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1,274 results for “disease models”
Data from: A qualitative analysis of an Aβ-monomer model with inflammation processes for Alzheimer's disease
<p>We introduce and study a new model for the progression of Alzheimer's disease incorporating the interactions of Aβ-monomers, oligomers, microglial cells and interleukins with neurons through different mechanisms such as protein polymerization, inflammation processes and neural stress reactions. In order to understand the complete interactions between these elements, we study a spatially-homogeneous simplified model that allows to determine the effect of key parameters such as degradation rates in the asymptotic behavior of the system and the stability of equilibriums. We observe that inflammation appears to be a crucial factor in the initiation and progression of Alzheimer's disease through a phenomenon of hysteresis, which means that there exists a critical threshold of initial concentration of interleukins that determines if the disease persists or not in the long term. These results give perspectives on possible anti-inflammatory treatments that could be applied to mitigate the progression of Alzheimer's disease. We also present numerical simulations that allow to observe the effect of initial inflammation and concentration of monomers in our model.</p>
Supplementary data: The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia in a xenotransplantation model of Alzheimer's disease
<p>Supplementary data for: The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia in a xenotransplantation model of Alzheimer’s disease. </p> <p>Supplementary_Table1_QC: Excel sheet containing QC metrics for the RNA-seq data and the other containing QC metrics for the ATAC-seq data. </p> <p>Supplementary_Table2_DEGs: Excel sheet containing DeSeq2 differential expression analysis results for the following comparisons: APOE2 vs APOE3, APOE4 vs APOE3, APOE4 vs APOE2, APOE-KO vs APOE3. </p> <p>Supplementary_Table3_MAGMA_geneset_analysis_res: CSV file containing MAGMA gene set analysis results using the differentially expressed genes (FDR < 0.05) for the comparisons outlined in Supplementary_Table2_DEGs and three independent AD GWAS. </p> <p>Supplementary_Table4_DARs: Excel sheet containing DeSeq2 differential accessibility analysis results for the following comparisons: APOE2 vs APOE3, APOE4 vs APOE3, APOE4 vs APOE2, APOE-KO vs APOE3. </p> <p>Supplementary_Table5_sLDSC_res.csv: CSV file containing s-LDSC results using the consensus set of ATAC-seq peaks with three brain disorder GWAS (Alzheimer's disease, autism spectrum disorder, and amyotrophic lateral sclerosis). </p> <p>Supplementary_Table6_WGCNA_clusterProfiler_pathway_enrichment.csv: CSV file containing pathway enrichment results using two WGCNA-identified modules that were significantly upregulated in APOE2-expressing microglia. </p> <p>Supplementary_Table7_homer_motifEnrichment_res.xlsx: Excel sheet containing Homer motif enrichment analysis results using top 100 peaks with increased and decreased chromatin accessibility for APOE2 vs APOE3, APOE4 vs APOE3, and APOE4 vs APOE2.</p>
Counterintuitive scaling between population abundance and local density: implications for modelling transmission of infectious diseases in bat populations
<p>1. Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density.</p> <p>2. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogenous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated.</p> <p>3. We collected a 13-month dataset of tree-roosting <i>Pteropus </i>spp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree-level measures of abundance and density – the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost-level, subplot-level, tree-level) are predictive of these local density dynamics.</p> <p>4. Roost-level features were not representative of tree-level abundance (bats per tree) or tree-level density (bats per m<sup>2</sup> or m<sup>3</sup>), with roost-level models explaining minimal variation in tree-level measures. Total roost abundance itself was either not a significant predictor (tree-level 3-D density) or only weakly predictive (tree-level abundance).</p> <p>5. This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree.</p> <p>6. Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.</p>
Hematopoietic Tumors in a Mouse Model of X-linked Chronic Granulomatous Disease after Lentiviral Vector-Mediated Gene Therapy
