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1,981 results for “coronary artery”
An integrated polygenic tool substantially enhances coronary artery disease prediction
<p>Summary-level CAD GWAS data generated by Genomics plc as presented in:</p> <p>Riveros-Mckay F. et al. An integrated polygenic tool substantially enhances coronary artery disease prediction. Circulation: Genomics and Precision Medicine (in press). </p> <p>If you have any questions or comments regarding these files, please contact Genomics plc at research@genomicsplc.com</p> <p> </p> <p>NOTES<br> -----------------------------<br> These analyses were carried out using the full UK Biobank imputation data release (v3b). Analyses were restricted to a subset of UK Biobank, described as “Group I” in the published paper. Group I, “no PCE/QRISK3 available”, included 114,196 European-ancestry individuals with missing data that prevented PCE or QRISK3 calculation.</p> <p>CAD case phenotypes were defined as described in the “Phenotype definitions” section of the paper’s Supplementary Materials, using both prevalent (pre-baseline) and incident (post-baseline) events.</p> <p>All analyses included Age at assessment, sex, genotyping chip, and 10 principal components as covariates. </p> <p>We used plink2.0 logistic regression. For chromosome X variants males were treated as having 0 or 2 alternative alleles. </p> <p>The results are not adjusted for genomic control.</p> <p> </p> <p>DATA FILE CONTENT DESCRIPTION<br> -----------------------------<br> cpra Variant ID in ‘CPRA’ format. Position reflects position in b37. <br> chrom Chromosome<br> pos Position in base pairs (b37, 1-based)<br> alt Alternative allele (effect allele)<br> beta Effect size (log odds ratio)<br> standard_error Standard error of beta <br> minus_log10_p Minus log(base 10) of P-value<br> ref Reference allele (non-effect allele)<br> ncase Number of cases<br> ncontrol Number of controls</p>
ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset
<p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 2 consist of two folders with 300 images in each of them as well as annotations. </p> <p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1 consists of two datasets of XCA images for each of two tasks of ARCADE challenge. The first task includes in total 1200 coronary vessel tree images, which are divided into train(1000) and validation(200) groups, images for training are followed with annotations, depicting the division of a heart into 26 different regions based on the Syntax Score methodology[1]. Similarly, the second task includes a different set of 1200 images with same train-val division proportion with annotated regions containing atherosclerotic plaques. This dataset, carefully annotated by medical experts, enables scientists to actively contribute towards the advancement of an automated risk assessment system for patients with CAD. </p> <p>The dataset structure is as follows: top-level directories "syntax" and "stenosis" contain files for the two dataset objectives, namely: i) vessel branch classification according to the SYNTAX methodology; and ii) stenosis detection. Inside both directories, there are 3 subsets of the dataset, such as "train", "val", and "test". Inside each of those folders, there are 2 lower-level directories - "images", and "annotations". Inside the "images" folder there are images in ".png" format, extracted from DICOM recordings. The "annotations" folders contain single ".JSON" files, which are named in correspondence to the objective, i.e. "train.JSON", "val.JSON", and "test.JSON".</p> <p>The structure of ".JSON" contains three top-level fields: "images", "categories", and "annotations". The "images" field contains the unique "id" of the image in the dataset, its "width" and "height" in pixels, and the "file_name" sub-field, which contains specific information about the image. The "categories" field contains a unique "id" from 1 to 26, and a "name", relating it to the SYNTAX descriptions. The "annotations" field contains a unique "id" of the annotation, "image_id" value, relating it to the specific image from the "images" field, and a "category_id" relating it to the specific category from the "categories" field. The "segmentation" sub-field contains coordinates of mask edge points in "XYXY" format. Bounding box coordinates are given in the "bbox" field in the "XYWH" format, where the first 2 values represent the x and y coordinates of the left-most and top-most points in the segmentation mask. The height and width of the bounding box are determined by the difference between the right-most and bottom-most points and the first two values. Finally, the "area" field provides the total area of the bounding box, calculated as the area of a rectangle.</p> <p> </p> <p>The corresponding Dataset Article will be provided later. </p> <p>[1] Syntax score segment definitions. https://syntaxscore.org/index.php/tutorial/definitions/14-appendix-i-segment-definitions</p>
Data for: Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease.
