IL-10 attenuates TNF- -induced NF B pathway activation and cardiomyocyte apoptosis
Bibliographic record
Abstract
AIMS: We have recently reported that tumour necrosis factor-alpha (TNF-alpha) increases oxidative stress and apoptosis in cardiomyocytes by upregulating p38 mitogen-activated protein (MAP) kinase (MAPK) phosphorylation. Interleukin-10 (IL-10) blocked these effects of TNF-alpha by upregulating extracellular signal-regulated kinase 1/2 (ERK 1/2) MAPK phosphorylation. However, the precise site of this IL-10 action is still unknown, and this is investigated in the present study. METHODS AND RESULTS: Cardiomyocytes isolated from adult Sprague-Dawley rats were exposed to TNF-alpha (10 ng/mL), IL-10 (10 ng/mL), and IL-10+TNF-alpha (ratio 1) for 4 h. Hydrogen peroxide and antioxidant trolox were used as positive controls. Exposure to TNF-alpha resulted in an increase in the production of reactive oxygen species, the number of apoptotic cells, caspase-3 activation, and poly-ADP ribose polymerase (PARP) cleavage. Increased oxidative stress by using hydrogen peroxide also caused apoptosis. The changes due to TNF-alpha were associated with an increase in the inhibitor of kappaB kinase (IKK) and nuclear factor kappa-B (NF kappaB) phosphorylation. IL-10 by itself had no effect, but it prevented the above mentioned TNF-alpha-induced changes. Trolox also mitigated TNF-alpha induced changes. Pre-exposure of cells to an IKK inhibitor (PS-1145) prevented TNF-alpha-induced caspase-3 and PARP cleavage. Inhibition of ERK 1/2 MAPK with PD98059 attenuated the protective role of IL-10 against TNF-alpha-induced activation of IKK and NF kappaB as well as cardiomyocyte apoptosis. CONCLUSION: The present study shows that TNF-alpha-induced activation of the NF kappaB pathway plays a critical role in cardiomyocyte apoptosis. IL-10 prevents TNF-alpha-induced NF kappaB activation and pro-apoptotic changes in cardiomyocytes by inhibiting IKK phosphorylation through the activation of ERK 1/2 MAPK.
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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".