Conjugated linoleic acid increases skeletal muscle ceramide content and decreases insulin sensitivity in overweight, non-diabetic humans
Bibliographic record
Abstract
The effect of conjugated linoleic acid (CLA), a popular weight-loss supplement, on insulin sensitivity in humans is controversial and has notbeen extensively studied. To date no studies have examined the effects of CLA supplementation on human skeletal muscle metabolism or lipid content. It is also unknown whether CLA accumulates in human skeletal muscle with supplementation. In the present study, 9 overweight, non-diabetic individuals received 4 g/d of mixed CLA isomers in the form of 1 g supplements, for 12 weeks. CLA isomers significantly increased in both plasma and skeletal muscle following supplementation. Skeletal muscle ceramide content was also significantly increased, although there was no consistent change in muscle diacylglycerol or triacylglycerol content. Insulin sensitivity was significantly decreased (p ≤ 0.05) following CLA supplementation, with a significant increase in glucose and insulin area under the curve during an oral glucose tolerance test (p ≤ 0.005). The protein content of PPARα, for which CLA is a potent ligand, was unchanged following supplementation. Accordingly, there was no change in markers of muscle oxidative capacity. In conclusion, mixed-isomer CLA supplementation in overweight non-diabetic humans results in the accumulation of CLA and ceramide in skeletal muscle, and decreases insulin sensitivity.
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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) | 0.001 | 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".