The cardioprotection of dihydrotanshinone I against myocardial ischemia–reperfusion injury via inhibition of arachidonic acid ω-hydroxylase
Bibliographic record
Abstract
Arachidonic acid (AA) is a precursor that is metabolized by several enzymes to many biological eicosanoids. Accumulating data indicate that the ω-hydroxylation metabolite of AA, 20-hydroxyeicosatetraenoic acid (20-HETE), is considered to be involved in the myocardial ischemia-reperfusion injury (MIRI). The inhibitors of AA ω-hydroxylase, however, are demonstrated to exhibit protective effects on MIRI. Dihydrotanshinone I (DI), a bioactive constituent of danshen, is proven to be a potent inhibitor of AA ω-hydroxylase by our preliminary study in vitro. The purpose of the present study was to investigate the cardioprotection of DI against MIRI and its effects on the concentrations of 20-HETE in vivo. Rats subjected to 30 min of ischemia followed by 24 h of reperfusion were assigned to intravenously receive vehicle (sham and ischemia-reperfusion), low (1 mg/kg), middle (2 mg/kg), or high (4 mg/kg) doses of DI before reperfusion. The results demonstrated that DI treatment could improve cardiac function, reduce infarct size, ameliorate the variations in myocardial zymogram and histopathological disorders, decrease 20-HETE generation, and regulate apoptosis-related protein in myocardial ischemia-reperfusion rats. These findings suggested DI could exert considerable cardioprotective action on MIRI by the attenuation of 20-HETE generation, subsequent myocardial injury, and apoptosis through inhibition on AA ω-hydroxylase.
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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) | 0.001 | 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) | 0.001 | 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".