Identification of IRS-1 Ser-1101 as a target of S6K1 in nutrient- and obesity-induced insulin resistance
Bibliographic record
Abstract
S6K1 has emerged as a critical signaling component in the development of insulin resistance through phosphorylation and inhibition of IRS-1 function. This effect can be triggered directly by nutrients such as amino acids or by insulin through a homeostatic negative-feedback loop. However, the role of S6K1 in mediating IRS-1 phosphorylation in a physiological setting of nutrient overload is unresolved. Here we show that S6K1 directly phosphorylates IRS-1 Ser-1101 in vitro in the C-terminal domain of the protein and that mutation of this site largely blocks the ability of amino acids to suppress IRS-1 tyrosine and Akt phosphorylation. Consistent with this finding, phosphorylation of IRS-1 Ser-1101 is increased in the liver of obese db/db and wild-type, but not S6K1(-/-), mice maintained on a high-fat diet and is blocked by siRNA knockdown of S6K1 protein. Finally, infusion of amino acids in humans leads to the concomitant activation of S6K1, phosphorylation of IRS-1 Ser-1101, a reduction in IRS-1 function, and insulin resistance in skeletal muscle. These findings indicate that nutrient- and hormonal-dependent activation of S6K1 causes insulin resistance in mice and humans, in part, by mediating IRS-1 Ser-1101 phosphorylation.
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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) | 0.001 | 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 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".