Amino Acid and Insulin Signaling via the mTOR/p70 S6 Kinase Pathway
Why this work is in the frame
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Bibliographic record
Abstract
Amino acids have emerged as potent modulators of the mTOR/p70 S6 kinase pathway. The involvement of this pathway in the regulation of insulin-stimulated glucose transport was investigated in the present study. Acute exposure (1 h) to a balanced mixture of amino acids reduced insulin-stimulated glucose transport by as much as 55% in L6 muscle cells. The effect of amino acids was fully prevented by the specific mTOR inhibitor rapamycin. Time course analysis of insulin receptor substrate 1 (IRS-1)-associated phosphatidylinositol (PI) 3-kinase activity revealed that incubation with amino acids speeds up its time-dependent deactivation, leading to a dramatic suppression (-70%) of its activity after 30 min of insulin stimulation as compared with its maximal activation (5 min of stimulation). This accelerated deactivation of PI 3-kinase activity in amino acid-treated cells was associated with a concomitant and sustained increase in the phosphorylation of p70 S6 kinase. In marked contrast, inhibition of mTOR by rapamycin maintained PI 3-kinase maximally activated for up to 30 min. The marked inhibition of insulin-mediated PI 3-kinase activity by amino acids was linked to a rapamycin-sensitive increase in serine/threonine phosphorylation of IRS-1 and a decreased binding of the p85 subunit of PI 3-kinase to IRS-1. Furthermore, amino acids were required for the degradation of IRS-1 during long term insulin treatment. These results identify the mTOR/p70 S6 kinase signaling pathway as a novel modulator of insulin-stimulated glucose transport in skeletal muscle cells.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 it