<p>Summary of Bivariate GWAS scan results reported in:<br> <a href="https://pubmed.ncbi.nlm.nih.gov/30525989/">Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease. </a>Siewert KM, Voight BF. Circ Genom Precis Med. 2018 Dec;11(12):e002239. doi: 10.1161/CIRCGEN.118.002239.</p> <p>PMID: 30525989 </p>
A protocol to assess the risk of dementia among patients with coronary artery diseases using CAIDE score-Extended Data
<p>The contents of this extended data file are-<br> 01. Consent form (English & Bengali Version)<br> 02. Interview Questionnaire (English & Bengali Version)<br> These contents will help to address the objectives of the study that attempted to identify the risk of long-term dementia among coronary artery disease patients in Bangladesh.</p>
The supplemental data for the paper: "Methodology of generation of CFD meshes and 4D shape reconstruction of coronary arteries from patient-specific dynamic CT"
<p>The supplemental data for the paper: "Methodology of generation of CFD meshes and 4D shape reconstruction of coronary arteries from patient-specific dynamic CT"</p><p>A video file (minimum play resolution is HD to see the mesh) showing the movement of the LCA throughout the heart cycle and .STL files for 10--100% (increment of 10\%) of the heart cycle phase.</p>
Data from: Coronary artery segmentation in non-contrast calcium scoring CT images using deep learning
<p><strong>Abstract</strong></p> <p>Precise segmentation of coronary arteries in non-contrast Computed Tomography (CT) scans plays an important role in the assessment of the coronary artery disease, where it is the key component for evaluating the Calcium Score (Agatston et al. 1990). In the paper by Bujny et al. (2024), a deep-learning approach for high-precision segmentation of coronary arteries in non-contrast CT was proposed along with a novel method for generating Ground Truth (GT) test data (<em>test-GT</em>) via manual registration of high-resolution coronary tree models obtained based on contrast CT with the non-contrast CT scans. In this dataset, we present the inferences of the neural network model together with the corresponding <em>test-GT</em> samples, based on 6 CT scans from the openly available OrCaScore dataset (Wolterink et al. 2016). The geometrical models included in the dataset can be used both for inspection of the proposed deep learning model and for testing of new non-contrast coronary vessel segmentation approaches, which is a unique opportunity since, to the best of our knowledge, manual generation of GT for non-contrast coronary artery segmentation was not addressed so far due to very challenging character of this particular segmentation task.</p> <p> </p> <p><strong>Methods</strong></p> <p><strong><em>Manual Generation of test-GT</em></strong></p> <p>The geometric models of coronary arteries used for the evaluation of the proposed neural network model were generated according to the manual mesh-to-image registration process as described by Bujny et al. (2024). In this approach, the high-resolution coronary artery masks obtained based on contrast CT scans are manually aligned with the corresponding non-contrast CT images using tools available in the open-source 3D computer graphics software, Blender (<a href="https://www.blender.org/">https://www.blender.org/</a>). To ease the manual alignment process, specialized add-ons for medical image processing such as Cardiac add-on for Blender of Graylight Imaging (<a href="https://graylight-imaging.com/3d-modelling/">https://graylight-imaging.com/3d-modelling/</a>) can be used, as well. The STL models in this dataset were manually generated by a medical expert with 4 years of experience.</p> <p><strong><em>Segmentation of Coronary Arteries using a Deep Learning Model</em></strong></p> <p>For each of the cases presented in this dataset, we run an inference of an nnU-Net (Isensee et al. 2021) model trained according to the process described in our paper (Bujny et al. 2024). Since we use a standard nnU-Net, which utilizes a sliding window approach for processing of the CT scan, the context information within a patch is limited, which can lead to some false-positive detections. To mitigate this problem, we additionally post-process the inferences by eliminating small vessel fragments of less than 50 [mm^3] volume and structures outside of pericardium, which we segment using another nnU-Net model, SegTHOR (Lambert et al. 2020). The resulting geometric models are stored using the STL format and presented as green masks in the HTML reports with an embedded viewer based on the K3D-jupyter library (<a href="https://k3d-jupyter.org/">https://k3d-jupyter.org/</a>).</p> <p> </p> <p><strong>Dataset organization</strong></p> <p>The root folder contains 6 folders whose names correspond to the CT scans from the OrCaScore dataset (Wolterink et al. 2016). In each of the folders, there are the following 4 files available:</p> <ul> <li><span>‘manualGT_rater1.stl’ – high-resolution STL model of coronary arteries obtained via manual alignment of the geometric model segmented in contrast CT with the corresponding non-contrast CT scan by the first rater.</span> A sample belonging to the <em>test-GT</em> set (Bujny et al. 2024).</li> <li>‘manualGT_rater2.stl’ – corresponding <em>test-GT</em> sample by the second rater.</li> <li>‘ML.stl’ – post-processed inference of the nnU-Net ML model in the STL format.</li> <li>‘report.html’ – interactive HTML report consisting of a manually-aligned <em>test-GT</em> sample (red mask), the ML segmentation based on the non-contrast CT scan (green mask), and selected slices of the non-contrast CT scan. The reports contain the relevant information related to the scanning device and present the main segmentation quality metrics for the ML model inference.</li> </ul>