<p>Chronic granulomatous disease (CGD) is a rare inherited disorder due to loss-of-function mutations in genes encoding the NADPH oxidase subunits. Hematopoietic stem and progenitor cell (HSPC) gene therapy (GT) using regulated lentiviral vectors (LVs) has emerged as a promising therapeutic option for CGD patients. We performed non-clinical Good Laboratory Practice (GLP) and laboratory-grade studies to assess the safety and genotoxicity of LV targeting myeloid specific Gp91phox expression in X-linked chronic granulomatous disease (XCGD) mice. We found persistence of gene-corrected cells for up to 1 year, restoration of Gp91phox expression and NADPH oxidase activity in XCGD phagocytes, and reduced tissue inflammation after LV-mediated HSPC GT.<br> Although most of the mice showed no hematological or biochemical toxicity, a small subset of XCGD GT mice developed<br> T cell lymphoblastic lymphoma (2.94%) and myeloid leukemia (5.88%). No hematological malignancies were identified in C57BL/6 mice transplanted with transduced XCGD HSPCs. Integration pattern analysis revealed an oligoclonal composition with rare dominant clones harboring vector insertions near oncogenes in mice with tumors. Collectively, our data support the long-term efficacy of LV-mediated HSPC GT in XCGD mice and provide a safety warning because the chronic inflammatory XCGD background may contribute to oncogenesis.</p>
Processed FDG-PET data from: A computational model of neurodegeneration in Alzheimer's disease
<p>Disruption of mental functions in Alzheimer's disease (AD) and related disorders is accompanied by selective degeneration of brain regions. These regions comprise large-scale ensembles of cells organized into systems for mental functioning, however the relationship between clinical symptoms of dementia, patterns of neurodegeneration, and functional systems is not clear. We developed a model of the association between dementia symptoms and degenerative brain anatomy using F18-fluorodeoxyglucose (FDG) PET and dimensionality reduction techniques patients with AD. This data and code package contains preprocessed FDG-PET images from 423 subjects across the Alzheimer's disease spectrum and the MATLAB code to produce eigenbrains from this data.</p>
Modelling the genetic aetiology of complex disease: human-mouse conservation of noncoding features and disease-associated loci
<p>Understanding the genetic aetiology of loci associated with disease is crucial for developing preventative measures and effective treatments. Mouse models are used extensively to understand human pathobiology and mechanistic functions of disease-associated loci. However, the utility of mouse models is limited by evolutionary divergence in transcription regulation for pathways of interest. Here, we summarise the conservation of genomic (exonic and multi-cell regulatory) features and complex disease associated variant sites between humans and mice. Our results highlight the importance of understanding evolutionary divergence in transcription regulation when interpreting functional studies using mice as models for human disease variants.</p>
Source Data files for: Primary cilia and SHH signaling impairments in human and mouse models of Parkinson's disease
<p>Parkinson’s disease (PD) as a progressive neurodegenerative disorder arises from multiple genetic and environmental factors. However, underlying pathological mechanisms remain poorly understood. Using multiplexed single-cell transcriptomics, we analyze human neural precursor cells (hNPCs) from sporadic PD (sPD) patients. Alterations in gene expression appear in pathways related to primary cilia (PC). Accordingly, in these hiPSC-derived hNPCs and neurons, we observe a shortening of PC. Additionally, we detect a shortening of PC in <em>PINK1</em>-deficient human cellular and mouse models of familial PD. Furthermore, in sPD models, the shortening of PC is accompanied by an increased SHH signal transduction. Inhibition of this pathway rescues the alterations in PC morphology and mitochondrial dysfunction. Thus, increased SHH activity due to ciliary dysfunction is needed for the development of pathoetiological phenotypes observed in sPD, like mitochondrial dysfunction. In sum, altered PC function is part of early PD pathoetiology and inhibiting the overactive SHH signaling is a potential neuroprotective therapy.</p>
