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2,143 results for “All Spinal Cord”
Atomic force microscopy indentation data of zebrafish spinal cord sections
<p>The HDF5 file was created using the Python package nanite. It contains 1132 raw atomic force microscopy (AFM) force-indentation curves of zebrafish spinal cord sections, the preprocessed curves, and the corresponding fits to the approach part. In addition, a manual rating was assigned to each force-indentation curve. The intended use of this dataset is the application of machine-learning approaches to quantify AFM data quality for biological tissues.</p>
Gene expression count data from human post-mortem spinal cord
<p>Gene expression data from human post-mortem tissue for three spinal cord sections (cervical, thoracic and lumbar) from amyotrophic lateral sclerosis (ALS) patients and non-neurological disease controls. RNA sequencing performed as part of the New York Genome Center ALS Consortium.</p> <p>Analysis workbooks: <a href="https://jackhump.github.io/ALS_SpinalCord_QTLs/">https://jackhump.github.io/ALS_SpinalCord_QTLs/</a> </p> <p>Preprint describing results: <a href="https://www.medrxiv.org/content/10.1101/2021.08.31.21262682v1">https://www.medrxiv.org/content/10.1101/2021.08.31.21262682v1</a> </p> <p><strong>Sample sizes:</strong></p> <table align="left"> <tbody> <tr> <td> <p><strong>Region</strong></p> </td> <td> <p><strong>Control</strong></p> </td> <td> <p><strong>ALS</strong></p> </td> </tr> <tr> <td> <p>Cervical</p> </td> <td> <p>35</p> </td> <td> <p>139</p> </td> </tr> <tr> <td> <p>Thoracic </p> </td> <td> <p>10</p> </td> <td> <p>42</p> </td> </tr> <tr> <td> <p>Lumbar</p> </td> <td> <p>32</p> </td> <td> <p>122</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p><strong>Library preparation</strong></p> <p>RNA was extracted from flash-frozen postmortem tissue using TRIzol (Thermo Fisher Scientific) chloroform, followed by column purification (RNeasy Minikit, QIAGEN). RNA integrity number (RIN) was assessed on a Bioanalyzer (Agilent Technologies). RNA-Seq libraries were prepared from 500ng total RNA using the KAPA Stranded RNA-Seq Kit with RiboErase (KAPA Biosystems) for rRNA depletion and Illumina-compatible indexes (NEXTflex RNA-Seq Barcodes, NOVA-512915, PerkinElmer, and IDT for Illumina TruSeq UD Indexes, 20022370). Pooled libraries (average insert size: 375 bp) passing the quality criteria were sequenced either on an Illumina HiSeq 2500 (125 bp paired end) or an Illumina NovaSeq (100 bp paired-end). The samples had a median sequencing depth of 42 million read pairs, with a range between 16 and 167 million read pairs.</p> <p><strong>Data processing</strong></p> <p>Samples were uniformly processed using RAPiD-nf, an efficient RNA-Seq processing pipeline implemented in the NextFlow framework. Following adapter trimming with Trimmomatic (version 0.36), all samples were aligned to the hg38 build (GRCh38.primary_assembly) of the human reference genome using STAR (2.7.2a), with indexes created from GENCODE, version 30. Gene expression was quantified using RSEM (1.3.1) using GENCODE v30. Quality control was performed using SAMtools and Picard, and the results were collated using MultiQC. Various technical metrics for sequencing quality control are provided in the metadata. Estimated read counts and normalised transcripts per million (TPM) matrices provided for each tissue.</p> <p><strong>Provided data:</strong></p> <p><em>gencode.v30.gene_meta.tsv.gz</em> - tab separated table with columns "genename", the HGNC gene symbol, and "geneid" the Ensembl ID, as set in the GENCODE v30 comprehensive annotation.</p> <p>For {tissue} in Cervical_Spinal_Cord, Thoracic_Spinal_Cord, Lumbar_Spinal_Cord:</p> <p><em>{tissue}_metadata.tsv.gz </em>- metadata describing each sample. Each row describes a sample. Descriptions of each column below.</p> <p><em>{tissue}_gene_tpm.tsv.gz</em> - the normalised TPM values from RSEM for all 58,884 genes in GENCODE v30. Each row describes a gene and each column describes a sample.