Summary statistics from "Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease"
<p>GWAMA summary statistics of four steroid hormone levels using fixed-effect model and GWAS summary statistics of four other steroid hormones.</p> <p>When using this data, please cite: Pott J, Bae YJ, Horn K, et al.. Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. <em>J Clin Endocrinol Metab</em> <strong>2019</strong> Nov 1;104(11):5008-5023. doi: 10.1210/jc.2019-00757</p> <p>All txt files contain the following columns:</p> <ul> <li>markername</li> <li>chr</li> <li>bp_hg19 (base position according to hg19)</li> <li>effect_allele</li> <li>other_allele</li> <li>effect_allele_freq</li> <li>min_info (minimal info score across all used studies)</li> <li>n (sample size per SNP)</li> <li>beta (effect estimate)</li> <li>se (standard error)</li> <li>p (p-value)</li> <li>CochransQ (only in GWAMA; SNP heterogeneity across studies)</li> <li>pCochransQ (only in GWAMA; p-value of Cochrans Q value)</li> </ul>
The Influence of Smoking Status on Prasugrel and Clopidogrel Treated Subjects Taking Aspirin and Having Stable Coronary Artery Disease
ClinicalTrials.gov study NCT01260584. IPD Sharing: YES. Countries: 1. Publications: 1.
A gene variation at the ZPR1 locus (rs964184) interacts with the type of diet to modulate postprandial triglycerides in patients with coronary artery disease: From the Cordioprev Study
<p>Background and Aims: rs964184 variant in the ZPR1 gene has been associated with blood lipids levels both in fasting and postprandial state and with the risk of myocardial<br>infarction in high-risk cardiovascular patients. However, whether this association is modulated by diet has not been studied.</p> <p>Objective: To investigate whether the type of diet (low-fat or Mediterranean diets) interacts with genetic variability at this loci to modulate fasting and postprandial lipids in<br>coronary patients.</p> <p>Materials and Methods: The genotype of the rs964184 polymorphism was determined in the Cordioprev Study population (NCT00924937). Fasting and Postprandial triglycerides were assessed before and after 3 years of dietary intervention with either a Mediterranean or a low-fat diet. Postprandial lipid assessment was done by a 4-h oral fat tolerance test (OFTT). Differences in triglycerides levels were identified using repeated-measures ANCOVA.</p> <p>Results: From 523 patients (85% males, mean age 59 years) that completed the OFTT at baseline and after 3 years of intervention and had complete genotype information, 125<br>of them were carriers of the risk allele G. At the start of the study, these patients showed a higher fasting and postprandial triglycerides (TG) plasma levels. After 3 years of dietary<br>intervention, G-carriers following a Mediterranean Diet maintained higher fasting and postprandial triglycerides, while those on the low-fat diet reduced their postprandial<br>triglycerides to similar values to the population without the G-allele.</p> <p>Conclusion: After 3 years of dietary intervention, the altered postprandial triglyceride response induced by genetic variability in the rs964184 polymorphism of the ZPR1 gene<br>can be modulated by a low-fat diet, better than by a Mediterranean diet, in patients with coronary artery disease.</p>
Dataset related to the article :"Mercaptoalbumin Is Associated with Graft Patency in Patients Undergoing Coronary Artery Bypass Grafting"
<p>This record contains raw data related to the article:" Mercaptoalbumin Is Associated with Graft Patency in Patients Undergoing Coronary Artery Bypass Grafting" </p> <p>Abstract</p> <p>Coronary artery bypass graft (CABG) surgery still represents the gold standard for patients with complex multivessel coronary artery disease. However, graft occlusion still occurs in a significant proportion of CABG conduits, and oxidative stress is currently considered to be a potential contributor. Human serum albumin (HSA) represents the main antioxidant in plasma through its reduced amino acid Cys34, which can efficiently scavenge several oxidants.<strong> </strong>In a nested case–control study including 36 patients with occluded grafts and 38 age- and sex-matched patients without occlusion, we assessed the levels of the native mercaptoalbumin (HSA-SH) and oxidized thiolated form of albumin (Thio-HSA) in relation with graft occlusion within 5 years after CABG.<strong> </strong>We found that the plasma level of preoperative HSA-SH was significantly lower in patients with occluded graft at 5 years follow-up than in patients with graft patency. Furthermore, low HSA-SH remained independently associated with graft occlusion even after adjusting for preoperative D-dimer, a well-known marker of activated coagulation recently found to be associated with graft occlusion. In conclusion, the preoperative level of HSA-SH is independently associated with graft occlusion in CABG and represents a measurable and potentially druggable predictor.</p>
Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.