DYRK1a inhibitor mediated rescue of Drosophila models of Alzheimer's disease-Down Syndrome phenotypes
<p>Alzheimer's disease (AD) is the most common neurodegenerative disease which is becoming increasingly prevalent due to ageing populations resulting in huge social, economic, and health costs to the community. Despite the pathological processing of genes such as Amyloid Precursor Protein (APP) into Amyloid-b and Microtubule Associated Protein Tau (MAPT) gene, into hyperphosphorylated Tau tangles being known for decades, there remains no treatments to halt disease progression. One population with increased risk of AD are people with Down syndrome (DS), who have a 90% lifetime incidence of AD, due to trisomy of human chromosome 21 (HSA21) resulting in three copies of APP and other AD-associated genes, such as DYRK1A (Dual specificity tyrosine-phosphorylation-regulated kinase 1A) overexpression. This suggests that blocking DYRK1A might have therapeutic potential. However, it is still not clear to what extent DYRK1A overexpression by itself leads to AD-like phenotypes and how these compare to Tau and Amyloid-b mediated pathology. Likewise, it is still not known how effective a DYRK1A antagonist may be at preventing or improving any Tau, Amyloid-b and DYRK1a mediated phenotype. To address these outstanding questions, we characterised Drosophila models with targeted overexpression of human Tau, human Amyloid-b or the fly orthologue of DYRK1A, called minibrain (mnb). We found targeted overexpression of these AD-associated genes caused degeneration of photoreceptor neurons, shortened lifespan, as well as causing loss of locomotor performance, sleep, and memory. Treatment with the experimental DYRK1A inhibitor PST-001 decreased pathological phosphorylation of human Tau (at serine (S) 262). PST-001 reduced degeneration caused by human Tau, Amyloid-b or mnb lengthening lifespan as well as improving locomotion, sleep and memory loss caused by expression of these AD and DS genes. This demonstrated PST-001 effectiveness as a potential new therapeutic targeting AD and DS pathology.</p>
Raw output data from ColabFold modelling for the paper 'Interaction of C21ORF2 with a domain of NEK1 mutated in human diseases is vital for NEK1 function in human cells'
<p><strong>Raw output data from ColabFold modelling for the paper 'Interaction of C21ORF2 with a domain of NEK1 mutated in human diseases is vital for NEK1 function in human cells'</strong></p> <p><strong>File descriptions:</strong></p> <p><strong>NEK11160endC21ORF2_amber_2e60f_relaxed_rank_1_model_1_fixed.pdb</strong><br> ColabFold output PDB file - Rank 1 model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_relaxed_rank_2_model_2_fixed.pdb</strong><br> ColabFold output PDB file - Rank 2 model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_relaxed_rank_3_model_4_fixed.pdb</strong><br> ColabFold output PDB file - Rank 3 model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_relaxed_rank_4_model_3_fixed.pdb</strong><br> ColabFold output PDB file - Rank 4 model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_relaxed_rank_5_model_5_fixed.pdb</strong><br> ColabFold output PDB file - Rank 5 model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_coverage.png</strong><br> ColabFold output chart - MSA sequence coverage</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_PAE.png</strong><br> ColabFold output chart - PAE for each model</p> <p><strong>NEK11160endC21ORF2_amber_2e60f_plddt.png</strong><br> ColabFold output chart - predicted IDDT per position</p> <p><strong>Supplementary Excel file 1</strong><br> List of residues predicted to be involved in intermolecular interactions, and the type of interaction (based on PDB files for each models, generated using BIOVIA Discovery Studio 2021)</p>
The c-Abl inhibitor IkT-148009 therapeutically suppresses neurodegeneration in models of heritable and sporadic Parkinson's Disease
