Heat shock proteins as molecular targets for intervention in atrial fibrillation
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common sustained clinical tachyarrhythmia. AF is a progressive condition as demonstrated by the finding that maintenance of normal rhythm and contractile function becomes more difficult the longer AF exists. AF causes cellular stress, which induces atrial remodelling, involving reduction in the expression of L-type Ca(2+) channels and structural changes (myolysis), finally resulting in contractile dysfunction. Heat shock proteins (HSPs) comprise a family of proteins involved in the protection against different forms of cellular stress. Their classical function is the prevention of toxic protein aggregation by binding to (partially) unfolded proteins. Recent investigations reveal that HSPs prevent atrial remodelling and attenuate the promotion of AF in both cellular and animal experimental models. Furthermore, studies in humans suggest a protective role for HSPs against progression from paroxysmal AF to chronic, persistent AF. Therefore, manipulation of the HSP system may offer novel therapeutic approaches for the prevention of atrial remodelling. Such approaches may contribute to the maintenance or restoration of tissue integrity and contractile function. Ultimately, this concept may offer an additional treatment strategy to delay progression towards chronic AF and/or improve the outcome of cardioversion.
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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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".