ArticleJournal of thoracic disease2022
Integrated gene expression profiling analysis reveals
Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 18 citations in OpenAlex.
- SerpinA3 is an Endogenous TGF-β Receptor Antagonist that Attenuates Cardiac Fibroblast Activation and Fibrotic Remodeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Prognostic and therapeutic implications of PSMD14 in hepatocellular carcinoma: an integrative analysis of transcriptomic and single-cell profiles.Translational cancer research · 2026Article
- Integrated transcriptomics and machine learning reveal diagnostic biomarkers and immune-stromal remodeling in ischemic heart failure.Frontiers in bioinformatics · 2026Article
- Identification of Glycosylation-Related Biomarkers in COPD and IPF Through Integrated Machine Learning and WGCNA Analysis.Journal of inflammation research · 2026Article
- Unveiling the Therapeutic Mechanisms of Chinese Herbs in Heart Failure: Integrating Network Pharmacology, Molecular Docking, and Simulation Analysis.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Identification of noval diagnostic biomarker for HFpEF based on proteomics and machine learning.Proteome science · 2025Article
- Dynamics of SERPINA3 in response to anthracycline treatment and cardiovascular dysfunction.Cardio-oncology (London, England) · 2025Article
- SERPINA3: A Novel Therapeutic Target for Diabetes-Related Cognitive Impairment Identified Through Integrated Machine Learning and Molecular Docking Analysis.International journal of molecular sciences · 2025Article
- Identification of signature genes and subtypes for heart failure diagnosis based on machine learning.Frontiers in cardiovascular medicine · 2025Article
- Uncovering key biomarkers, potential therapeutic targets and development of deep learning model in heart failure.PloS one · 2025Article
- Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with dilated cardiomyopathy (DCM) by bioinformatics analysis and machine learning.Frontiers in genetics · 2025Article
- A personalized mRNA signature for predicting hypertrophic cardiomyopathy applying machine learning methods.Scientific reports · 2024Article
- Characterization of systolic and diastolic function, alongside proteomic profiling, in doxorubicin-induced cardiovascular toxicity in mice.Cardio-oncology (London, England) · 2024Article
- Doxorubicin-induced cardiovascular toxicity: a longitudinal evaluation of functional and molecular markers.Cardiovascular research · 2023Article
- Article
- SERPINA3: Stimulator or Inhibitor of Pathological Changes.Biomedicines · 2023Review
- GeneCompete: an integrative tool of a novel union algorithm with various ranking techniques for multiple gene expression data.PeerJ. Computer science · 2023Article
- Heart failure-related genes associated with oxidative stress and the immune landscape in lung cancer.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The purpose of this study was to identify possible diagnostic indicators for heart failure (HF) and to investigate the function of immune cell infiltration in this pathophysiology. Methods: HF datasets from the Gene Expression Metascape database were utilized. R software was used to the identify differentially-expressed genes (DEGs) and perform functional correlation analysis. Least absolute shrinkage and selection operator (LASSO) and Boruta algorithms elimination algorithms were then employed to screen and validate the HF diagnostic variables. Finally, Single-sample Gene Set Enrichment Analysis (ssGSEA) was utilized to assess immune cell infiltration in HF tissues, and the Spearman association between gene expression and immune cell concentration was investigated. Results: A total of 239 DEGs were screened in this study. Conclusions: Given the importance of immune cell infiltration in the genesis and progression of HF,
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Registered trials
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 OpenQuestion graph.