</p> <p><em>{tissue}_gene_counts.tsv.gz</em> - the estimated read counts from RSEM for all 58,884 genes in GENCODE v30. Each row describes a gene and each column describes a sample.</p> <p><strong>Metadata Column Description</strong></p> <p><em>rna_id</em> - de-identified sample ID for each unique RNA-seq sample</p> <p><em>dna_id</em> - de-identified donor ID for each patient enrolled in the study</p> <p><em>site_id</em> - de-identified site name for each contributing site</p> <p><em>tissue</em> - name of tissue/region</p> <p><em>age_rounded</em> - age at death, rounded to nearest decade</p> <p><em>sex</em> - biological sex of donor</p> <p><em>subject_group</em> - long form disease group</p> <p><em>disease</em> - short form disease group</p> <p><em>site_of_motor_onset </em>- for ALS donors, where did symptoms start?</p> <p><em>disease_duration</em> - for ALS donors, how long did donor live with disease? </p> <p><em>mutations </em>- any known ALS gene mutations</p> <p><em>library_prep</em> - type of library preparation method used</p> <p><em>seq_platform </em>- sequencing platform used for sequencing</p> <p><em>rin</em> - RNA integrity number, 0-10</p> <p><em>c9orf72_repeat_size</em> - estimated C9orf72 repeat expansion size</p> <p><em>gPC1 - gPC5 </em>- principal component of genetic ancestry from whole genome sequencing</p> <p>Remaining metadata columns are from Picard - see here: <a href="http://broadinstitute.github.io/picard/picard-metric-definitions.html#RnaSeqMetrics">http://broadinstitute.github.io/picard/picard-metric-definitions.html#RnaSeqMetrics</a> </p> <p> </p>
Flow cytometry of mesenteric lymph nodes, small and large intestinal lamina propria, and spinal cord cells from fibre-rich and fiber-free diet-fed gnotobiotic mice at baseline and after experimental autoimmune encephalomyelitis (EAE) induction
<p>We perform profiling of different immune cell populations in the small (SILP) and large intestine lamina propria (CLP), mesenteric lymph nodes (MLN) and spinal cords (SC). We are specifically interested to evaluate the impact of dietary fiber deprivation followed by mucus erosion on the immune cell profiles of T helper cells (Th cells, T cell population) of gnotobiotic mice fed a fiber-rich (FR) or fiber-free (FF) diet. This dataset aims to assess the impact of microbiome and diet on disease course in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis, EAE) via T cell populations. Mice are either germ-free or colonized by intragastric gavage with a defined variation of a 14-member synthetic human gut microbiome (doi: 10.1016/j.cell.2016.10.043 and 10.1016/j.xpro.2021.100607): SM01 (Akkermansia muciniphila monocolonisation), SM03 (Bacteroides caccae, Bacteroides thetaiotaomicron, Barnesiella intestinihominis), SM04 (B. caccae, B. thetaiotaomicron, B. intestinihominis, A. muciniphila), SM12 (full community except mucin-specialists B. intestinihominis and A. muciniphila), SM13 (full community except mucin specialist A. muciniphila), or SM14 (full community: Roseburia intestinalis, Faecalibacterium prausnitzii, Marvinbryantia formatexigens, Collinsella aerofaciens, Desulfovibrio piger, B. caccae, B. thetaiotaomicron, Bacteroides ovatus, Bacteroides uniformis, B. intestinihominis, Eubacterium rectale, Clostridium symbiosum, Escherichia coli, and A. muciniphila). At age 5 to 8 weeks, mice were colonized with SM combinations while fed an FR diet. Mice were either maintained on an FR diet or switched to an FF diet at 5 days after initial colonization, until the end of experiment. Baseline samples were collected 20 days following the diet switch. Otherwise, EAE induction was performed 15 days after the diet switch and samples were collected 30 days after the induction.</p>
Full summary statistics of mixQTL for GTEx v8 Brain_Spinal_cord_cervical_c-1
The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.
