Sustained Exposure of L6 Myotubes to High Glucose and Insulin Decreases Insulin-Stimulated GLUT4 Translocation but Upregulates GLUT4 Activity
Bibliographic record
Abstract
Hyperglycemia and hyperinsulinemia are cardinal features of acquired insulin resistance. In adipose cell cultures, high glucose and insulin cause insulin resistance of glucose uptake, but because of altered GLUT4 expression and contribution of GLUT1 to glucose uptake, the basis of insulin resistance could not be ascertained. Here we show that GLUT4 determines glucose uptake in L6 myotubes stably overexpressing myc-tagged GLUT4. Preincubation for 24 h with high glucose and insulin (high Glc/Ins) reduced insulin-stimulated GLUT4 translocation by 50%, without affecting GLUT4 expression. Insulin receptor and insulin receptor substrate-1 tyrosine phosphorylation, phosphatidylinositol 3-kinase activation, and Akt phosphorylation also diminished, as did insulin-mediated glucose uptake. However, basal glucose uptake rose by 40% without any gain in surface GLUT4. High Glc/Ins elevated basal p38 mitogen-activated protein kinase (MAPK) phosphorylation and activity, and a short inhibition of p38 MAPK with SB202190 corrected the rise in basal glucose uptake, suggesting that p38 MAPK activity contributes to this rise. We propose that in a cellular model of skeletal muscle, chronic exposure to high Glc/Ins reduced the acute, insulin-elicited GLUT4 translocation. In addition, basal state GLUT4 activity was augmented to partially compensate for the translocation defect, resulting in a more robust glucose uptake than what would be predicted from the amount of cell surface GLUT4 alone.
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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 | 0.001 |
| 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".