower than in control CG4 cells hinting towards a possible role of PV in counteracting oxidative stress. Unexpectedly, PV also decreased the length of processes in undifferentiated CG4 cells and moreover diminished branching of differentiated CG4 cell processes, strongly correlated with the decreased density of mitochondria in CG4 cell processes. Thus besides conferring a protective role against oxidative stress, PV in a cell autonomous fashion additionally affects process’ growth and branching in CG4 cells.</p>
Single-nucleus RNA-sequencing reveals oligodendrocytes and their progenitors as vulnerable cell types in prefrontal cortex and anterior cingulate of brains with Parkinson's disease
<p>Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson's disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from post-mortem control and PD brain tissue. We found a dramatic association of oligodendrocytes and oligodendrocyte precursor cells with PD-linked risk loci and reported several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria.</p>
A Study to Evaluate the Efficacy and Safety of Rozanolixizumab in Adult Participants With Myelin Oligodendrocyte Glycoprotein (MOG) Antibody-associated Disease (MOG-AD)
ClinicalTrials.gov study NCT05063162. IPD Sharing: YES. Countries: 21. Publications: 1.
Primary Chemotherapy by BCNU-TMZ Combination in Newly Diagnosed Anaplastic Oligodendrocytic Tumors: Phase II Trial With Translational Molecular Analysis
ClinicalTrials.gov study NCT04755023. IPD Sharing: NO. Countries: 1. Publications: 0.
Frequency of FCGR3A Gene Polymorphisms in Patients With Neuromyelitis Optica Spectrum Disorders, Anti-oligodendrocyte Myelin Protein Antibody Disease, and Multiple Sclerosis.
ClinicalTrials.gov study NCT06865274. IPD Sharing: NO. Countries: 1. Publications: 30.
Initial Clinical Presentation of Inflammatory Optic Neuritis Associated or Not With Autoantibodies Anti-Myelin-oligodendrocyte-glycoprotein
ClinicalTrials.gov study NCT03345537. IPD Sharing: NO. Countries: 1. Publications: 15.
Oligodendrocyte
Drawing uploaded to scidraw.io on: 26 May 2020
Data from: Loss of mTORC2 signaling in oligodendrocyte precursor cells delays myelination
Myelin abnormalities are increasingly being recognized as an important component of a number of neurologic developmental disorders. The integration of many signaling pathways and cell types are critical for correct myelinogenesis. The PI3-K and mechanistic target of rapamycin (mTOR) pathways have been found to play key roles. mTOR is found within two distinct complexes, mTORC1 and mTORC2. mTORC1 activity has been shown to play a major role during myelination, while the role of mTORC2 is not yet well understood. To determine the role of mTORC2 signaling in myelinogenesis, we generated a mouse lacking the critical mTORC2 component Rictor in oligodendrocyte precursors (OPCs). Targeted deletion of Rictor in these cells decreases and delays the expression of myelin related proteins and reduces the size of cerebral white matter tracts. This is developmentally manifest as a transient reduction in myelinated axon density and g-ratio. OPC cell number is reduced at birth without detectable change in proliferation with proportional reductions in mature oligodendrocyte number at P15. The total number of oligodendrocytes as well as extent of myelination, does improve over time. Adult conditional knock-out (CKO) animals do not demonstrate a behavioral phenotype likely due in part to preserved axonal conduction velocities. These data support and extend prior studies demonstrating an important but transient contribution of mTORC2 signaling to myelin development.
Mature Oligodendrocyte
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Oligodendrocyte progenitor cell
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The BHMT-Betaine methylation pathway epigenetically modulates oligodendrocyte maturation
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Data from: Loss of mTORC2 signaling in oligodendrocyte precursor cells delays myelination
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Role of fatty acid synthase in oligodendrocyte myelination
GEO Series GSE112725. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
Hdac3 Interaction with p300 Histone Acetyltransferase Regulates the Oligodendrocyte and Astrocyte Lineage Fate Switch
GEO Series GSE76412. Mus musculus; Rattus norvegicus. 6 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Oligodendrocyte differentiation alters tRNA modifications and codon-dependent mRNA decay [QuantM-seq II]
GEO Series GSE198271. Saccharomyces cerevisiae. 8 samples. Type: Non-coding RNA profiling by high throughput sequencing.
PAD2-mediated citrullination contributes to efficient oligodendrocyte differentiation and myelination
GEO Series GSE115929. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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.