The Antihyperglycemic Drug α-Lipoic Acid Stimulates Glucose Uptake via Both GLUT4 Translocation and GLUT4 Activation
Bibliographic record
Abstract
The cofactor of mitochondrial dehydrogenase complexes and potent antioxidant alpha-lipoic acid has been shown to lower blood glucose in diabetic animals. alpha-Lipoic acid enhances glucose uptake and GLUT1 and GLUT4 translocation in 3T3-L1 adipocytes and L6 myotubes, mimicking insulin action. In both cell types, insulin-stimulated glucose uptake is reduced by inhibitors of p38 mitogen-activated protein kinase (MAPK). Here we explore the effect of alpha-lipoic acid on p38 MAPK, phosphatidylinositol (PI) 3-kinase, and Akt1 in L6 myotubes. alpha-Lipoic acid (2.5 mmol/l) increased PI 3-kinase activity (31-fold) and Akt1 (4.9-fold). Both activities were inhibited by 100 nmol/l wortmannin. alpha-Lipoic acid also stimulated p38 MAPK phosphorylation by twofold within 10 min. The phosphorylation persisted for at least 30 min. Like insulin, alpha-lipoic acid increased the kinase activity of the alpha (2.8-fold) and beta (2.1-fold) isoforms of p38 MAPK, measured by an in vitro kinase assay. Treating cells with 10 micromol/l of the p38 MAPK inhibitors SB202190 or SB203580 reduced the alpha-lipoic acid-induced stimulation of glucose uptake by 66 and 55%, respectively. In contrast, SB202474, a structural analog that does not inhibit p38 MAPK, was without effect on glucose uptake. In contrast to 2-deoxyglucose uptake, translocation of GLUT4myc to the cell surface by either alpha-lipoic acid or insulin was unaffected by 20 micromol/l of SB202190 or SB203580. The results suggest that inhibition of 2-deoxyglucose uptake in response to alpha-lipoic acid by inhibitors of p38 MAPK is independent of an effect on GLUT4 translocation. Instead, it is likely that regulation of transporter activity is sensitive to these inhibitors.
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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) | 0.002 | 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".