<p>*.sh and *.R are codes to test rare coding variants for association with ISCAD.</p> <p>Petrazzini_etal_2024_*_level_meta_analysis.txt.gz are summary statistics of variant- and gene-level associations of rare coding variants in the exome sequences of 604,914 individuals with an in-silico score for coronary artery disease (ISCAD).</p> <p>Chromosomal positions are mapped to the GRCh38 (hg38) human genome reference.</p> <p>Directions of effect correspond to associations in the UK Biobank, the All of Us Research Program, the BioMe Biobank sample 1 and the BioMe Biobank sample 2, in that order.</p>
Structural coronary artery remodelling in the rabbit fetus as a result of intrauterine growth restriction
<p>Segmentation of the coronary arteries in synchrotron X-Ray Phase Contrast images from 8fetal rabbit hearts: 4 controls (healthy), and the other 4 with intrauterine growth restriction (IUGR).</p>
Datasets corresponding to "Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets"
<p><strong>Datasets corresponding to "Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets"</strong></p> <p><strong>02_CNN_PhenotypeClassif.7z</strong></p> <p>CNN Phenotype classification. Model was trained using AIDeveloper. using manually labelled data. Labelled Data is contained in folder "03_GatedData". The AIDeveloper session file in "02_Model\M10_Nitta6l_32pix_8class_meta.xlsx" shows, which files correspond to which subpopulation. The final model "M10_Nitta6l_32pix_8class_448.model" and corresponding .pb files are also located in that folder.</p> <p><strong>codeforclassification.zip</strong></p> <p>Code for applying model on unlabelled data. Test data is contained in 'sampledata.zip'</p> <p> </p> <p> </p> <p> </p>
Risk of Dementia and Its Associated Factors Among the Patients with Coronary Artery Disease Attending a Tertiary Cardiac Hospital of Dhaka City: A Cross-sectional Study
<p>This data set of research assessed the risk of dementia among patients with coronary artery disease.</p>
Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci
<p>All full-sample files contain results generated in coronary artery tissue from 138 American adults. Subset analyses utilized 80 individuals selected from the original 138. Scripts accompanying some of these data in downstream analyses can be viewed on our Github, which also contains a link to the current version of our accompanying manuscript: https://github.com/MillerLab-CPHG/CAD_QTL</p> <p>Full summary statistics for eQTL associations using mixQTL (https://github.com/hakyimlab/mixqtl/wiki) by chromosome are located in UVA_coronary_mixQTL_sumstats_by_chromosome.zip</p> <p>Full summary statistics for eQTL associations using mixQTL in the subset of 100% European-ancestry study sample members by chromosome are located in Hodonsky_mixQTL_Euro_sumstats.zip</p> <p>Full summary statistics for eQTL associations using mixQTL in the genetically diverse downsampled subset by chromosome are located in Hodonsky_mixQTL_downsample_sumstats.zip</p> <p>Full summary statistics for nominal pass for all genes identified as significant in the permutation pass using QTLtools (https://qtltools.github.io/qtltools/) adjusting for local ancestry by gene by chromosome are located in Local_ancestry_UVA_coronary_QTLtools_nominal_sumstats.zip</p> <p>Full summary statistics for sQTL associations with splice junctions using QTLtools by gene are located in sQTL_results_UVA_coronary_full_sumstats.zip</p>
The PLATINUM Clinical Trial to Assess the PROMUS Element Stent System for Treatment of Long De Novo Coronary Artery Lesions (PLATINUM LL)
ClinicalTrials.gov study NCT01500434. IPD Sharing: UNDECIDED. Countries: 7. Publications: 2.
Protection of the Heart With Doxycycline During Coronary Artery Bypass Grafting
ClinicalTrials.gov study NCT00246740. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Pharmacokinetics (PK)/Safety Study of Atorvastatin in Children With Kawasaki Disease and Coronary Artery Abnormalities
ClinicalTrials.gov study NCT01431105. IPD Sharing: Not stated. Countries: 1. Publications: 1.
PCP Use of a Gene Expression Test (Corus CAD or ASGES) in Coronary Artery Disease Diagnosis
ClinicalTrials.gov study NCT01594411. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Rivaroxaban for the Prevention of Major Cardiovascular Events in Coronary or Peripheral Artery Disease
ClinicalTrials.gov study NCT01776424. IPD Sharing: NO. Countries: 33. Publications: 66.
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
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DANDI Archive for NWB datasets
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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.