<p>Parkinson's Disease (PD) is the second most prevalent neurodegenerative disease of the central nervous system, with an estimated 5,000,000 cases worldwide. PD pathology is characterized by the accumulation of misfolded a-synuclein, which is thought to play a critical role in the etiopathogenesis of the disease. Animal models of PD suggest that activation of the Abelson Tyrosine Kinase, or c-Abl, plays an essential role in the initiation and progression of a-synuclein pathology and initiates processes leading to the degeneration of dopaminergic and non-dopaminergic neurons. Given the essential role of c-Abl in the disease, a proprietary c-Abl inhibitor library was developed to identify potent, orally bioavailable c-Abl inhibitors capable of crossing the blood-brain barrier based on pre-defined characteristics, leading to the discovery of IkT-148009. IkT-148009 is a selective, potent, brain-penetrant c-Abl inhibitor with a favorable toxicology profile that was analyzed for therapeutic potential in animal models of slowly progressive, a-synuclein-dependent disease. In models of both inherited and sporadic Parkinson's disease in the mouse, IkT-148009 suppressed c-Abl activation to baseline and substantially protected neurons from degeneration when administered therapeutically by once daily oral gavage beginning four weeks after disease initiation. Recovery of normal behavioral function in diseased mice occurred within 8 weeks of initiating treatment and occurred concomitantly with a substantial reduction of a-synuclein pathology in the brain. These disease-modifying outcomes in mice suggest IkT-148009 has the potential to be a disease-modifying therapy in human disease.</p>
Psoriatic arthritis disease subtypes are phenocopied in a novel humanized murine model of psoriasis and joint inflammation
<p><em><span>Data processing and analysis</span></em></p> <p><span>Data normalization, quality control, and analysis was conducted by the UPMC Hillman Cancer Bioinformatics Services. Following the GeoMX NGS pipeline (<span>sequencing saturation 92%±0.12% (mean±S.E.M)), t</span>he resulting read count matrix was passed through robust QC procedure to remove ROIs of low surface area (<5000 µm<sup>2</sup>) or low perfect aligned reads (<80%), and probes of low quality or identified as global or local outliers (fails Grubbs outlier test in ≥ 20% segments). The remaining data were back-ground subtracted and Q3 normalized to house-keeping genes. ROIs were considered positive for CD8 T cells if their CD8 memory T cell deconvolution fraction was > 0 (R, spatialDecon, CellProfileLibrary; Human Adult ImmuneTumor_safeTME profile). Genes differentially expressed between groups of interest were detected using gene-wise linear modeling in R (edgeR, limma v3.50.3), with p-value adjusted for false discovery rate. Contrasts of groups were performed using t-tests at a significance level of 0.05.</span></p>
Interviews for New Business Models for Pharmaceutical Innovation and Access to Medicines - Neglected Diseases
<p>These supplementary materials represent the partial dataset in the form of semi-structured interviews, collected and analyzed in the research article "Alternative pharmaceutical innovation models for neglected diseases: How can they continue to thrive?". This article is one of the outcomes of the "New Business Models for Pharmaceutical Innovation and Global Access to Medicines" research project, conducted at the Global Health Center, within the Geneva Graduate Institute. The dataset contains 8/21 interviews collected and used in this article, which are published with the informed consent of the interviewees.</p> <p>Details about the research project can be found at: <a href="https://www.graduateinstitute.ch/NBM">https://www.graduateinstitute.ch/NBM</a></p>
Modeling Lewy Body Disease with SNCA Triplication iPSC-Derived Cortical Organoids and Identifying Therapeutic Drugs
<p><span>This repository contains the source code for the single-cell and single-nuclei RNA sequencing data analysis for the study <strong><span>Modeling Lewy Body Disease with SNCA Triplication iPSC-Derived Cortical Organoids and Identifying Therapeutic Drugs</span></strong> by Yunjung Jin et al.<br></span></p>
Noscapine treatment effect in transgenic mouse model of Alzheimer's disease
<p>Cerebrovascular dysfunction and neuroinflammation play key roles in the pathophysiology of Alzheimer’s disease (AD). The kinin-kallikrein system involving bradykinin receptor has been proposed at the nexus of beta-amyloid, vascular pathology and inflammation in patients with AD and in animal models. Here, we evaluated the effect of blocking the bradykinin receptors 1 and 2 by treatment with the bradykinin antagonist noscapine on cerebrovascular dysfunction, inflammation and amyloid pathology in a transgenic mouse model of amyloidosis. Transgenic arcAβ mice, and wild-type littermates of 14 months-of-age were either treated with noscapine (3 g/L, acidified drinking water) or received drinking water as control for three months (n = 8-11 per group). Arterial spin labeling magnetic resonance imaging showed alleviated regional hypoperfusion in noscapine-treated arcAb compared to control arcAb mice. Functional magnetic resonance imaging showed mitigated reduced regional cerebral vascular reactivity in noscapine-treated arcAb compared to control arcAb mice.</p>
