ArticleBioMed research international2020
Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis.
Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed, 24 citations in OpenAlex.
- The Latest Advances in Omics Technology for Assessing Tissue Damage: Implications for the Study of Sudden Cardiac Death.International journal of molecular sciences · 2025Review
- Dendritic cell-derived lncRNAs in patients with acute coronary syndrome.Journal of cellular and molecular medicine · 2024Article
- Posttranscriptional Regulation by Proteins and Noncoding RNAs.Advances in experimental medicine and biology · 2024Article
- M2 macrophage exosomal LINC01001 promotes non-small cell lung cancer development by affecting METTL3 and glycolysis pathway.Cancer gene therapy · 2023Article
- Long non-coding RNA expression in PBMCs of patients with active pulmonary tuberculosis.Frontiers in microbiology · 2023Article
- Association of theFrontiers in molecular biosciences · 2023Article
- From multi-omics approaches to personalized medicine in myocardial infarction.Frontiers in cardiovascular medicine · 2023Review
- Candidate genes and their alternative splicing may be potential biomarkers of acute myocardial infarction: a study of mouse model.BMC cardiovascular disorders · 2022Article
- Sex-specific transcriptome differences in a middle-aged frailty cohort.BMC geriatrics · 2022Article
- Clinical assessment and molecular mechanism of the upregulation of Toll-like receptor 2 (TLR2) in myocardial infarction.BMC cardiovascular disorders · 2022Article
- LncRNA XIST facilitates hypoxia-induced myocardial cell injury through targeting miR-191-5p/TRAF3 axis.Molecular and cellular biochemistry · 2022Article
- Transcription factor JDP2 activates PDE4B to participate in hypoxia/reoxygenation-induced H9c2 cell injury.Experimental and therapeutic medicine · 2022Article
- Overexpression of LINC00936 Inhibits the Proliferation and Invasion of Endometrial Carcinoma Cells.Journal of oncology · 2022Article
- Review
- ATP2B1-AS1 Promotes Cerebral Ischemia/Reperfusion Injury Through Regulating the miR-330-5p/TLR4-MyD88-NF-κB Signaling Pathway.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI. MATERIALS AND
methodsMicroarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis. The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI. The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs.
resultsIn the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs). Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI. Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that
conclusionIn conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.
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.