ArticleOxidative medicine and cellular longevity2022
Gpx3 and Egr1 Are Involved in Regulating the Differentiation Fate of Cardiac Fibroblasts under Pressure Overload.
Article in Oxidative medicine and cellular longevity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- GPX3 Overexpression Ameliorates Cardiac Injury Post Myocardial Infarction Through Activating LSD1/Hif1α Axis.Journal of cellular and molecular medicine · 2025Article
- Advances in cardiac organoid research: implications for cardiovascular disease treatment.Cardiovascular diabetology · 2025Review
- Cardiac-targeted delivery of a novel Drp1 inhibitor for acute cardioprotection.Journal of molecular and cellular cardiology plus · 2024Article
- Review
- Transcription Factor EGR1 Facilitates Neovascularization in Mice with Retinopathy of Prematurity by Regulating the miR-182-5p/EFNA5 Axis.Biochemical genetics · 2024Article
- Integrative Single-Cell Analysis of Cardiomyopathy Identifies Differences in Cell Stemness and Transcriptional Regulatory Networks among Fibroblast Subpopulations.Cardiology research and practice · 2024Article
- What Links Chronic Kidney Disease and Ischemic Cardiomyopathy? A Comprehensive Bioinformatic Analysis Utilizing Bulk and Single-Cell RNA Sequencing Data with Machine Learning.Life (Basel, Switzerland) · 2023Article
- Article
- Selenium and Selenoproteins in Health.Biomolecules · 2023Review
- Exploring the molecular mechanism of Gan Shuang granules for the treatment of non-alcoholic steatohepatitis using network pharmacology, molecular docking, and experimental verification.Frontiers in pharmacology · 2023Article
- Editorial: Myocardial fibrosis: What we know now.Frontiers in cardiovascular medicine · 2022Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Although myocardial fibrosis is a common pathophysiological process associated with many heart diseases, the molecular mechanisms regulating the development of fibrosis have not been fully determined. Recently, single cell RNA sequencing (scRNA-seq) analysis has been used to examine cellular fate and function during cellular differentiation and has contributed to elucidating the mechanisms of various diseases. The main purpose of this study was to characterize the fate of cardiac fibroblasts (CFs) and the dynamic gene expression patterns in a model of cardiac pressure overload using scRNA-seq analysis. Methods: The public scRNA-seq dataset of the transverse aortic coarctation (TAC) model in mice was downloaded from the GEO database, GSE155882. First, we performed quality control, dimensionality reduction, clustering, and annotation of the data through the Seurat R package (v4.0.5). Then, we constructed the pseudotime trajectory of cell development and identified key regulatory genes using the Monocle R package (v2.22.0). Different cell fates and groups were fully characterized by Gene Set Enrichment Analysis (GSEA) analysis and Transcription factor (TF) activity analysis. Finally, we used Cytoscape (3.9.1) to extensively examine the gene regulatory network related to cell fate. Results: Pseudotime analysis showed that CFs differentiated into two distinct cell fates, one of which produced activated myofibroblasts, and the other which produced protective cells that were associated with reduced fibrosis levels, increased antioxidative stress responses, and the ability to promote angiogenesis. In the TAC model, activated CFs were significantly upregulated, while protective cells were downregulated. Treatment with the bromodomain inhibitor JQ1 reversed this change and improved fibrosis. Analysis of dynamic gene expression revealed that Conclusions: The scRNA-seq analysis was used to characterize the dynamic changes associated with fibroblast differentiation and identified
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.