AMP-Activated Protein Kinase Is Not Down-Regulated in Human Skeletal Muscle of Obese Females
Bibliographic record
Abstract
Obesity in humans is associated with lipid accumulation in skeletal muscle, insulin and leptin resistance, and type 2 diabetes. AMP-activated protein kinase (AMPK) is an important regulator of fatty acid (FA) metabolism in skeletal muscle. To address the hypothesis that lipid accumulation in skeletal muscle of obese subjects may be due to down-regulation of AMPK, we measured mRNA and protein levels of AMPK isoforms, AMPKalpha1 and -alpha2 activity, AMPK kinase activity, acetyl-coenzyme A carboxylase (ACCbeta) expression and phosphorylation, and FA metabolism in biopsies of rectus abdominus muscle from lean and obese women. We also examined the effect of 5-aminoimidazole-4-carboxamide riboside (AICAR) on AMPK activity and the effects of AICAR and leptin on FA metabolism. Skeletal muscle of obese subjects had increased total FA uptake and triglyceride esterification, and leptin failed to stimulate FA oxidation. However, AMPK mRNA and protein expression, AMPKalpha1 and -alpha2 activities, AMPK kinase activity, ACCbeta phosphorylation, and FA oxidation were similar in lean and obese subjects. Moreover, AICAR increased AMPKalpha2 activity, ACCbeta phosphorylation, and palmitate oxidation to a similar degree in muscle from lean and obese subjects. We conclude that the abnormal lipid metabolism and leptin resistance of skeletal muscle of obese subjects is not due to down-regulation of AMPK. In addition, the similar stimulation by AICAR of AMPK in skeletal muscle of lean and obese subjects suggests that direct pharmacological activation of AMPK may be a therapeutic approach for stimulating FA oxidation in the treatment of human obesity.
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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) | 0.004 | 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".