Polydatin Protects Diabetic Heart against Ischemia‐Reperfusion Injury via Notch1/Hes1‐Mediated Activation of Pten/Akt Signaling
Bibliographic record
Abstract
Diabetes exacerbates oxidative/nitrative stress during myocardial ischemia‐reperfusion (MI/R) injury. Recent studies highlighted the cardioprotective actions of polydatin. However, its effect on diabetic MI/R injury and the underlying mechanisms remain unknown. This work was undertaken to evaluate the effect of polydatin on diabetic MI/R injury with a focus on Notch1/Hes1 signaling and myocardial oxidative/nitrative stress. Streptozotocin‐ (STZ‐) induced diabetic rats were administered with polydatin (20 mg/kg/d) in the absence or presence of DAPT (a γ ‐secretase inhibitor) or LY294002 (a PI3K/Akt inhibitor) and then subjected to MI/R injury. Polydatin administration preserved cardiac function and reduced myocardial infarct size. Moreover, polydatin ameliorated myocardial oxidative/nitrative stress damage as evidenced by decreased myocardial superoxide generation, malondialdehyde, gp91 phox expression, iNOS expression, NO metabolite level, and nitrotyrosine content and increased eNOS phosphorylation. However, these effects were blocked by DAPT administration. DAPT also inhibited the stimulatory effect of polydatin on the Notch1/Hes1‐Pten/Akt signaling pathway in a diabetic myocardium. Additionally, LY294002 not only abolished polydatin’s antiapoptotic effect but also reversed its inhibitory effect on myocardial oxidative/nitrative stress. Polydatin effectively reduced MI/R injury and improved left ventricular functional recovery under diabetic condition by ameliorating oxidative/nitrative stress damage. Importantly, Notch1/Hes1‐mediated activation of Pten/Akt signaling played a crucial role in this process.
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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 | 0.001 |
| 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".