A High-Protein Diet Promotes Atrial Arrhythmogenesis via Absent-in-Melanoma 2 Inflammasome
Bibliographic record
Abstract
High-protein diets (HPDs) offer health benefits, such as weight management and improved metabolic profiles. The effects of HPD on cardiac arrhythmogenesis remain unclear. Atrial fibrillation (AF), the most common arrhythmia, is associated with inflammasome activation. The role of the Absent-in-Melanoma 2 (AIM2) inflammasome in AF pathogenesis remains unexplored. In this study, we discovered that HPD increased susceptibility to AF. To demonstrate the involvement of AIM2 signaling in the pathogenesis of HPD-induced AF, wildtype (WT) and Aim2−/− mice were fed normal-chow (NC) and HPD, respectively. Four weeks later, inflammasome activity was upregulated in the atria of WT-HPD mice, but not in the Aim2−/−-HPD mice. The increased AF vulnerability in WT-HPD mice was associated with abnormal sarcoplasmic reticulum (SR) Ca2+-release events in atrial myocytes. HPD increased the cytoplasmic double-strand (ds) DNA level, causing AIM2 activation. Genetic inhibition of AIM2 in Aim2−/− mice reduced susceptibility to AF, cytoplasmic dsDNA level, mitochondrial ROS production, and abnormal SR Ca2+-release in atrial myocytes. These data suggest that HPD creates a substrate conducive to AF development by activating the AIM2-inflammasome, which is associated with mitochondrial oxidative stress along with proarrhythmic SR Ca2+-release. Our data imply that targeting the AIM2 inflammasome might constitute a novel anti-AF strategy in certain patient subpopulations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".