IL‐10 promotes cardiomyocyte survival through the activation of Akt and transcription factor Stat3
Bibliographic record
Abstract
We have already reported that IL‐10 prevents TNF‐α induced increase in oxidative stress and apoptosis in cardiomyocytes. Present study investigated the role of Akt and Jak/Stat pathway in IL‐10 mediated survival of cardiomyocytes. Isolated cardiomyocytes from adult Sprague Dawley rats were exposed to TNF‐α (10ng/ml), IL‐10 (10ng/ml) and TNF‐α+IL‐10 (ratio 1) for 4h. Exposure to TNF‐α resulted in decrease in cell viability and an increase in cardiomyocyte apoptosis. IL‐10 by itself had no effect, but it prevented TNF‐α induced cardiomyocyte apoptosis and enhanced the cell survival. Furthermore, 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/or Stat3 inhibitor prevented IL‐10 modulation of TNF‐α induced cardiomyocyte apoptosis. Furthermore, in the presence of Akt inhibitor IL‐10 treatment was unable to induce Stat3 phosphorylation. It is concluded that Akt regulates IL‐10 mediated survival of cardiomyocytes by upregulating Stat3 phosphorylation (Supported by CIHR‐IMPACT, Canada).
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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) | 0.002 | 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".