Tyrosol Prevents Ischemia/Reperfusion-Induced Cardiac Injury in H9c2 Cells: Involvement of ROS, Hsp70, JNK and ERK, and Apoptosis
Bibliographic record
Abstract
Ischemia-Reperfusion (I/R) injury causes ROS overproduction, creating oxidative stress, and can trigger myocyte death, resulting in heart failure. Tyrosol is an antioxidant abounded in diets and medicine. Our objective was to investigate the protective effect of tyrosol on I/R-caused mortality in H9c2 cardiomyocytes through its influence on ROS, Hsp70, ERK, JNK, Bcl-2, Bax and caspase-8. A simulated I/R model was used, myocytes loss was examined by MTT, and ROS levels were measured using DCFH-DA. Nuclear condensation and caspase-3 activity were assessed by DAPI staining and fluorometric assay. Phosphorylated ERK and JNK were determined by electrochemiluminescent ELISA, and Hsp70, Bcl-2, Bax and caspase-8 were examined by Western blotting. Results show that tyrosol salvaged myocyte loss, inhibited nuclear condensation and caspase-3 activity dose-dependently, indicating its protection against I/R-caused myocyte loss. Furthermore, tyrosol significantly inhibited ROS accumulation and activation of ERK and JNK, augmenting Hsp70 expression. Besides, tyrosol inhibited I/R-induced apoptosis, associated with retained anti-apoptotic Bcl-2 protein, and attenuated pro-apoptotic Bax protein, resulting in a preservation of Bcl-2/Bax ratio. Finally, tyrosol notably decreased cleaved caspase-8 levels. In conclusion, cytoprotection of tyrosol in I/R-caused myocyte mortality was involved with the mitigation of ROS, prohibition of the activation of ERK, JNK and caspase-8, and elevation of Hsp70 and Bcl-2/Bax ratio.
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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".