Calcitonin signalling system regulates function and arhythmogenicity of atrial cardiomyocytes
Bibliographic record
Abstract
Abstract Background Atrial fibrillation (AF) poses a significant therapeutic challenge due to myocardial remodelling, involving both structural and electrical alterations. Recent investigations have shed light on the role of atrial cardiomyocytes (CMs) in secreting Calcitonin (CT), a factor crucial for maintaining atrial tissue integrity. Dysregulated CT secretion in AF showed to contribute to fibrotic tissue production by atrial fibroblasts, exacerbating arrhythmogenesis [1]. However, the direct impact of CT on CM function and arrhythmogenicity remains unclear, driving the objectives of our study. Methods/Results Serum samples from 20 cardiac surgery patients revealed a noteworthy association between higher pre-operative CT levels and a significant ~2.8-fold reduction in the incidence of post-operative AF (poAF). Using freshly isolated atrial guinea pig CMs, confirmed (by qPCR and immunofluorescence) that CMs express CT-receptor (CTR) to enable CT actions in the cell. Functional studies found that CT administration inhibits spontaneous calcium (Ca2+)-release events induced by pacing and decreases the Ca2+ transients amplitude (at 2 Hz; IonOptix μstep system) in fura2-loaded CMs (n=22 cells) in a concentration-dependent manner. Atrial iPSC-CMs transduced with global RGECO sensor (Genetically encoded Ca2+ indicator) and treated with 15 pM CT showed a reduction in the beat rate when paced at 2Hz, and a significantly increased the time to 50% baseline. Evaluation of the expression and phosphorylation of selected Ca2+ handling proteins, which may potentially account for the observed changes in Ca2+ transients, showed no differences in total or phospho-(ser2808) ryanodine receptor, and SERCA2α in response to CT but an increase in phospho-(Ser16) Phospholamban. Conclusion Our findings highlight the effects of CT on atrial CM function. Maintaining physiological CT levels offer a promising approach for managing AF clinically, potentially through the use of already in clinical use CT-analogues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".