The multidimensional role of calcium in atrial fibrillation pathophysiology: mechanistic insights and therapeutic opportunities
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its prevalence is increasing with the ageing of the population. Presently available treatment options are far from optimal and new insights into underlying mechanisms are needed to improve therapy. A variety of recent lines of research are converging to reveal important and relatively underappreciated multidimensional roles of cellular Ca(2+) content, distribution, and handling in AF pathophysiology. The objective of the present paper is to review the participation of changes in cell Ca(2+) and related processes in the mechanisms that lead to AF initiation and maintenance, and to consider the relevance of new knowledge in this area to therapeutic innovation. We first review the involvement of Ca(2+)-related functions in the principal arrhythmia mechanisms underlying AF: focal ectopic activity due to afterdepolarizations and re-entrant mechanisms. The detailed molecular pathophysiology of focal ectopic and re-entrant activity is then discussed in relationship to the participation of cell Ca(2+) changes and related Ca(2+)-handling and Ca(2+)-sensitive signalling systems. We then go on to consider the participation of Ca(2+)-related functions in electrical and structural remodelling processes leading to the AF substrate. Finally, we consider the implications for development of new arrhythmia management approaches and future research and development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".