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143 results for “Neurodegenerative diseases”
The contribution of Neanderthal introgression and natural selection to neurodegenerative diseases
<p>Files used to create binary annotations for LDSC in the following repository: https://github.com/RHReynolds/als-neanderthal-analysis.</p> <p>See the following link for details: https://github.com/RHReynolds/als-neanderthal-analysis/tree/main/raw_data/01_annotations</p>
Supplemental data for: A bibliometric assessment of the incidence of amyloid-Eszett (Aß), a false positive of amyloid-beta (Aβ), in the neurodegenerative disease literature
<p>One claimed reason for the development of Alzheimer’s disease (AD), a prominent neurodegenerative disease, is the extracellular aggregation of amyloid-beta (Aβ). A linguistic or formatting error has resulted in the misrepresentation of the Greek letter β with the German letter Eszett (ß), resulting in the formation of a non-existent compound, amyloid-Eszett (Aß). These datasets offer a quantified appreciation of the AD-related literature, carrying a mention of this false positive in the title, abstract and keywords of papers indexed in the Web of Science Core Collection and Scopus. Also, as a curiosity given the popularity of this large language model, we asked the questions to ChatGPT. This AI chatbot developed by OpenAI was able to recognize Eszett as a linguistic or typographic error, within this context, recognizing Aß and Aβ as equals. This erroneous substitution of a Greek letter (in Aβ) by a German one (Aß), despite giving a non-existent compound, will likely not change the underlying scientific conclusions of the affected papers, although errata might be useful to enlighten others, including metadata managers and journal copyeditors, so as not to repeat the same mistake.</p>
Anti-TNF therapy for inflammatory bowel disease in patients with neurodegenerative Niemann-Pick disease Type C
<p>Abstract:</p> <p>Background: Blockade of tumour necrosis factor (anti-TNF) is effective in patients with Crohn’s Disease but has been associated with infection risk and neurological complications such as demyelination. Niemann-Pick disease Type C1 (NPC1) is a lysosomal storage disorder presenting in childhood with neurological deterioration, liver damage and respiratory infections. Some NPC1 patients develop severe Crohn’s disease. Our objective was to investigate the safety and effectiveness of anti-TNF in NPC1 patients with Crohn’s disease.</p> <p>Methods: Retrospective data on phenotype and therapy response were collected from patients with genetically confirmed NPC1 defects and intestinal inflammation. We investigated TNF secretion in peripheral blood mononuclear cells treated with NPC1 inhibitor in response to bacterial stimuli.</p> <p>Results: NPC1 inhibitor treated PBMCs show significantly increased TNF production after lipopolysaccharide or bacterial challenge providing a rationale for anti-TNF therapy. We identified 5 NPC1 patients with CD-like intestinal inflammation treated using anti-TNF therapy (mean age of onset 8.6 years, mean treatment length 27.2 months, overall treatment period 11.3 patient years). Anti-TNF therapy was associated with reduced gastrointestinal symptoms with no apparent adverse neurological events. Therapy improved intestinal inflammation in 4 patients.</p> <p>Conclusion: Anti-TNF therapy appears safe in patients with NPC1 and is an effective treatment strategy for the management of intestinal inflammation in these patients.</p>
White matter hyperintensity maps in aging and neurodegenerative diseases
<div>The files contain voxel-wise white matter hyperintensity (WMH) maps for 11 different neurodegenerative disease cohorts from the <em>Canadian</em> Consortium on Neurodegeneration in Aging (<em>CCNA</em>) COMPASS-ND dataset in the MNI-ICBM152-2009c space.</div> <div> </div> <div>For more information regarding the participants and method details, see: </div> <div>Dadar, M., Mahmoud, S., Zhernovaia, M., Camicioli, R., Maranzano, J., Duchesne, S., & CCNA Group. (2022). White matter hyperintensity distribution differences in aging and neurodegenerative disease cohorts. <em>NeuroImage: Clinical</em>, <em>36</em>, 103204.</div>
[Supp. mat.] Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: initial application to the GENFI cohort
<p>Supplementary tables and figure of paper Spatio-temporal analysis for detection of pre-symptomatic shape changes in neuro-degenerative diseases: initial application to the GENFI cohort, for testing different number of clusters of the spatio-temporal regression. The supplementary materials shows results for 2 4 6 8 12 14 and 16 clusters. The 10 clusters analysis is in the paper.</p>
Neurodegenerative Alzheimer's Disease and Amyotrophic Lateral Sclerosis (NADALS) Basket Trial
ClinicalTrials.gov study NCT05189106. IPD Sharing: YES. Countries: 1. Publications: 2.
The Ontario Neurodegenerative Disease Research Initiative
ClinicalTrials.gov study NCT04104373. IPD Sharing: YES. Countries: 1. Publications: 1.
A Safety Study of Pimavanserin in Adult and Elderly Subjects Experiencing Neuropsychiatric Symptoms Related to Neurodegenerative Disease
ClinicalTrials.gov study NCT03575052. IPD Sharing: NO. Countries: 12. Publications: 1.
Inhibition of amyloid beta oligomer accumulation by NU-9: A unifying mechanism for the treatment of neurodegenerative diseases data set
Open the record for dataset details and reuse information.
