A Dominant-negative p38 MAPK Mutant and Novel Selective Inhibitors of p38 MAPK Reduce Insulin-stimulated Glucose Uptake in 3T3-L1 Adipocytes without Affecting GLUT4 Translocation
Bibliographic record
Abstract
Participation of p38 mitogen-activated protein kinase (p38) in insulin-induced glucose uptake was suggested using pyridinylimidazole p38 inhibitors (e.g. SB203580). However, the role of p38 in insulin action remains controversial. We further test p38 participation in glucose uptake using a dominant-negative p38 mutant and two novel pharmacological p38 inhibitors related to but different from SB203580. We present the structures and activities of the azaazulene pharmacophores A291077 and A304000. p38 kinase activity was inhibited in vitro by A291077 and A304000 (IC(50) = 0.6 and 4.7 microm). At higher concentrations A291077 but not A304000 inhibited JNK2alpha (IC(50) = 3.5 microm). Pretreatment of 3T3-L1 adipocytes and L6 myotubes expressing GLUT4myc (L6-GLUT4myc myotubes) with A291077, A304000, SB202190, or SB203580 reduced insulin-stimulated glucose uptake by 50-60%, whereas chemical analogues inert toward p38 were ineffective. Expression of an inducible, dominant-negative p38 mutant in 3T3-L1 adipocytes reduced insulin-stimulated glucose uptake. GLUT4 translocation to the cell surface, immunodetected on plasma membrane lawns of 3T3-L1 adipocytes or on intact L6-GLUT4myc myotubes, was not altered by chemical or molecular inhibition of p38. We propose that p38 contributes to enhancing GLUT4 activity, thereby increasing glucose uptake. In addition, the azaazulene class of inhibitors described will be useful to decipher cellular actions of p38 and JNK.
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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 | 0.001 |
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".