Cardioprotection by Postconditioning Is Lost in WOKW Rats With Metabolic Syndrome: Role of Glycogen Synthase Kinase 3β
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Postconditioning by repetitive I/R cycles immediately after onset of reperfusion protects the heart. Metabolic disorders undermine the protection of preconditioning. The present study tested whether postconditioning protects hearts from rats with established metabolic syndrome [Wistar-Ottawa-Karlsburg W rats (WOKW)]. METHODS AND RESULTS: After 28 weeks of age, WOKW rats were much heavier than DA (Dark Agouti) and Wistar control rats and showed the pattern of the metabolic syndrome. Postconditioning was performed by 3 30-second cycles of reperfusion/ischemia immediately after the regional ischemia (30 minutes). Infarct size was comparable in all control hearts from DA, Wistar, and WOKW rats (58 +/- 2%, 49 +/- 3%; 49 +/- 2%, respectively). Postconditioning significantly reduced the infarct size in DA rats (39 +/- 5%) and Wistar rats (29 +/- 3%). In WOKW rats, the infarct sparing effect of postconditioning was lost (43 +/- 4%).GSK-3beta and Erk are involved in the signaling of postconditioning. Therefore, the phosphorylation of these proteins was determined by Western blot analysis. Postconditioning significantly increased the phosphorylation of GSK-3beta in DA and Wistar rats (1.6-fold in DA rats, 2.3-fold in Wistar rats, P < 0.05) but failed to do so in WOKW rats. Similarly, a trend for an increased phosphorylation of Erk was found in DA rats but not in WOKW rats. Thus the inefficacy of postconditioning in reducing infarct size in rats with metabolic syndrome is paralleled by a lack of phosphorylation of GSK-3beta and Erk. CONCLUSION: The metabolic syndrome, as shown in this animal model, completely abrogates the postconditioning. This blockade involves the phosphorylation of GSK-3beta. Further studies have to evaluate whether this block of postconditioning makes patients with a metabolic syndrome more susceptible to myocardial damage after infarction.
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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".