Accelerated cell divisions drive the outgrowth of the regenerating spinal cord in axolotls - Supplementary file 1
<p>Tiff stack of individual high-resolution images that are shown in Figure 1 – figure supplement 1 (<a href="http://dx.doi.org/10.5281/zenodo.59817">http://dx.doi.org/10.5281/zenodo.59817</a>). It can be opened with Fiji or ImageJ.</p> <p>For details see:</p> <p>Rost, F, Albors, AR, Mazurov, V, Brusch, L, Deutsch, A, Tanaka, EM, Chara, O. 2016. Accelerated cell divisions drive the outgrowth of the regenerating spinal cord in axolotls. <em>bioRxiv</em> 67785. doi: <a href="http://dx.doi.org/10.1101/067785">10.1101/067785</a>.</p>
First-in-human study of epidural spinal cord stimulation in individuals with spinal muscular atrophy
<p>Data from the paper: First-in-human study of epidural spinal cord stimulation in individuals with spinal muscular atrophy, Nature Medicine 2024</p>
Genes regulated by CARTp/GPR160 in the dorsal horn of the spinal cord
<p><span>Analysis of the dorsal horn spinal cord (DH-SC) after an intrathecal injection of CARTp or CARTp with a neutralizing GPR160 antibody after 1hr. Results provide insight into genes regulated by CARTp/GPR160-induced behavioral hypersensitivities in the DH-SC.</span></p>
Diet-microbiome interactions following spinal cord injury in mice
<p>Here, we performed 16S (V3-V4) rRNA sequencing of the stool microbiome in mice following spinal cord injury, with or without a dietary fiber intervention. Provided here are two .zip files containing the downstream analyses of two independent cohorts (both experimentally and in sequencing/analysis), as performed by Zymo, Inc through their Microbiomics platform. Each .zip file contains a "Report" HTML file which summarizes key findings. All underlying data for each analysis are included in sub folders, inclusive of taxonomic composition and various diversity measurements. Sequences used in these analyses have been deposited into the NCBI SRA database under accession #PRJNA1119045.</p>
Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury
<p>We show that persons with spinal cord injury (SCI) retain decodable neural correlates of attempted arm and hand movements. We investigated hand open, palmar grasp, lateral grasp, pronation, and supination in 10 persons with cervical SCI. Discriminative movement information was provided by the time-domain of low-frequency electroencephalography (EEG) signals. Based on these signals, we obtained a maximum average classification accuracy of 45% (chance level was 20%) with respect to the five investigated classes. Pattern analysis indicates central motor areas as the origin of the discriminative signals. Furthermore, we introduce a proof-of-concept to classify movement attempts online in a closed loop, and tested it on a person with cervical SCI. We achieved here a modest classification performance of 68.4% with respect to palmar grasp vs hand open (chance level 50%).</p>
Full expression and splicing QTL summary statistics for three human spinal cord segments
<p>This dataset is part of the manuscript: <strong>"Integrative genetic analysis of the amyotrophic lateral sclerosis spinal cord implicates glial activation and suggests new risk genes</strong>" by Jack Humphrey, et al.</p> <p>The files below contain nominal and permuted quantitative trait loci (QTL) associations between common genetic variants derived from whole genome sequencing and either gene expression or splicing phenotypes generated from RNA-seq of post-mortem spinal cord sections. All QTLs were mapped with TensorQTL.</p> <p>Nominal association files are coordinate sorted, bgzip-compressed and tabix-indexed tab-separated variable files. Top association files are gzip-compressed tab-separated variable files.</p> <p>Sample sizes for each dataset are as follows:</p> <p>Cervical spinal cord n = 216.</p> <p>Lumbar spinal cord n = 197.</p> <p>Thoracic spinal cord n = 68.</p> <p>Description of files:<br> CervicalSpinalCord_expression_peer30_gene.cis_qtl.txt.gz - <strong>Top per-gene </strong>eQTL summary statistics from cervical spinal cord <br> CervicalSpinalCord_expression_peer30_gene.cis_qtl_nominal_tabixed.tsv.gz - <strong>Full nominal</strong> eQTL summary statistics from cervical spinal cord <br> CervicalSpinalCord_splicing_peer15_cluster.cis_qtl.txt.gz - <strong>Top per-cluster </strong>sQTL summary statistics from cervical spinal cord<br> CervicalSpinalCord_splicing_peer15_gene.cis_qtl_nominal_tabixed.tsv.gz - <strong>Full nominal</strong> sQTL summary statistics from cervical spinal cord<br> LumbarSpinalCord_expression_peer30_gene.cis_qtl.txt.gz - <strong>Top per-gene </strong>eQTL summary statistics from lumbar spinal