Insulin Preconditioning Elevates p-Akt and Cardiac Contractility after Reperfusion in the Isolated Ischemic Rat Heart
Bibliographic record
Abstract
Insulin induces cardioprotection partly via an antiapoptotic effect. However, the optimal timing of insulin administration for the best quality cardioprotection remains unclear. We tested the hypothesis that insulin administered prior to ischemia provides better cardioprotection than insulin administration after ischemia. Isolated rat hearts were prepared using Langendorff method and divided into three groups. The Pre-Ins group (Pre-Ins) received 0.5 U/L insulin prior to 15 min no-flow ischemia for 20 min followed by 20 min of reperfusion. The Post-Ins group (Post-Ins) received 0.5 U/L insulin during the reperfusion period only. The control group (Control) was perfused with KH buffer throughout. The maximum of left ventricular derivative of pressure development (dP/dt(max)) was recorded continuously. Measurements of TNF-α and p-Akt in each time point were assayed by ELISA. After reperfusion, dP/dt(max) in Pre-Ins was elevated, compared with Post-Ins at 10 minutes after reperfusion and Control at all-time points. TNF-α levels at 5 minutes after reperfusion in the Pre-Ins were lower than the others. After 5 minutes of reperfusion, p-Akt was elevated in Pre-Ins compared with the other groups. Insulin administration prior to ischemia provides better cardioprotection than insulin administration only at reperfusion. TNF-α suppression is possibly mediated via p-Akt leading to a reduction in contractile myocardial dysfunction.
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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) | 0.001 | 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".