Tanshinone IIA protects against sudden cardiac death induced by lethal arrhythmias via repression of microRNA‐1
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Tanshinone IIA is an active component of a traditional Chinese medicine based on Salvia miltiorrhiza, which reduces sudden cardiac death by suppressing ischaemic arrhythmias. However, the mechanisms underlying the anti-arrhythmic effects remain unclear. EXPERIMENTAL APPROACH: A model of myocardial infarction (MI) in rats by ligating the left anterior descending coronary artery was used. Tanshinone IIA or quinidine was given daily, before (7 days) and after (3 months) MI; cardiac electrical activity was monitored by ECG recording. Whole-cell patch-clamp techniques were used to measure the inward rectifying K(+) current (I(K1)) in rat isolated ventricular myocytes. Kir2.1 and serum response factor (SRF) levels were analysed by Western blot and microRNA-1 (miR-1) level was determined by real-time RT-PCR. KEY RESULTS: Tanshinone IIA decreased the incidence of arrhythmias induced by acute cardiac ischaemia and mortality in rats 3 months after MI. Tanshinone IIA restored the diminished I(K1) current density and Kir2.1 protein after MI in rat ventricular myocytes, while quinidine further inhibited I(K1)/Kir2.1. MiR-1 was up-regulated in MI, possibly due to the concomitant increase in SRF, a transcriptional activator of the miR-1 gene, accounting for decreased Kir2.1. Treatment with tanshinone IIA prevented increased SRF and hence increased miR-1 post-MI, whereas quinidine did not. CONCLUSIONS AND IMPLICATIONS: Down-regulation of miR-1 and consequent recovery of Kir2.1 may account partially for the efficacy of tanshinone IIA in suppressing ischaemic arrhythmias and cardiac mortality. These finding support the proposal that miR-1 could be a potential therapeutic target for the prevention of ischaemic arrhythmias.
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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) | 0.001 | 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) | 0.002 | 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".