Stimulatory effects of leptin and muscle contraction on fatty acid metabolism are not additive
Bibliographic record
Abstract
Leptin has been shown to acutely stimulate fatty acid oxidation and triacylglycerol hydrolysis in skeletal muscle. These effects are similar to those induced by muscle contraction alone. Several studies have demonstrated that, during aerobic exercise, plasma leptin concentrations are well maintained; however, none has examined whether the stimulatory effects of leptin and contraction on muscle lipid metabolism are additive. This is the first study to examine the direct effect of leptin on lipid and carbohydrate (CHO) metabolism in isolated oxidative muscle over a range of contraction intensities. We examined the effect of leptin (10 microg/ml) on the synthesis and degradation of muscle lipid pools [phospholipid (PL), diacylglycerol (DG), triacylglycerol (TG)] and palmitate oxidation in isolated resting and contracting (2, 8, and 20 tetani/min) soleus muscles. At rest, leptin increased fatty acid oxidation (+ 40%, P < 0.05) and TG hydrolysis (+ 47%, P < 0.05), while blunting TG esterification (-20%, P < 0.05). Glucose oxidation was unaffected at rest in the presence of leptin. During tetanic contraction, fatty acid oxidation (+20-114%, P < 0.05) and TG esterification (+ 19-33%, P < 0.05) as well as net TG utilization (+ 23%, P < 0.05) were all significantly increased. However, leptin was without further effect on any of these parameters during contraction. Net utilization of intramuscular glycogen, as well as glucose oxidation, was unaffected during contraction by leptin. The findings of the present study indicate that leptin has an important influence on lipid metabolism in resting muscle, but not during contraction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".