Resveratrol Prevents the Prohypertrophic Effects of Oxidative Stress on LKB1
Bibliographic record
Abstract
BACKGROUND: Master regulators of protein synthesis such as mammalian target of rapamycin (mTOR) and p70S6 kinase contribute to left ventricular hypertrophy. These prohypertrophic pathways are modulated by a number of kinase cascades, including the hierarchical LKB1/AMP-activated protein kinase (AMPK) energy-sensing pathway. Because oxidative stress inhibits the LKB1/AMPK signaling axis to promote abnormal cell growth in cancer cells, we investigated whether oxidative stress associated with hypertension also results in the inhibition of this kinase circuit to contribute to left ventricular hypertrophy. METHODS AND RESULTS: In the spontaneously hypertensive rat, a well-established genetic model of hypertension and subsequent cardiac hypertrophy, the development of left ventricular hypertrophy is associated with an increase in the electrophilic lipid peroxidation byproduct 4-hydroxy-2-nonenal (HNE). Using isolated cardiomyocytes, we show that elevated levels of HNE result in the formation of HNE-LKB1 adducts that inhibit LKB1 and subsequent AMPK activity. Consistent with inhibition of the LKB1/AMPK signaling pathway, the mTOR/p70S6 kinase system is activated, which is permissive for cardiac myocyte cell growth. Treatment of cardiomyocytes with resveratrol prevents HNE modification of the LKB1/AMPK signaling axis and blunts the prohypertrophic p70S6 kinase response. Furthermore, administration of resveratrol to spontaneously hypertensive rats results in increased AMPK phosphorylation and activity and reduced left ventricular hypertrophy. CONCLUSIONS: Our data identify a molecular mechanism in the cardiomyocyte involving the oxidative stress-derived lipid peroxidation byproduct HNE and the LKB1/AMPK signaling pathway that contributes to the development of left ventricular hypertrophy. We also suggest that resveratrol may be a potential therapy for patients at risk for developing pathological cardiac hypertrophy by preventing this prohypertrophic process.
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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".