data set related to article A Nervous System-Specific Model of Creatine Transporter Deficiency Recapitulates the Cognitive Endophenotype of the Disease: a Longitudinal Study
<p>This record contains raw data related to article A Nervous System-Specific Model of Creatine Transporter Deficiency Recapitulates the Cognitive Endophenotype of the Disease: a Longitudinal Study</p>
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation [Models]
<p>This file contains the pretrained models and the evaluation of the pipelines described in the paper <em>Convolutional Neural Networks for Classification of Alzheimer’s Disease: Overview and Reproducible Evaluation</em>.</p> <p>Source code can be downloaded at: <a href="https://github.com/aramis-lab/AD-DL">https://github.com/aramis-lab/AD-DL</a></p> <p>Also, single files can be obtained at: <a href="https://aramislab.paris.inria.fr/clinicadl/files/models/v0.0.1/">https://aramislab.paris.inria.fr/clinicadl/files/models/v0.0.1/</a></p> <p>The structure of the compressed file is as follows:</p> <p>clinicadl_models/<br> ├── 2D_slice<br> │ ├── baseline<br> │ │ ├── AD_CN<br> │ │ │ ├── best_model<br> │ │ │ └── performances<br> │ │ └── AD_CN_dataleakage<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── longitudinal<br> │ └── AD_CN<br> │ ├── best_model<br> │ └── performances<br> ├── 3D_patch<br> │ ├── baseline<br> │ │ ├── AD_CN<br> │ │ │ ├── best_model<br> │ │ │ └── performances<br> │ │ └── sMCI_pMCI<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── longitudinal<br> │ ├── AD_CN<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── sMCI_pMCI<br> │ ├── best_model<br> │ └── performances<br> ├── 3D_ROI_based<br> │ ├── baseline<br> │ │ ├── AD_CN<br> │ │ │ ├── best_model<br> │ │ │ └── performances<br> │ │ └── sMCI_pMCI<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── longitudinal<br> │ ├── AD_CN<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── sMCI_pMCI<br> │ ├── best_model<br> │ └── performances<br> ├── 3D_subject<br> │ ├── baseline<br> │ │ ├── AD_CN<br> │ │ │ ├── best_model<br> │ │ │ └── performances<br> │ │ └── sMCI_pMCI<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── longitudinal<br> │ ├── AD_CN<br> │ │ ├── best_model<br> │ │ └── performances<br> │ └── sMCI_pMCI<br> │ ├── best_model<br> │ └── performances<br> ├── autoencoders<br> │ ├── 3D_patch<br> │ │ ├── baseline<br> │ │ │ └── best_model<br> │ │ └── longitudinal<br> │ │ └── best_model<br> │ ├── 3D_ROI_based<br> │ │ ├── baseline<br> │ │ │ └── best_model<br> │ │ └── longitudinal<br> │ │ └── best_model<br> │ └── 3D_subject<br> │ └── baseline<br> │ ├── extensive<br> │ └── minimal<br> └── svm<br> ├── baseline<br> │ ├── AD_CN<br> │ │ ├── all_subjects.tsv<br> │ │ └── classifier<br> │ └── sMCI_pMCI<br> │ ├── all_subjects.tsv<br> │ └── classifier<br> └── longitudinal<br> ├── AD_CN<br> │ ├── all_subjects.tsv<br> │ └── classifier<br> └── sMCI_pMCI<br> ├── all_subjects.tsv<br> └── classifier</p> <p>We provide the pretrained CNN models for the frameworks 3D subject-level, 3D ROI-based, 3D patch-level and 2D slice-level. This models can be found as a <strong><em>.pth.tar</em> </strong>file (<em>Pytorch</em> format) inside the <em>best_model</em> folder for each framework (and for each fold). We also provide the autoencoders that initialize the training stage of the CNN networks. The <em>performances </em>folder contains the computed metrics for the correponding model (ACC, BA, etc). <em> </em></p> <p>For the svn classification, we provide files with the dual coefficients, the support vector indices and the weights. Also, <em>tsv</em> files with the subject list.</p>
Identification of early genes in the pathophysiology of fibrotic interstitial lung disease in a new model of pulmonary fibrosis
