ROSEMARY EXTRACT: RECENT ADVANCES AND PERSPECTIVES - CARNOSIC ACID STIMULATES SKELETAL MUSCLE CELL GLUCOSE UPTAKE VIA AMPK ACTIVATION
Bibliographic record
Abstract
Compounds that increase the activity of the energy sensor AMP-activated kinase (AMPK) have the potential to regulate blood glucose levels. Rosemary extract (RE) has been reported to activate AMPK and reduce blood glucose levels in vivo. In the present study, we measured the levels of the polyphenol carnosic acid (CA) in RE and examined the effects and the mechanism of action of CA on glucose transport system in muscle cells. High performance liquid chromatography (HPLC) was used to measure the levels of CA in RE. Parental and GLUT4myc or GLUT1myc overexpressing L6 rat myotubes were used. Glucose uptake was assessed using [3H]-2-deoxy-D-glucose. Total and phosphorylated levels of Akt and AMPK were measured by immunoblotting. Plasma membrane GLUT4myc and GLUT1myc levels were examined using a GLUT translocation assay. At concentrations found in rosemary extract, CA stimulated glucose uptake in L6 myotubes. At 2.0 μM CA a response (226±9.62% of control, p<0.001), similar to maximum insulin (201±7.86%, p<0.001) and metformin (213±10.74%, p<0.001) was seen. Insulin sensitivity was increase by CA. Akt phosphorylation was not affected by CA while AMPK phosphorylation was increased and the CA-stimulated glucose uptake was significantly reduced by the AMPK inhibitor compound C. Plasma membrane GLUT4 or GLUT1 glucose transporter levels were not affected by CA. Our study is the first to show increased muscle cell glucose uptake and AMPK activation by low CA concentrations, found in rosemary extract, indicating that CA may be responsible for the anti-hyperglycemic properties of rosemary extract seen in vivo.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".