Abstract 4144530: IL-37 promotes resolution of Right Heart Disease-induced inflammation and atrial fibrillation.
Bibliographic record
Abstract
INTRODUCTION: Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Hypertension, obesity, diabetes or right heart disease (RHD) are important risk factors for AF. Inflammation stands as a common denominator among most AF risk factors. Studies have shown that patients with AF present high levels of circulating IL-18. Our group recently described that inflammation-resolution may prevent AF in RHD, however, the mechanism remains unclear. To inhibit IL-18-induced inflammation, IL37, a specific antagonist of IL-18-receptor was shown to attenuate cardiac fibrosis in a mice model of myocardial infarction, but little is known about its efficacy to prevent AF. HYPOTHESIS: IL-37 curbs RHD-induced atrial inflammation and AF vulnerability. METHODS: To induce right-sided cardiac hypertrophy and dilation, pulmonary artery banding (PAB) was performed in male and female Wistar rats (250-300g). Sham animals did not receive the ligation. Animals were randomized into four groups: Sham and PAB treated or not with IL37 (100 ng/ml/kg). Electrophysiological studies and echocardiography were performed in vivo before sacrifices at day (D)0, D7, D14 and D21. To analyze the atrial conduction, right atrial (RA) optical mapping was performed on Langendorff-perfused hearts. Histology, western blot, and qPCR were performed to study the expression of proteins and genes involved in atrial inflammation, fibrosis, and electrical remodeling. RESULTS: Twenty-one days after surgery, PAB rats were more vulnerable to AF and developed severe right-sided hypertrophy and dilation compared to Sham. Reliable to clinical evidence, female rats might be more resistant to AF than males. AF was associated with increased RA levels of inflammatory biomarkers including IL18, IL1β, and IL6. IL37 treatment was associated with decreased atrial expression of inflammatory markers. CONCLUSION: IL37 is a potential new therapeutic strategy to reduce atrial inflammation and prevent AF vulnerability in RHD.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".