Attenuation of Free Fatty Acid-Induced Muscle Insulin Resistance by Rosemary Extract
Bibliographic record
Abstract
Elevated blood free fatty acids (FFAs), as seen in obesity, impair muscle insulin action leading to insulin resistance and Type 2 diabetes mellitus. Serine phosphorylation of the insulin receptor substrate (IRS) is linked to insulin resistance and a number of serine/threonine kinases including JNK, mTOR and p70 S6K have been implicated in this process. Activation of the energy sensor AMP-activated protein kinase (AMPK) increases muscle glucose uptake, and in recent years AMPK has been viewed as an important target to counteract insulin resistance. We reported recently that rosemary extract (RE) increased muscle cell glucose uptake and activated AMPK. However, the effect of RE on FFA-induced muscle insulin resistance has never been examined. In the current study, we investigated the effect of RE in palmitate-induced insulin resistant L6 myotubes. Exposure of myotubes to palmitate reduced the insulin-stimulated glucose uptake, increased serine phosphorylation of IRS-1, and decreased the insulin-stimulated phosphorylation of Akt. Importantly, exposure to RE abolished these effects and the insulin-stimulated glucose uptake was restored. Treatment with palmitate increased the phosphorylation/activation of JNK, mTOR and p70 S6K whereas RE completely abolished these effects. RE increased the phosphorylation of AMPK even in the presence of palmitate. Our data indicate that rosemary extract has the potential to counteract the palmitate-induced muscle cell insulin resistance and further studies are required to explore its antidiabetic properties.
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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) | 0.001 | 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".