Akt Activity Negatively Regulates Phosphorylation of AMP-activated Protein Kinase in the Heart
Bibliographic record
Abstract
In the heart, insulin stimulates a variety of kinase cascades and controls glucose utilization. Because insulin is able to activate Akt and inactivate AMP-activated protein kinase (AMPK) in the heart, we hypothesized that Akt can regulate the activity of AMPK. To address the potential existence of this novel signaling pathway, we used a number of experimental protocols to activate Akt in cardiac myocytes and monitored the activation status of AMPK. Mouse hearts perfused in the presence of insulin demonstrated accelerated glycolysis and glucose oxidation rates as compared with non-insulin-perfused hearts. In addition, insulin caused an increase in Akt phosphorylation and a decrease in AMPK phosphorylation at its major regulatory site (threonine 172 of the alpha catalytic subunit). Transgenic mice overexpressing a constitutively active mutant form of Akt1 displayed decreased phosphorylation of cardiac alpha-AMPK. Isolated neonatal cardiac myocytes infected with an adenovirus expressing constitutively active mutant forms of either Akt1 or Akt2 also suppressed AMPK phosphorylation. However, Akt-dependent depression of alpha-AMPK phosphorylation could be overcome in the presence of the AMPK activator, metformin, suggesting that an override mechanism exists that can restore AMPK activity. Taken together, this study suggests that there is cross-talk between the AMPK and Akt pathways and that Akt activation can lead to decreased AMPK activity. In addition, our data suggest that the ability of insulin to inhibit AMPK may be controlled via an Akt-mediated 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".