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15 results for “neuronal communication”
Data for Altered Glia-Neuron Communication in Alzheimer's Disease Affects WNT, p53, and NFkB Signaling Determined by snRNA-seq
<p><strong>data.tar.gz contains all files from the data directory associated with the 230313_TS_CCCinHumanAD GitHub project and includes the following:</strong></p><ul><li><strong>CellRangerCounts/</strong><ul><li><strong>GSE157827/</strong><ul><li><strong>post_soupX/ : </strong>contains 21 directories for 21 samples, which each contain 3 files obtained from ambient RNA removal with soupX. Below is a representative example, but this repo contains 1 directory per sample:<ul><li><strong>SAMN16100290_S01_AD/</strong><ul><li><strong>barcodes.tsv</strong></li><li><strong>genes.tsv</strong></li><li><strong>matrix.mtx</strong></li></ul></li></ul></li><li><strong>pre_soupX/ : </strong>contains 21 directories for 21 samples, which each contain 2 files obtained from Cell Ranger after aligning fastq files to the reference genome. Below is a representative example, but this repo contains 1 directory per sample:<ul><li><strong>SAMN16100290_S01_AD/</strong><ul><li><strong>filtered_feature_ bc_matrix.h5</strong></li><li><strong>Raw_feature_bc_matrix.h5</strong></li></ul></li></ul></li></ul></li><li><strong>GSE174367/ : </strong>contains 19 directories for 19 samples, which contain 3 files each from Cell Ranger alignment of fastq files to the reference genome. Below is a representative example, but this repo contains 1 directory per sample:<ul><li><strong>SAMN19128610_S1_CTRL/</strong><ul><li><strong>barcodes.tsv</strong></li><li><strong>genes.tsv</strong></li><li><strong>Matrix.mtx</strong></li></ul></li></ul></li></ul></li><li><strong>ccc/</strong><ul><li><strong>nichenet_grn/</strong><ul><li><strong>gr_network_human_21122021.rds : </strong>accessed in October 2023, gene regulation network – gene regulatory information from MultiNicheNet</li><li><strong>ligand_tf_matrix_nsga2r_final.rds: </strong>accessed in October 2023, ligand tf matrix for signaling path determination from MultiNicheNet</li><li><strong>signaling_network_human_21122021.rds : </strong>accessed in October 2023, signaling network – protein-protein interaction information from MultiNicheNet</li><li><strong>weighted_networks_nsga2r_final.rds : </strong>accessed in October 2023, networks weighted by literature evidence from MultiNicheNet</li></ul></li><li><strong>nichenet_prior/</strong><ul><li><strong>ligand_target_matrix.rds : </strong>accessed in April 2023, ligand to target matrix from NicheNet</li><li><strong>lr_network.rds : </strong>accessed in April 2023, ligand-receptor matrix from NicheNet</li></ul></li><li><strong>nichenet_v2_prior/</strong><ul><li><strong>ligand_target_matrix_nsga2r_final.rds : </strong>accessed in June 2023, ligand to target matrix from MultiNicheNet used to predict target genes.</li><li><strong>lr_network_human_21122021.rds : </strong>accessed in June 2023, ligand-receptor matrix from MultiNicheNet used to predict ligand-receptor pairs.</li></ul></li><li><strong>geo_multinichenet_output.rds </strong>: MultiNicheNet output for Morabito et al., 2021 data</li><li><strong>geo_signaling_igraph_objects.rds </strong>: list of igraph objects for 17 overlapping LRTs and their signaling mediators in the Morabito et al., 2021 dataset. </li><li><strong>gse_multinichenet_output.rds</strong> : MultiNicheNet output for Lau et al., 2020 data</li><li><strong>gse_signaling_igraph_objects.rds</strong> : list of igraph objects for 17 overlapping LRTs and their signaling mediators in the Lau et al., 2020 dataset </li></ul></li><li><strong>seurat_preprocessing/</strong><ul><li><strong>geo_filtered_seurat.rds : </strong>merged and filtered seurat object of Morabito et al., 2021 data</li><li><strong>geo_integrated_seurat.rds :</strong> seurat object integrated