ArticleFrontiers in immunology2026
Potential of
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute myocardial infarction (AMI) is a global health burden. Ferroptosis drives cardiomyocyte death, but specific ferroptosis-related genes (FRGs) and pathways underlying ischemic injury remain unclear. Methods: First, differentially expressed mRNAs (DE-mRNAs) from GSE61144 were intersected with FRGs to obtain differentially expressed ferroptosis-related genes (DE-FRGs). Subsequently, GO/KEGG functional enrichment, PPI network construction, expression heatmap visualization and tissue-specific expression were performed on DE-FRGs to clarify their biological characteristics. To explore the potential causal relationship between DE-FRGs and AMI, we conducted summary-data-based Mendelian randomization (SMR) analysis in four cardiovascular-related tissues and performed Bayesian colocalization analysis, ultimately identifying a key transcription factor (TF). With this TF as the hub, a miRNA-TF-mRNA regulatory network was constructed. Based on this pathway, we conducted a series of analyses, including prediction of transcription factor binding sites, GSEA and GeneMANIA analysis, prediction of gene-diseases and gene-drugs associations, phenome-wide association study (PheWAS), ROC curve assessment and RT-qPCR validation, thereby systematically elucidating the molecular mechanisms of this pathway in AMI. Results: The SMR analysis showed that one key TF- Conclusions: In this study, by integrating transcriptomic, SMR and PheWAS analysis, we first established a robust causal association between
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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 Socratic graph.