Insulin but not PDGF relies on actin remodeling and on VAMP2 for GLUT4 translocation in myoblasts
Bibliographic record
Abstract
Insulin promotes the translocation of glucose transporter 4 (GLUT4) from intracellular pools to the surface of muscle and fat cells via a mechanism dependent on phosphatidylinositol (PtdIns) 3-kinase, actin cytoskeletal remodeling and the v-SNARE VAMP2. The growth factor PDGF-BB also robustly activates PtdIns 3-kinase and induces actin remodeling, raising the question of whether it uses similar mechanisms to insulin in mobilizing GLUT4. In L6 myoblasts stably expressing Myc-tagged GLUT4, neither stimulus affected the rate of GLUT4 endocytosis, confirming that they act primarily by enhancing exocytosis to increase GLUT4 at the cell surface. Although surface GLUT4myc in response to insulin peaked at 10 minutes and remained steady for 30 minutes, PDGF action was transient, peaking at 5 minutes and disappearing by 20 minutes. These GLUT4myc translocation time courses mirrored that of phosphorylation of Akt by the two stimuli. Interestingly, insulin and PDGF caused distinct manifestations of actin remodeling. Insulin induced discrete, long (>5 microm) dorsal actin structures at the cell periphery, whereas PDGF induced multiple short (<5 microm) dorsal structures throughout the cell, including above the nucleus. Latrunculin B, cytochalasin D and jasplakinolide, which disrupt actin dynamics, prevented insulin- and PDGF-induced actin remodeling but significantly inhibited GLUT4myc translocation only in response to insulin (75-85%, P<0.05), not to PDGF (20-30% inhibition). Moreover, transfection of tetanus toxin light chain, which cleaves the v-SNAREs VAMP2 and VAMP3, reduced insulin-induced GLUT4myc translocation by >70% but did not affect the PDGF response. These results suggest that insulin and PDGF rely differently on the actin cytoskeleton and on tetanus-toxin-sensitive VAMPs for mobilizing GLUT4.
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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) | 0.001 | 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".