AMPK as a metabolic switch in rat muscle, liver and adipose tissue after exercise
Bibliographic record
Abstract
UNLABELLED: An increasing body of evidence has revealed that activation of adenosine monophosphate (AMP)-activated protein kinase (AMPK)-activated protein kinase increases fatty acid oxidation by lowering the concentration of malonyl coenzyme A (CoA), an inhibitor of carnitine palmitoyl transferase 1. Studies carried out primarily in skeletal muscle suggest that AMPK modulates the concentration of malonyl CoA by concurrently phosphorylating and inhibiting acetyl CoA carboxylase (ACC), the rate limiting enzyme in malonyl CoA synthesis, and phosphorylating and activating malonyl CoA decarboxylase (MCD), an enzyme involved in its degradation. We have recently observed that AMPK and MCD activities are increased and ACC activity diminished in skeletal muscle, liver and, surprisingly, in adipose tissue 30 min following exercise (treadmill run) in normal rats. In liver and adipose tissue these changes were associated with a decrease in the activity of glycerol-3-phosphate acyltransferase (GPAT), which catalyses the first committed reaction in glycerolipid synthesis and, which like ACC, is phosphorylated and inhibited by AMPK. Similar changes in ACC, MCD and GPAT were observed following the administration of 5-aminoimidazole 4-carboxamide-riboside (AICAR), further indicating that the exercise-induced alterations in these enzymes were AMPK-mediated. CONCLUSIONS: (1) AMPK plays a major role in regulating lipid metabolism in multiple tissues following exercise. (2) The net effect of its activation is to increase fatty acid oxidation and diminish glycerolipid synthesis. (3) The relevance of these findings to the regulation of muscle glycogen repletion in the post-exercise state and to the demonstrated ability of AMPK activation to decrease adiposity and increase insulin sensitivity in rodents remains to be determined.
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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) | 0.002 | 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".