Regulation of AMP-activated protein kinase and acetyl-CoA carboxylase phosphorylation by palmitate in skeletal muscle cells
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of long-chain fatty acids (LCFAs) on AMP-activated protein kinase (AMPK) and acetyl-coenzyme A carboxylase (ACC) phosphorylation and beta-oxidation in skeletal muscle. L6 rat skeletal muscle cells were exposed to various concentrations of palmitate (1-800 microM). Subsequently, ACC and AMPK phosphorylation and fatty acid oxidation were measured. A 2-fold increase in both AMPK and ACC phosphorylation was observed in the presence of palmitate concentrations as low as 10 microM, which was also accompanied by a significant increase in fatty acid oxidation. The effect of palmitate on AMPK and ACC phosphorylation was dose-dependent, reaching maximum increases of 3.5- and 4.5-fold, respectively. Interestingly, ACC phosphorylation was coupled with AMPK activation at palmitate concentrations ranging from 10 to 100 microM; however, at concentrations >200 microM, ACC phosphorylation and fatty acid oxidation remained high even after AMPK phosphorylation was completely prevented by the use of a selective AMPK inhibitor. This indicates that LCFAs regulate ACC activity by AMPK-dependent and -independent mechanisms, based on their abundance in skeletal muscle cells. Here, we provide novel evidence that the AMPK/ACC pathway may operate as a mechanism to sense and respond to the lipid energy charge of skeletal muscle cells.
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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 | 0.001 |
| 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 | 0.001 |
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".