Attenuation of Free Fatty Acid (FFA)-Induced Skeletal Muscle Cell Insulin Resistance by Resveratrol is Linked to Activation of AMPK and Inhibition of mTOR and p70 S6K
Bibliographic record
Abstract
Insulin resistance, a main characteristic of type 2 diabetes mellitus (T2DM), is linked to obesity and excessive levels of plasma free fatty acids (FFA). Studies indicated that significantly elevated levels of FFAs lead to skeletal muscle insulin resistance, by dysregulating the steps in the insulin signaling cascade. The polyphenol resveratrol (RSV) was shown to have antidiabetic properties but the exact mechanism(s) involved are not clearly understood. In the present study, we examined the effect of RSV on FFA-induced insulin resistance in skeletal muscle cells in vitro and investigated the mechanisms involved. Parental and GLUT4myc-overexpressing L6 rat skeletal myotubes were used. [3H]2-deoxyglucose (2DG) uptake was measured, and total and phosphorylated levels of specific proteins were examined by immunoblotting. Exposure of L6 cells to FFA palmitate decreased the insulin-stimulated glucose uptake, indicating insulin resistance. Palmitate increased ser307 (131% ± 1.84% of control, p < 0.001) and ser636/639 (148% ± 10.1% of control, p < 0.01) phosphorylation of IRS-1, and increased the phosphorylation levels of mTOR (174% ± 15.4% of control, p < 0.01) and p70 S6K (162% ± 20.2% of control, p < 0.05). Treatment with RSV completely abolished these palmitate-induced responses. In addition, RSV increased the activation of AMPK and restored the insulin-mediated increase in (a) plasma membrane GLUT4 glucose transporter levels and (b) glucose uptake. These data suggest that RSV has the potential to counteract the FFA-induced muscle insulin resistance.
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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) | 0.001 | 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) | 0.001 | 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".