Cardiac connexins as candidate genes for idiopathic atrial fibrillation
Bibliographic record
Abstract
PURPOSE OF REVIEW: Atrial fibrillation is the most common sustained cardiac arrhythmia and may cause significant morbidity. Current management strategies offer only modest success and may be associated with intolerable drug side effects or risk of procedural complications. As with other cardiac arrhythmias, the identification of genetic determinants predisposing to atrial fibrillation may provide novel molecular targets for drug development. This review discusses the role of cardiac connexins in the heart and suggests that genetic defects in cardiac connexins may predispose to arrhythmia vulnerability. RECENT FINDINGS: Animal models deficient in cardiac connexins demonstrate abnormalities in myocardial tissue conduction and vulnerability to re-entrant arrhythmias, including ventricular tachycardia and atrial fibrillation. Atrial tissue analyses from human patients with atrial fibrillation consistently demonstrate alterations in connexin distribution and protein levels, suggesting a role of connexins in the perpetuation of the arrhythmia. Most recently, genetic studies of Cx43 and Cx40 indicate that genetic variations in these genes may predispose to arrhythmia vulnerability in humans. SUMMARY: Current data support the critical role of cardiac connexins in mediating coordinated electrical activation and conduction through myocardial tissue. Alterations in the tissue distribution or function of cardiac connexins may predispose to cardiac arrhythmias, supporting a previously proposed hypothesis that cardiac connexins should be considered a major therapeutic target in the management of atrial fibrillation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".