Activation of AMP-activated Protein Kinase Inhibits Protein Synthesis Associated with Hypertrophy in the Cardiac Myocyte
Bibliographic record
Abstract
A necessary mediator of cardiac myocyte enlargement is protein synthesis, which is controlled at the levels of both translation initiation and elongation. Eukaryotic elongation factor-2 (eEF2) mediates the translocation step of peptide-chain elongation and is inhibited through phosphorylation by eEF2 kinase. In addition, p70S6 kinase can regulate protein synthesis by phosphorylating eEF2 kinase or via phosphorylation of ribosomal protein S6. We have recently shown that eEF2 kinase is also controlled by phosphorylation by AMP-activated protein kinase (AMPK), a key regulator of cellular energy homeostasis. Moreover, the mammalian target of rapamycin has also been shown to be inhibited, indirectly, by AMPK, thus leading to the inhibition of p70S6 kinase. Although AMPK activation has been shown to modulate protein synthesis, it is unknown whether AMPK could also be a regulator of cardiac hypertrophic growth. Therefore, we investigated the role of AMPK activation in regulating protein synthesis during both phenylephrine- and Akt-induced cardiac hypertrophy. Metformin and 5-aminoimidazole-4-carboxamide 1-beta-D-ribofuranoside were used to activate AMPK in neonatal rat cardiac myocytes. Activation of AMPK significantly decreased protein synthesis induced by phenylephrine treatment or by expression of constitutively active Akt. Activation of AMPK also resulted in decreased p70S6 kinase phosphorylation and increased phosphorylation of eEF2, suggesting that inhibition of protein synthesis involves the eEF2 kinase/eEF2 axis and/or the p70S6 kinase pathway. Together, our data suggest that the inhibition of protein synthesis by pharmacological activation of AMPK may be a key regulatory mechanism by which hypertrophic growth can be controlled.
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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) | 0.001 | 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".