Macrophage-mediated IL-6 signaling drives ryanodine receptor–2 calcium leak in postoperative atrial fibrillation
Bibliographic record
Abstract
Postoperative atrial fibrillation (poAF) is AF occurring days after surgery, with a prevalence of 33% among patients undergoing open-heart surgery. The degree of postoperative inflammation correlates with poAF risk, but less is known about the cellular and molecular mechanisms driving postoperative atrial arrhythmogenesis. We performed single-cell RNA-seq comparing atrial nonmyocytes from mice with and without poAF, which revealed infiltrating CCR2+ macrophages to be the most altered cell type. Pseudotime trajectory analyses identified Il-6 as a gene of interest driving in macrophages, which we confirmed in pericardial fluid collected from human patients after cardiac surgery. Indeed, macrophage depletion and macrophage-specific Il6ra conditional knockout (cKO) prevented poAF in mice. Downstream STAT3 inhibition with TTI-101 and cardiomyocyte-specific Stat3 cKO rescued poAF, indicating a proarrhythmogenic role of STAT3 in poAF development. Confocal imaging in isolated atrial cardiomyocytes (ACMs) uncovered what we believe to be a novel link between STAT3 and CaMKII-mediated ryanodine receptor-2 (RyR2)-Ser(S)2814 phosphorylation. Indeed, nonphosphorylatable RyR2S2814A mice were protected from poAF, and CaMKII inhibition prevented arrhythmogenic Ca2+ mishandling in ACMs from mice with poAF. Altogether, we provide multiomic, biochemical, and functional evidence from mice and humans that IL-6-STAT3-CaMKII signaling driven by infiltrating atrial macrophages is a pivotal driver of poAF, which portends therapeutic utility for poAF prevention.
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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 | 0.000 |
| 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".