cord<br> LumbarSpinalCord_expression_peer30_gene.cis_qtl_nominal_tabixed.tsv.gz -<strong> Full nominal</strong> eQTL summary statistics from lumbar spinal cord<br> LumbarSpinalCord_splicing_peer10_cluster.cis_qtl.txt.gz - <strong>Top per-cluster </strong>sQTL summary statistics from lumbar spinal cord<br> LumbarSpinalCord_splicing_peer10_gene.cis_qtl_nominal_tabixed.tsv.gz - <strong>Full nominal</strong> sQTL summary statistics from lumbar spinal cord<br> ThoracicSpinalCord_expression_peer10_gene.cis_qtl.txt.gz - <strong>Top per-gene </strong>eQTL summary statistics from thoracic spinal cord<br> ThoracicSpinalCord_expression_peer10_gene.cis_qtl_nominal_tabixed.tsv.gz - <strong>Full nominal</strong> eQTL summary statistics from thoracic spinal cord<br> ThoracicSpinalCord_splicing_peer5_cluster.cis_qtl.txt.gz - <strong>Top per-cluster </strong>sQTL summary statistics from thoracic spinal cord<br> ThoracicSpinalCord_splicing_peer5_gene.cis_qtl_nominal_tabixed.tsv.gz - <strong>Full nominal</strong> sQTL summary statistics from thoracic spinal cord</p> <p>als_snps_maf0.01_alleles.tsv.gz<strong> - Allele information</strong> for all SNPs tested in the eQTL and sQTL analysis</p> <p>Table columns are formatted as follows:</p> <p>Nominal QTL results include all SNP-gene pairs tested using either a 1Mb window from each side of the transcription start site (TSS) of the gene (eQTLs) or 100kb either side of the middle of the splicing cluster (sQTLs). Table columns are formatted as follows:</p> <ul> <li>phenotype_id - ensembl ID of the gene tested (GENCODE v30) for eQTL, or the ID of the splice junction for sQTLs, splicing junction position, splicing cluster id, and gene Ensembl id (GENCODE v30),separated by a colon</li> <li>variant_id - SNP tested for association (rsid or chr:position:ref:alt)</li> <li>tss_distance - distance of the SNP to the gene transcription start site (TSS)</li> <li>maf - minor allele frequency in cohort</li> <li>ma_samples - number of samples carrying the minor allele</li> <li>ma_count - total number of minor alleles across individuals</li> <li>pval_nominal - nominal <em>P</em>-value from linear regression</li> <li>slope - slope of the linear regression</li> <li>slope_se - standard error of the slope</li> </ul> <p>Permuted QTL results include only the top SNP-gene association for each gene (eQTL) or cluster (sQTL). Table columns are formatted as follows:</p> <ul> <li>phenotype_id - ensembl ID of the gene tested (GENCODE v30), or the coordinates of the cluster, formatted as coordinate, splicing cluster id, and gene Ensembl id (GENCODE v30), separated by a colon</li> <li>num_var - total number of variants tested in <em>cis</em></li> <li>beta_shape1 - first parameter value of the fitted beta distribution</li> <li>beta_shape2 - second parameter value of the fitted beta distribution</li> <li>true_df - effective degrees of freedom the beta distribution approximation</li> <li>pval_true_df - empirical <em>P</em>-value for the beta distribution approximation</li> <li>variant_id - ID of the top variant (rsid or chr:position:ref:alt)</li> <li>tss_distance - distance of the SNP to the gene transcription start site (TSS)</li> <li>ma_samples - number of samples carrying the minor allele</li> <li>ma_count - total number of minor alleles across individuals</li> <li>maf -minor allele frequency in MiGA cohort</li> <li>ref_factor - flag indicating if the alternative allele is the minor allele in the cohort (1 if AF <= 0.5, -1 if not)</li> <li>pval_nominal - nominal <em>P</em>-value from linear regression</li> <li>slope - slope of the linear regression</li> <li>slope_se - standard error of the slope</li> <li>pval_perm - first permutation <em>P</em>-value directly obtained from the permutations with the direct method</li> <li>pval_beta - second permutation <em>P</em>-value obtained via beta approximation. This is the one to use for downstream analysis</li> <li>qval - Storey q-value derived from pval_beta (FDR adjusted)</li> <li>pval_nominal_threshold - nominal <em>P</em>-value threshold for calling a variant-gene pair significant for the gene</li> </ul> <p>Allele Information for each variant:</p> <ul> <li>CHROM - chromosome position of the variant</li> <li>POS - position of the variant in the chromosome</li> <li>REF - reference allele (GRCh38)</li> <li>ALT - alternative allele (this is the <strong>effect</strong> allele in the eQTL and sQTL analysis)</li> <li>ID - variant id (rsid or chr:position:ref:alt)</li> </ul>
Dysport® Treatment of Urinary Incontinence in Adults Subjects With Neurogenic Detrusor Overactivity (NDO) Due to Spinal Cord Injury or Multiple Sclerosis - Study 2
ClinicalTrials.gov study NCT02660359. IPD Sharing: YES. Countries: 16. Publications: 1.