using harmony of Morabito et al., 2021 data</li><li><strong>geo_clustered_seurat.rds : </strong>clustered seurat object of Morabito et al., 2021 data</li><li><strong>geo_processed_seurat.rds : </strong>processed seurat object with final cell type assignments at specified resolution of Morabito et al., 2021 data</li><li><strong>gse_filtered_seurat.rds : </strong>merged and filtered seurat object of Lau et al., 2020 data</li><li><strong>gse_integrated_seurat.rds : </strong>seurat object integrated using harmony of Lau et al., 2020 data</li><li><strong>gse_clustered_seurat.rds :</strong> clustered seurat object of Lau et al., 2020 data</li><li><strong>gse_processed_seurat.rds : </strong>processed seurat object with final cell type assignments at specified resolution of Lau et al., 2020 data </li></ul></li></ul>
Data for Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points
<p>processed_data.tar.gz contains all files from the data directory associated with the 230418_TS_AgingCCC GitHub project and includes the following:</p> <ul> <li> <p>CellRangerCounts/</p> </li> <ul> <li> <p>post_soupX/ : contains 12 directories for 12 samples, which each contain 3 files obtained from ambient RNA removal with soupX. Below is a representative example, but the post_soupX directory contains one directory for each of the 12 samples:</p> </li> <ul> <li> <p>S01_6m_AD/</p> </li> <ul> <li> <p>barcodes.tsv</p> </li> <li> <p>genes.tsv</p> </li> <li> <p>matrix.mtx</p> </li> </ul> </ul> <li> <p>pre_soupX/ : contains 12 directories for 12 samples, which each contain 2 files obtained from Cell Ranger after aligning fastq files to the reference genome. Below is a representative example, but this directory contains 1 directory for each individual sample:</p> </li> <ul> <li> <p>S01_6m_AD/outs/</p> </li> <ul> <li> <p>filtered_feature_ bc_matrix.h5</p> </li> <li> <p>raw_feature_bc_matrix.h5 </p> </li> </ul> </ul> </ul> <li> <p>PANDA_inputs/</p> </li> <ul> <li> <p>PANDA_exp_files_array.txt: Text files with files paths to expression inputs for PANDA gene regulatory networks.</p> </li> <li> <p>mm10_TFmotifs.txt: Mouse TF motif input for PANDA gene regulatory networks. Previously published in Whitlock et al. 2023 </p> </li> <li> <p>mm10_ppi.txt: Mouse protein-protein interaction information from SringDB input for PANDA gene regulatory networks. Previously published in Whitlock et al. 2023 </p> </li> </ul> <li> <p>ccc/</p> </li> <ul> <li> <p>nichenet_v2_prior/</p> </li> <ul> <li> <p>gr_network_mouse_21122021.rds : accessed in December 2023, gene regulation network – gene regulatory information from MultiNicheNet</p> </li> <li> <p>ligand_target_matrix_nsga2r_final_mouse.rds: accessed in December 2023, ligand target matrix for mouse from MultiNicheNet.</p> </li> <li> <p>ligand_tf_matrix_nsga2r_final_mouse.rds: accessed in December 2023, mouse ligand tf matrix for signaling path determination from MultiNicheNet</p> </li> <li> <p>lr_network_mouse_21122021.rds : accessed in December 2023, ligand-receptor matrix from MultiNicheNet</p> </li> <li> <p>signaling_network_mouse_21122021.rds : accessed in December 2023, signaling network – protein-protein interaction information from MultiNicheNet for mouse</p> </li> <li> <p>weighted_networks_nsga2r_final_mouse.rds : accessed in October 2023, networks weighted by literature evidence from MultiNicheNet for mouse</p> </li> </ul> <li> <p>multinichenet_output.rds : MultiNicheNet output for 3xTg-AD snRNA-seq data</p> </li> <li> <p>12m_signaling_igraph_objects.rds : list of igraph objects for 93 LRTs and their signaling mediators at 12 months</p> </li> <li> <p>6m_signaling_igraph_objects.rds :list of igraph objects for 2 LRTs and their signaling mediators at 6 months</p> </li> </ul> <li> <p>elisa/: CSV files of measured OD values for every ELISA.