Effects of a heat shock protein inducer on the atrial fibrillation substrate caused by acute atrial ischaemia
Bibliographic record
Abstract
AIMS: Heat shock proteins (HSPs) are a set of endogenous cytoprotective factors activated by various pathological conditions. This study addressed the effects of geranylgeranylacetone (GGA), an orally active HSP inducer, on the atrial fibrillation (AF) substrate associated with acute atrial ischaemia (AI). METHODS AND RESULTS: Four groups of mongrel dogs were studied: (1) a group subjected to AI without GGA (AI-CTL, n = 13 dogs); (2) dogs that underwent AI after GGA pretreatment (120 mg/kg/day; AI-GGA, n = 12); (3) dogs receiving GGA pretreatment without AI (n = 5); (4) control dogs for tissue sampling (n = 5). Isolated right AI was produced by occluding a right atrial (RA) coronary-artery branch. AI reduced ischaemic-zone conduction velocity (CV, from 94 +/- 3 to 46 +/- 5 cm/s; P < 0.01) and increased maximum local phase delays (P95, from 1.6 +/- 0.1 to 4.6 +/- 0.6 ms/mm; P < 0.01), conduction heterogeneity index (CHI, from 0.7 +/- 0.1 to 2.9 +/- 0.5; P < 0.01), and the mean duration of burst pacing-induced AF (DAF, from 44 +/- 18 to 890 +/- 323 s; P < 0.01) in AI-CTL dogs. GGA pretreatment attenuated ischaemia-induced conduction abnormalities (CV, 77 +/- 8 cm/s; P95, 2.1 +/- 0.4 ms/mm; CHI, 1.1 +/- 0.2; all P < 0.01 vs. AI-CTL) and DAF (328 +/- 249 s; P < 0.01) in AI-GGA dogs. GGA treatment alone, without ischaemia, did not alter DAF or conduction indices. AI slightly prolonged atrial refractory period, an effect also prevented by GGA. GGA significantly increased HSP70 protein expression in RA tissues of ischaemic hearts. CONCLUSIONS: GGA prevents ischaemia-induced atrial conduction abnormalities and suppresses ischaemia-related AF. These results suggest that HSP induction might be a useful new anti-AF intervention for patients with coronary artery disease.
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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 | 0.000 |
| 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".