MicroRNAs and atrial fibrillation: new fundamentals
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most commonly encountered clinical arrhythmia associated with pronounced morbidity, mortality, and socio-economic burden. This pathological entity is associated with an altered expression profile of genes that are important for atrial function. MicroRNAs (miRNAs), a new class of non-coding mRNAs of around 22 nucleotides in length, have rapidly emerged as one of the key players in the gene expression regulatory network. The potential roles of miRNAs in controlling AF have recently been investigated. The studies have provided some promising results for our better understanding of the molecular mechanisms of AF. In this review article, we provide a synopsis of the studies linking miRNAs to cardiac excitability and other processes pertinent to AF. To introduce the main topic, we discuss basic knowledge about miRNA biology and our current understanding of mechanisms for AF. The most up-to-date research data on the possible roles of miRNAs in AF initiation and maintenance are presented, and the available experimental results on miRNA and AF are discussed. Some speculations pertinent to the subject are made. Finally, perspectives on future directions of research on miRNAs in AF are provided.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".