ArticleFrontiers in immunology2022
Immune-associated pivotal biomarkers identification and competing endogenous RNA network construction in post-operative atrial fibrillation by comprehensive bioinformatics and machine learning strategies.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review.Journal of anesthesia · 2024Pooled it
- Nuclear factor I-C as a novel candidate regulator in postoperative atrial fibrillation: integrated omics and proof-of-concept validation.Molecular and cellular biochemistry · 2026Article
- Circular RNAs as Novel Biomarkers and Application in Cardiovascular Diseases.Advances in experimental medicine and biology · 2025Review
- Gene modules and genes associated with postoperative atrial fibrillation: weighted gene co-expression network analysis and circRNA-miRNA-mRNA regulatory network analysis.Journal of thoracic disease · 2023Article
- APOC1 exacerbates renal fibrosis through the activation of the NF-κB signaling pathway in IgAN.Frontiers in pharmacology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Atrial fibrillation (AF) is the most common arrhythmia. Previous studies mainly focused on identifying potential diagnostic biomarkers and treatment strategies for AF, while few studies concentrated on post-operative AF (POAF), particularly using bioinformatics analysis and machine learning algorithms. Therefore, our study aimed to identify immune-associated genes and provide the competing endogenous RNA (ceRNA) network for POAF. Methods: Three GSE datasets were downloaded from the GEO database, and we used a variety of bioinformatics strategies and machine learning algorithms to discover candidate hub genes. These techniques included identifying differentially expressed genes (DEGs) and circRNAs (DECs), building protein-protein interaction networks, selecting common genes, and filtering candidate hub genes via three machine learning algorithms. To assess the diagnostic value, we then created the nomogram and receiver operating curve (ROC). MiRNAs targeting DEGs and DECs were predicted using five tools and the competing endogenous RNA (ceRNA) network was built. Moreover, we performed the immune cell infiltration analysis to better elucidate the regulation of immune cells in POAF. Results: We identified 234 DEGs (82 up-regulated and 152 down-regulated) of POAF Conclusion: We identified four immune-associated candidate hub genes (
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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.