Muscle cell palmitate-induced insulin resistance, JNK, IKK/NF-κB, and STAT3 activation are attenuated by carnosic and rosmarinic acid
Bibliographic record
Abstract
The worldwide epidemic of obesity has drastically worsened with the increase in more sedentary lifestyles and increased consumption of fatty foods. Increased blood free fatty acids, often observed in obesity, lead to impaired insulin action, and promote the development of insulin resistance and type 2 diabetes mellitus. c-Jun N-terminal kinase (JNK), inhibitor of kappa B (IκB) kinase (IKK)-nuclear factor-kappa B (NF-κB), and signal transducer and activator of transcription 3 (STAT3) are known to be involved in skeletal muscle insulin resistance. We reported previously that carnosic acid (CA) and rosmarinic acid (RA) attenuated the palmitate-induced skeletal muscle insulin resistance, an effect that was associated with increased AMPK activation and reduced mammalian target of rapamycin-p70S6K signaling. In the present study, we examined the effects of CA and RA on JNK, IKK-NF-κB, and STAT3. Exposure of cells to palmitate increased the phosphorylation/activation of JNK, IKKα/β, IκBα, NF-κBp65, and STAT3. Importantly, CA and RA attenuated the deleterious effects of palmitate. Our data indicate that CA and RA have the potential to counteract the palmitate-induced skeletal muscle cell insulin resistance by modulating JNK, IKK-NF-κB, and STAT3 signaling.
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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) | 0.000 | 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 | 0.001 |
| 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".