Multimodal Exercises to Improve Leg Function After Spinal Cord Injury
ClinicalTrials.gov study NCT01740128. IPD Sharing: YES. Countries: 1. Publications: 2.
Spinal Cord Stimulation for Predominant Low Back Pain
ClinicalTrials.gov study NCT01697358. IPD Sharing: NO. Countries: 9. Publications: 3.
Neurogenic Detrusor Overactivity Following Spinal Cord Injury or Multiple Sclerosis
ClinicalTrials.gov study NCT01357980. IPD Sharing: YES. Countries: 5. Publications: 1.
Spinal Cord Stimulation in Spinal Muscular Atrophy
ClinicalTrials.gov study NCT05430113. IPD Sharing: YES. Countries: 1. Publications: 1.
Investigation of Brain Functional MRI as an Early Biomarker of Recovery in Individuals With Spinal Cord Injury
ClinicalTrials.gov study NCT03854214. IPD Sharing: YES. Countries: 1. Publications: 4.
Dysport® Treatment of Urinary Incontinence in Adults Subjects With Neurogenic Detrusor Overactivity (NDO) Due to Spinal Cord Injury or Multiple Sclerosis - Study 1
ClinicalTrials.gov study NCT02660138. IPD Sharing: YES. Countries: 10. Publications: 1.
Longitudinal stability of brain and spinal cord quantitative MRI measures
<p><strong>About: </strong>Tabular (CSV) files are generated by the Courtois Neuromod<a href="https://github.com/courtois-neuromod/anat-processing"> structural data processing workflow</a>. These files contain quantitative MRI metrics such as T1, MTsat, and MTR, in addition to fundamental diffusion tensor imaging indices like RD and FA derived from brain data. The results also encompass the same metrics for spinal cord imaging data, supplemented with additional metrics for spinal cord morphometry. For details regarding the raw data please visit <a href="https://www.cneuromod.ca">https://www.cneuromod.ca</a>. </p><p>Dataset provided for NeuroLibre preprint. Author repo: https://github.com/courtois-neuromod/anat-processing-paper NeuroLibre fork:https://github.com/roboneurolibre/anat-processing-paper</p><p>For details, please visit the corresponding <a href="https://github.com/neurolibre/neurolibre-reviews/issues/18">NeuroLibre technical screening.</a></p><p><a href="https://neurolibre.org"><strong>https://neurolibre.org</strong></a></p>
Datasets related to the manuscript 'Hypothalamic deep brain stimulation augments walking after spinal cord injury'
<p>The deposited datasets consist in the following:<br>Supplementary Table 1: All kinematics data and statistical analyses</p> <p>Supplementary Table 2: All differential analyses and statistics for the quantification of transcriptional activity (cFos) and spinal cord-projecting neurons (Rabies) from the contralesional (right) lateral hypothalamus (n = 3 per group).</p> <p> </p>
(Dataset) Analysis code for the paper "RF shimming in the cervical spinal cord at 7T"
Dataset provided for NeuroLibre preprint. Author repo: https://github.com/shimming-toolbox/rf-shimming-7t NeuroLibre fork:https://github.com/roboneurolibre/rf-shimming-7t <p>For details, please visit the corresponding <a href="https://github.com/neurolibre/neurolibre-reviews/issues/25">NeuroLibre technical screening.</a></p> <p><strong><a href="https://neurolibre.org" target="NeuroLibre">https://neurolibre.org</a></strong></p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.