<p>Some interstitial lung diseases involve pulmonary fibrosis, which is a process that is characterized by the excessive and abnormal accumulation of extracellular matrix in the pulmonary interalveolar space. Although the current anti-fibrotic therapy aims at slowing down the progression of pulmonary fibrosis, it does not reverse it, and many of the drugs that were identified in basic-research studies failed in clinical phases, mainly because of the lack of a model that can recapitulate the pathophysiological mechanisms of human pulmonary fibrosis. We developed a novel experimental model of pulmonary fibrosis induced by a cocktail of molecules on an air/liquid interface culture of mouse embryonic lung explants. Histological analyses revealed a pattern of usual interstitial pneumonia, the worst-prognosis form of pulmonary fibrosis. We performed a transcriptomics analysis at the single-cell level after the induction of fibrosis and before any histological signs of fibrosis could be observed. The results revealed increased expression of several gene families that are involved in early inflammation, fibrosis and iron homeostasis, as well as potential new genetic targets.</p> <p>This Zenodo repository includes original datasets of single cell RNA sequencing, analysis R scripts, final dataset/markers, and HTML codes for the interactive 3D UMAP and VolcanoPlot.</p>
Supplementary data for: Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signalling in a Model of Niemann-Pick Disease Type C
<p>Supplementary example data for the work presented in "<em>Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signalling in a Model of Niemann-Pick Disease Type C</em>". </p> <p><strong>Abstract: </strong></p> <p>Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing our understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavour. Here, we use specially designed graphene microelectrode arrays (G-MEAs), which are compatible with high spatial resolution imaging across various scales as well as permit high temporal resolution electrophysiological recordings to address these challenges. Furthermore, alongside G-MEAs, we have developed an easy-to-implement machine learning algorithm to efficiently process the large datasets collected from MEA recordings. We demonstrate that the combined use of G-MEAs, machine learning (ML) spike analysis, and four-dimensional (4D) structured illumination microscopy (SIM) enables monitoring the impact of disease progression on hippocampal neurons which have been treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC), and show that synaptic boutons, compared to untreated controls, significantly increase in size, leading to a loss in neuronal signalling capacity.</p> <p> </p>
Emergent Ecological Patterns and Modelling of Gut Microbiomes in Health and in Disease
<p><strong><em>Data associated with the paper "Emergent Ecological Patterns and Modelling of Gut Microbiomes in Health and in Disease".</em></strong></p> <p><strong>Content:</strong></p> <ul> <li><strong>Metagenomic curated data considering healthy and diseased state of the human individuals. Aligned against RefSeq with Kaiju.</strong></li> <li><strong>Curated metadata with anonymised physiological and medical information</strong></li> </ul> <p><strong>Paper authors</strong>: Jacopo Pasqualini, Sonia Facchin, Andrea Rinaldo, Amos Maritan, Edoardo Vincenzo Savarino, Samir Suweis</p> <p><strong>Paper preprint</strong>: https://www.biorxiv.org/content/10.1101/2023.10.19.563037v2</p> <p><strong>Data Curator</strong>: Jacopo Pasqualini.</p> <p><strong>Pipeline used to generate the data</strong>: https://github.com/jacopopasqualini/MetaGym</p> <p><strong>Complete description of data generation</strong>: https://www.biorxiv.org/content/10.1101/2023.10.19.563037v2</p>
Systematic creation and phenotyping of Mendelian disease models in C. elegans: towards large-scale drug repurposing
<p>Data collected for the eLife OpenAccess paper: Systematic creation and phenotyping of Mendelian disease models in <em>C. elegans</em>: towards large-scale drug repurposing. (doi: 10.7554/eLife.92491.1)</p> <p>Contains: extracted features, calculated stats, normalised z-scores and timerseries data of all the disease model mutants generated. In addition, there is a static .html file that allows for mousing over the clustermaps to easily view differences in strains compared to the N2 wild-type. Dataset also contains, metadata and feature summary/file name information of FDA-library drug screen and the confirmation screen of the hit from this (i.e., all data collected in published in the associated paper). </p>
ScienceDex guides
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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.