Atrial cardiomyocytes contribute to the inflammatory status associated with atrial fibrillation in right heart disease
Bibliographic record
Abstract
AIMS: Right heart disease (RHD), characterized by right ventricular (RV) and atrial (RA) hypertrophy, and cardiomyocytes' (CM) dysfunctions have been described to be associated with the incidence of atrial fibrillation (AF). Right heart disease and AF have in common, an inflammatory status, but the mechanisms relating RHD, inflammation, and AF remain unclear. We hypothesized that right heart disease generates electrophysiological and morphological remodelling affecting the CM, leading to atrial inflammation and increased AF susceptibility. METHODS AND RESULTS: Pulmonary artery banding (PAB) was surgically performed (except for sham) on male Wistar rats (225-275 g) to provoke an RHD. Twenty-one days (D21) post-surgery, all rats underwent echocardiography and electrophysiological studies (EPS). Optical mapping was performed in situ, on Langendorff-perfused hearts. The contractility of freshly isolated CM was evaluated and recorded during 1 Hz pacing in vitro. Histological analyses were performed on formalin-fixed RA to assess myocardial fibrosis, connexin-43 levels, and CM morphology. Right atrial levels of selected genes and proteins were obtained by qPCR and Western blot, respectively. Pulmonary artery banding induced severe RHD identified by RV and RA hypertrophy. Pulmonary artery banding rats were significantly more susceptible to AF than sham. Compared to sham RA CM from PAB rats were significantly elongated and hypercontractile. Right atrial CM from PAB animals showed significant augmentation of mRNA and protein levels of pro-inflammatory interleukin (IL)-6 and IL1β. Sarcoplasmic-endoplasmic reticulum Ca2+-ATPase-2a (SERCA2a) and junctophilin-2 were decreased in RA CM from PAB compared to sham rats. CONCLUSIONS: Right heart disease-induced arrhythmogenicity may occur due to dysfunctional SERCA2a and inflammatory signalling generated from injured RA CM, which leads to an increased risk of AF.
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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) | 0.001 | 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".