Strategic delivery of Omega-3 fatty acids for modulating inflammatory neurodegenerative diseases
Open the record for dataset details and reuse information.
Prediction of individual disease progression including parameter uncertainty in rare neurodegenerative diseases: the example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS) - code and data sets
<p>This repository contains the scripts for the paper in revision to the AAPS J: Prediction of individual disease progression including parameter uncertainty in rare neurodegenerative diseases: the example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS) </p> <p>Authors: Niels Hendrickx, MSc, France Mentré, MD, PhD, Andreas Traschütz, MD, PhD, Cynthia Gagnon, PhD, Rebecca Schüle, MD, ARCA Study Group, EVIDENCE-RND consortium, Matthis Synofzik, MD, Emmanuelle Comets, PhD</p> <p>A simulated dataset (<strong>simulated_arsacs.csv</strong>) has been included in the repository to make the code executable as a standalone. Four main scripts have been provided in addition with the present Readme describing the files. The repository also includes 3 R objects and 2 folders which will be overwritten when the scripts are run, and are included as examples of the expected outputs. The main scripts are:</p> <p>- <strong>Script_imputation_selection.R</strong>: runs the covariate selection method. It uses a simulated dataset provided in the depot. The multiple imputation model is hardcoded as an input to the mice package to generate 10 imputed datasets, saved in current_directory/imputed_data_sets/df_arsacs_mi_i.csv. The script then runs the covariate selection method. The script prints out the list of selected covariates and returns a saemixObject containing the fit of the selected covariate model.<br> After the script executes, a list will be saved with the name of the selected covariates in the current directory (an example is included under the name "cov_matrix_model.RData" in the repository), the output of the selection, containing the whole history of runs will be saved under "final_covariate_model.RData", the list of selected covariate names will be saved under "list_covariates.RData".</p> <p>- <strong>source_mi.R</strong>: contains the functions used by Script_imputation_selection.R</p> <p>- <strong>script_bootstrap_indfit.R</strong>: This script loads "cov_matrix_model.RData" containing the matrix of covariate effects (used by saemix) and "list_covariates.RData", the list of covariates included, fits the model on the imputed data sets and computes its bootstrap distribution for each imputed data set (in the script, using only 20 samples for computation time, saved in current_directory/bootstrap/boot.arsacs.case.mi.i). It then computes the mean parameter and relative standard error of each parameter. It then computes the conditional distribution of each patient in each bootstrap samples and returns a data frame of individual predictions. The script will then plot 4 indivudal predictions. </p> <p>-<strong> source_bootstrap.R</strong>: contains the functions used by script_bootstrap_indfit.R</p> <p>Both scripts need the saemix package to run, which we haven’t included in the repository as it is freely available on the CRAN (https://cran.r-project.org/web/packages/saemix/index.html). Additional libraries we make use of in the code (MICE, tidyverse, ggplot2) also need to be installed prior to execution. <br>The R code provided can be further customised to be adapted to different scenarios.</p> <p>For the code to run, it is preferable to unzip the whole folder and set the working directory to the source file location as the script uses the "bootstrap" and "imputed_data_sets" sub-folders</p> <p>To execute this code, assuming the required libraries are available in the local R installation, please open an R session and run:<br>source("Script_imputation_selection.R") # for the covariate selection method (runtime: 3h on a i7-8565U laptop)<br>source("script_bootstrap_indfit.R") # to obtain individual trajectories (runtime: 1h on a i7-8565U laptop)</p>
Table A6 images from Computer-aided drug design (CADD) to de-orphanise marine molecules: Finding potential therapeutic agents for neurodegenerative and cardiovascular diseases
<p>High Reslution Images from Table A6</p>
Repurposing Major Metabolites of Lamiaceae Family as Potential Inhibitors of α-Synuclein Aggregation to Alleviate Neurodegenerative Diseases: An In Silico Approach
Open the record for dataset details and reuse information.
Retinal Neurodegenerative Signs in Alzheimer's Diseases
ClinicalTrials.gov study NCT01555827. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PET Imaging of Cyclooxygenases in Neurodegenerative Brain Disease
ClinicalTrials.gov study NCT04396873. IPD Sharing: YES. Countries: 1. Publications: 0.
Sociodemographic Factors and Criminal Behaviour Preceding Neurodegenerative Disease - Retrospective Register Study
ClinicalTrials.gov study NCT06209515. IPD Sharing: NO. Countries: 1. Publications: 0.
Computerized Cognitive Training in Neurodegenerative Diseases (NDD2019)
ClinicalTrials.gov study NCT04111640. IPD Sharing: NO. Countries: 1. Publications: 10.
Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling
ClinicalTrials.gov study NCT06529744. IPD Sharing: NO. Countries: 1. Publications: 33.
Saliva and Extracellular Vesicles for Neurodegenerative Diseases
ClinicalTrials.gov study NCT06869135. IPD Sharing: NO. Countries: 1. Publications: 2.
DaTSCAN Imaging in Aging and Neurodegenerative Disease
ClinicalTrials.gov study NCT01453127. IPD Sharing: Not stated. Countries: 1. Publications: 7.
ScienceDex guides
Understand access before you commit
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.