</p> </li> <ul> <li> <p>240319_ELISA_Ab40.csv: OD measurements for Ab40</p> </li> <li> <p>240319_ELISA_Ab42.csv: OD measurements for Ab42</p> </li> <li> <p>240319_ELISA_total_tau.csv: OD measurements for Total Tau</p> </li> </ul> <li> <p>panda/: PANDA gene regulatory networks for each time point and condition in excitatory and inhibitory neurons. Used for differential gene targeting.</p> </li> <ul> <li> <p>excitatory_neurons_AD12.Rdata</p> </li> <li> <p>excitatory_neurons_AD6.Rdata</p> </li> <li> <p>excitatory_neurons_WT12.Rdata</p> </li> <li> <p>excitatory_neurons_WT6.Rdata</p> </li> <li> <p>inhibitory_neurons_AD12.Rdata</p> </li> <li> <p>inhibitory_neurons_AD6.Rdata</p> </li> <li> <p>inhibitory_neurons_WT12.Rdata</p> </li> <li> <p>inhibitory_neurons_WT6.Rdata</p> </li> </ul> <li> <p>pseudobulk/: includes pseudo bulk matrices for every cell type which were used for downstream analyses. Each matrix also includes metadata information on condition and time point.</p> </li> <ul> <li> <p>all_counts_ls.rds: List of all the pseudo bulk matrices (below).</p> </li> <li> <p>astrocytes.rds: pseudobulk matrix for astrocytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>endothelial_cells.rds: pseudobulk matrix for endothelial cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>ependymal_cells.rds: pseudobulk matrix for ependymal cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>excitatory_neurons.rds: pseudobulk matrix for excitatory neurons. Include time point and condition information for downstream analyses.</p> </li> <li> <p>fibroblasts.rds: pseudobulk matrix for fibroblasts. Include time point and condition information for downstream analyses.</p> </li> <li> <p>inhibitory_neurons.rds: pseudobulk matrix for inhibitory neurons. Include time point and condition information for downstream analyses.</p> </li> <li> <p>meningeal_cells.rds: pseudobulk matrix for meningeal cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>microglia.rds: pseudobulk matrix for microglia. Include time point and condition information for downstream analyses.</p> </li> <li> <p>oligodendrocytes.rds: pseudobulk matrix for oligodendrocytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>opcs.rds: pseudobulk matrix for oligodendrocyte progenitor cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>percicytes.rds: pseudobulk matrix for pericytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>rgcs.rds: pseudobulk matrix for retinal ganglion cells. Include time point and condition information for downstream analyses.</p> </li> </ul> <li> <p>pseudobulk_split/: Includes pseudo bulk count matrices split by time point and condition. Used for input to PANDA for gene regulatory network construction.</p> </li> <ul> <li> <p>excitatory_neurons_AD12.Rdata</p> </li> <li> <p>excitatory_neurons_AD6.Rdata</p> </li> <li> <p>excitatory_neurons_WT12.Rdata</p> </li> <li> <p>excitatory_neurons_WT6.Rdata</p> </li> <li> <p>inhibitory_neurons_AD12.Rdata</p> </li> <li> <p>inhibitory_neurons_AD6.Rdata</p> </li> <li> <p>inhibitory_neurons_WT12.Rdata</p> </li> <li> <p>inhibitory_neurons_WT6.Rdata</p> </li> </ul> <li> <p>seurat_preprocessing/</p> </li> <ul> <li> <p>filtered_seurat.rds : merged and filtered seurat object</p> </li> <li> <p>integrated_seurat.rds : seurat object integrated using harmony</p> </li> <li> <p>clustered_seurat.rds : clustered seurat object</p> </li> <li> <p>processed_seurat.rds : processed seurat object with final cell type assignments at specified resolution</p> </li> </ul> </ul> <p> </p> <p>Raw data publicly available on GEO under series accession: GSE261596</p>
Data from: Exogenous α-synuclein hinders synaptic communication in cultured cortical primary rat neurons
