Akt Regulates IL-10 Mediated Suppression of TNFα-Induced Cardiomyocyte Apoptosis by Upregulating Stat3 Phosphorylation
Bibliographic record
Abstract
BACKGROUND: We have already reported that TNF-α increases cardiomyocyte apoptosis and IL-10 treatment prevented these effects of TNF-α. Present study investigates the role of Akt and Jak/Stat pathway in the IL-10 modulation of TNF-α induced cardiomyocyte apoptosis. METHODOLOGY/PRINCIPAL FINDINGS: Cardiomyocytes isolated from adult Sprague Dawley rats were exposed to TNF-α (10 ng/ml), IL-10 (10 ng/ml) and TNF-α+IL-10 (ratio 1) for 4 h. Exposure to TNF-α resulted in an increase in cardiomyocyte apoptosis as measured by flow cytometry and TUNEL assay. IL-10 by itself had no effect, but it prevented TNF-α induced apoptosis. IL-10 treatment increased Akt levels within cardiomyocytes and this change was associated with an increase in Jak1 and Stat3 phosphorylation. Pre-exposure of cells to Akt inhibitor prevented IL-10 induced Stat3 phosphorylation. Furthermore, in the presence of Akt or Stat3 inhibitor, IL-10 treatment was unable to block TNF-α induced cardiomyocyte apoptosis. CONCLUSION: It is suggested that IL-10 modulation of TNF-α induced cardiomyocyte apoptosis is mediated by Akt via Stat3 activation.
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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) | 0.003 | 0.001 |
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".