AMP-activated protein kinase confers protection against TNF-α-induced cardiac cell death
Bibliographic record
Abstract
AIMS: Although a substantial role for 5' adenosine monophosphate-activated protein kinase (AMPK) has been established in regulating cardiac metabolism, a less studied action of AMPK is its ability to prevent cardiac cell death. Using established AMPK activators like dexamethasone (DEX) or metformin (MET), the objective of the present study was to determine whether AMPK activation prevents tumour necrosis factor-alpha (TNF-alpha) induced apoptosis in adult rat ventricular cardiomyocytes. METHODS AND RESULTS: Cardiomyocytes were incubated with DEX, MET, or TNF-alpha for varying durations (0-12 h). TNF-alpha-induced cell damage was evaluated by measuring caspase-3 activity and Hoechst staining. Protein and gene estimation techniques were employed to determine the mechanisms mediating the effects of AMPK activators on TNF-alpha-induced cardiomyocyte apoptosis. Incubation of myocytes with TNF-alpha for 8 h has increased caspase-3 activation and apoptotic cell death, an effect that was abrogated by DEX and MET. The beneficial effect of DEX and MET was associated with stimulation of AMPK, which led to a rapid and sustained increase in Bad phosphorylation. This event reduced the interaction between Bad and Bcl-xL, limiting cytochrome c release and caspase-3 activation. Addition of Compound C to inhibit AMPK reduced Bad phosphorylation and prevented the beneficial effects of AMPK against TNF-alpha-induced cytotoxicity. CONCLUSION: Our data demonstrate that although DEX and MET are used as anti-inflammatory agents or insulin sensitizers, respectively, their common property to phosphorylate AMPK promotes cardiomyocyte cell survival through its regulation of Bad and the mitochondrial apoptotic mechanism.
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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".