Amyloid aggregates of the protein α-synuclein (αS) called Lewy Bodies (LB) and Lewy Neurites (LN) are the pathological hallmark of Parkinson's disease (PD) and other synucleinopathies. We have previously shown that high extracellular αS concentrations can be toxic to cells and that neurons take up αS. Here we aimed to get more insight into the toxicity mechanism associated with high extracellular αS concentrations (50-100 μM). High extracellular αS concentrations resulted in a reduction of the firing rate of the neuronal network by disrupting synaptic transmission, while the neuronal ability to fire action potentials was still intact. Furthermore, many cells developed αS deposits larger than 500 nm within five days, but otherwise appeared healthy. Synaptic dysfunction clearly occurred before the establishment of large intracellular deposits and neuronal death, suggesting that an excessive extracellular αS concentration caused synaptic failure and which later possibly contributed to neuronal death.
Data from: Exogenous α-synuclein hinders synaptic communication in cultured cortical primary rat neurons
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Highly Selective Brain-to-Gut Communication via Genetically-Defined Vagus Neurons
GEO Series GSE172411. Mus musculus. 383 samples. Type: Expression profiling by high throughput sequencing.
Neuronal–Glial Communication Perturbations in Murine SOD1G93A Spinal Cord
GEO Series GSE173524. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional architecture of synaptic communication delineates cortical GABAergic neuron identity
GEO Series GSE92522. Mus musculus. 46 samples. Type: Expression profiling by high throughput sequencing.
Transcription factor 4 regulates the interhemispheric midline remodeling through neuron–astroglia communications during corpus callosum formation
GEO Series GSE298404. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points
GEO Series GSE261596. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
MYC-Driven Gliosis Impairs Neuron-Glia Communication in Amyotrophic Lateral Sclerosis
GEO Series GSE275841. Mus musculus. 32 samples. Type: Expression profiling by high throughput sequencing.
Data from: Neuron-specific knockouts indicate the importance of network communication to Drosophila rhythmicity
<p>Animal circadian rhythms persist in constant darkness and are driven by intracellular transcription-translation feedback loops. Although these cellular oscillators communicate, isolated mammalian cellular clocks continue to tick away in darkness without intercellular communication. To investigate these issues in Drosophila, we assayed behavior as well as molecular rhythms within individual brain clock neurons while blocking communication within the ca. 150 neuron clock network. We also generated CRISPR-mediated neuron-specific circadian clock knockouts. The results point to two key clock neuron groups: loss of the clock within both regions but neither one alone has a strong behavioral phenotype in darkness; communication between these regions also contributes to circadian period determination. Under these dark conditions, the clock within one region persists without network communication. The clock within the famous PDF-expressing s-LNv neurons however was strongly dependent on network communication, likely because clock gene expression within these vulnerable sLNvs depends on neuronal firing or light</p>
Impairments of Neuro-muscular Communication in Motor-Neuron Disease: A Bio-Marker for Early and Personalised Diagnosis
ClinicalTrials.gov study NCT05663008. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Neuron-specific knockouts indicate the importance of network communication to Drosophila rhythmicity
Open the record for dataset details and reuse information.
The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson’s disease
GEO Series GSE152768. Homo sapiens. 27 samples. Type: Expression profiling by high throughput sequencing.
PRDM16 orchestrates neuron-vascular communication for angiogenesis during brain development
GEO Series GSE130802. Mus musculus. 4 samples. Type: Expression 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.