Increased atrial arrhythmia susceptibility induced by intense endurance exercise in mice requires TNFα
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common supraventricular arrhythmia that, for unknown reasons, is linked to intense endurance exercise. Our studies reveal that 6 weeks of swimming or treadmill exercise improves heart pump function and reduces heart-rates. Exercise also increases vulnerability to AF in association with inflammation, fibrosis, increased vagal tone, slowed conduction velocity, prolonged cardiomyocyte action potentials and RyR2 phosphorylation (CamKII-dependent S2814) in the atria, without corresponding alterations in the ventricles. Microarray results suggest the involvement of the inflammatory cytokine, TNFα, in exercised-induced atrial remodelling. Accordingly, exercise induces TNFα-dependent activation of both NFκB and p38MAPK, while TNFα inhibition (with etanercept), TNFα gene ablation, or p38 inhibition, prevents atrial structural remodelling and AF vulnerability in response to exercise, without affecting the beneficial physiological changes. Our results identify TNFα as a key factor in the pathology of intense exercise-induced AF. Endurance exercise is associated with an increased risk of atrial fibrillation. Here, the authors show the adipokine TNFα is a crucial mediator of exercise-induced atrial fibrillation and irreversible atrial remodelling characterized by fibrosis and inflammation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".