Myocardial Ischemia Differentially Regulates LKB1 and an Alternate 5′-AMP-activated Protein Kinase Kinase
Bibliographic record
Abstract
During myocardial ischemia, activation of 5'-AMP-activated protein kinase (AMPK) leads to the stimulation of glycolysis and fatty acid oxidation. Together these metabolic changes contribute to cardiac dysfunction. Although AMPK signaling in the ischemic heart is well characterized, the relative contribution of phosphorylation by AMPK kinase (AMPKK), and positive allosterism by the ratios of AMP:ATP and creatine (Cr):phosphocreatine (PCr), in stimulating AMPK during ischemia are unknown. In hearts subjected to severe ischemia, the ratios of AMP:ATP and Cr:PCr were significantly elevated as compared with aerobic hearts. Severe ischemia stimulated AMPK signaling, as demonstrated by an increase in both AMPK activity and acetyl-CoA carboxylase phosphorylation. Although AMPK phosphorylation was increased by severe ischemia, the protein abundance and activity of the recently identified AMPKK, LKB1, were similar between aerobic and severely ischemic hearts. However, in contrast to LKB1, the activity of AMPKK was stimulated in severely ischemic hearts. To further delineate the relative roles of positive allosterism and AMPKK in the regulation of AMPK during ischemia, hearts were subjected to mild ischemia. Although mild ischemia did not alter the ratios of AMP:ATP and Cr:PCr, mild ischemia increased AMPK activity and increased AMPK phosphorylation. Mild ischemia also stimulated the activity of AMPKK. In summary, we demonstrate that myocardial ischemia stimulates AMPK via an AMPKK other than LKB1. Additionally, we show that changes in high energy phosphates are not essential for the activation of AMPK by ischemia. Our data emphasize the critical role AMPKK plays in mediating AMPK signaling during myocardial ischemia.
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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 | 0.000 | 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) | 0.000 | 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".