Role of Akt substrate of 160 kDa in insulin-stimulated and contraction-stimulated glucose transport
Bibliographic record
Abstract
Insulin and exercise, the most important physiological stimuli to increase glucose transport in skeletal muscle, trigger a redistribution of GLUT4 glucose transporter proteins from the cell interior to the cell surface, thereby increasing glucose transport capacity. The most distal insulin signaling protein that has been linked to GLUT4 translocation, Akt substrate of 160 kDa (AS160), becomes phosphorylated in insulin-stimulated 3T3-L1 adipocytes; this is important for insulin-stimulated GLUT4 translocation and glucose transport. Insulin also induces a rapid and dose-dependent increase in AS160 phosphorylation in skeletal muscle. Available data from skeletal muscle support the concepts developed in adipocytes with regard to the role AS160 plays in the regulation of insulin-stimulated glucose transport. In vivo exercise, in vitro contractions, or in situ contractions can also stimulate AS160 phosphorylation. AMP-activated protein kinase (AMPK) is likely important for phosphorylating AS160 in response to exercise/contractile activity, whereas Akt2 appears to be important for insulin-stimulated AS160 phosphorylation in muscle. Evidence of a role for AS160 in exercise/contraction-stimulated glucose uptake is currently inconclusive. The distinct signaling pathways that are stimulated by insulin and exercise/contraction converge at AS160. Although AS160 phosphorylation is apparently important for insulin-stimulated GLUT4 translocation and glucose transport, it is uncertain whether elevated AS160 phosphorylation plays a similar role with exercise/contraction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".