DISSECTING THE SIGNALLING PATHWAYS INVOLVED IN THEANTI-HYPERTROPHIC EFFECTS OF RESVERATROL
Bibliographic record
Abstract
Background: Pathological left ventricular hypertrophy is associated with all-cause mortality; however, effective treatment for this condition is currently lacking. We have shown that activation of AMP-activated protein kinase (AMPK) by resveratrol can inhibit myocardial hypertrophy by decreasing protein synthesis and suppressing nuclear factor ofactivated T-cells (NFAT) activation. However, the mechanism by which resveratrol affects AMPK isunknown. Since LKB1 is the upstream kinase of AMPK, we hypothesize that resveratrol signals via LKB1 toactivate AMPK and it is this signalling pathway that contributes to the anti-hypertrophic effects of resveratrol. Methods: Wildtype (WT), LKB1 null, and AMPK null mouseembryonic fibroblasts (MEFs) were treated with vehicle or 100?M resveratrol for 1 h. Cell lysates were subjected to immunoblot analysis to examine the phosphorylation status of the proteins of interest. NFAT-dependent transcription was also measured in these MEFs using a NFAT-luciferase reporter transgene. Results: While resveratrol treatment increased AMPK phosphorylation in WT MEFs, resveratrol was unable to activate AMPK in LKB1 null MEFs. In addition, resveratrol suppressed NFAT-dependent transcription in WT MEFs, yet failed to inhibit NFAT activity in AMPK null MEFs. Conclusion: These data combined with our previous data suggest that resveratrol signals through LKB1 to activate AMPK and that this activation results in suppressed protein synthesis and reduced NFAT activation. As the development of pathologicalcardiac hypertrophy is dependent on protein synthesis and NFAT activation, inhibition of these two pathways by resveratrol may be an exciting new approach for the treatment of pathological cardiac hypertrophy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".