The Rab GTPase-Activating Protein AS160 Integrates Akt, Protein Kinase C, and AMP-Activated Protein Kinase Signals Regulating GLUT4 Traffic
Bibliographic record
Abstract
Insulin-dependent phosphorylation of Akt target AS160 is required for GLUT4 translocation. Insulin and platelet-derived growth factor (PDGF) (Akt activators) or activation of conventional/novel (c/n) protein kinase C (PKC) and 5' AMP-activated protein kinase (AMPK) all promote a rise in membrane GLUT4 in skeletal muscle and cultured cells. However, the downstream effectors linking these pathways to GLUT4 traffic are unknown. Here we explore the hypothesis that AS160 is a molecular link among diverse signaling cascades converging on GLUT4 translocation. PDGF and insulin increased AS160 phosphorylation in CHO-IR cells. Stimuli that activate c/n PKC or AMPK also elevated AS160 phosphorylation. We therefore examined if these signaling pathways engage AS160 to regulate GLUT4 traffic in muscle cells. Nonphosphorylatable AS160 (4P-AS160) virtually abolished the net surface GLUT4myc gains elicited by insulin, PDGF, K(+) depolarization, or 5-aminoimidazole-4-carboxamide-1-beta-d-ribofuranoside but partly, yet significantly, inhibited the effects of 4-phorbol-12-myristate-13-acetate. However, the hypertonicity or 2,4-dinitrophenol-dependent gains in surface GLUT4myc were unaffected by 4P-AS160. RK-AS160 (GTPase-activating protein [GAP] inactive) or 4PRK-AS160 (GAP inactive, nonphosphorylatable) had no effect on surface GLUT4myc elicited by all stimuli. Collectively, these results indicate that activation of Akt, c/n PKC, or alpha2-AMPK intersect at AS160 to regulate GLUT4 traffic, as well as highlight the potential of AS160 as a therapy target to increase muscle glucose uptake.
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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 | 0.001 |
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".