ArticleFrontiers in immunology2023
Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases.International journal of molecular sciences · 2024Pooled it
- Exploring the mechanism of Dieda Qili Tablet on fracture healing based on network pharmacology combined with machine learning models.Scientific reports · 2026Article
- Different forms of cardiomyocyte death in post-myocardial infarction ventricular remodeling: mechanisms and therapeutic strategies.Frontiers in cardiovascular medicine · 2026Review
- Network Pharmacology-Based Identification of Potential Targets and Mechanisms of Isoginkgetin in Gastric Cancer.BioMed research international · 2026Article
- DNA Methylation Patterns of 5mC Regulators: Insights into Immune Microenvironment Regulation in Heart Failure.Applied biochemistry and biotechnology · 2026Article
- The role of cellular senescence in cardiovascular disease.Cell death discovery · 2025Review
- Integrated genomics reveals cellular senescence-driven molecular networks and immune crosstalk in myopia pathogenesis.Journal of cell communication and signaling · 2025Article
- Identification of senescence-related biomarkers for osteoporosis based on microarray analysis, Mendelian randomization, and experimental validation.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Novel insights into post-myocardial infarction cardiac remodeling through algorithmic detection of cell-type composition shifts.PLoS genetics · 2025Article
- Article
- Knockdown of TGFB2 Attenuates Ischemic Heart Failure by Inhibiting Apoptosis.Cardiovascular toxicology · 2025Article
- Screening core genes for minimal change disease based on bioinformatics and machine learning approaches.International urology and nephrology · 2025Article
- DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggability programmed cell death in heart failure.Frontiers in genetics · 2025Article
- Integrated multi-omics analysis and predictive modeling of heart failure using sepsis-related gene signature.PloS one · 2025Article
- Identification of signature genes and subtypes for heart failure diagnosis based on machine learning.Frontiers in cardiovascular medicine · 2025Article
- Identification of Anoikis-related potential biomarkers and therapeutic drugs in chronic thromboembolic pulmonary hypertension via bioinformatics analysis and in vitro experiment.Scientific reports · 2024Article
- Integrated bioinformatics and machine learning algorithms reveal the unfolded protein response pathways and immune infiltration in acute myocardial infarction.Journal of thoracic disease · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Heart failure (HF) is the final stage of many cardiovascular illnesses and the leading cause of death worldwide. At the same time, ischemic cardiomyopathy has replaced valvular heart disease and hypertension as the primary causes of heart failure. Cellular senescence in heart failure is currently receiving more attention. In this paper, we investigated the correlation between the immunological properties of myocardial tissue and the pathological mechanisms of cellular senescence during ischemic cardiomyopathy leading to heart failure (ICM-HF) using bioinformatics and machine learning methodologies. Our goals were to clarify the pathogenic causes of heart failure and find new treatment options. First, after obtaining GSE5406 from the Gene Expression Omnibus (GEO) database and doing limma analysis, differential genes (DEGs) among the ICM-HF and control groups were identified. We intersected these differential genes with cellular senescence-associated genes (CSAG)
Indexed as
Identifiers
What OpenQuestion holds
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.