Increased Activation of the Mammalian Target of Rapamycin Pathway in Liver and Skeletal Muscle of Obese Rats: Possible Involvement in Obesity-Linked Insulin Resistance
Bibliographic record
Abstract
The mammalian target of rapamycin (mTOR) pathway integrates insulin and nutrient signaling in numerous cell types. Recent studies also suggest that this pathway negatively modulates insulin signaling to phosphatidylinositol 3-kinase/Akt in adipose and muscle cells. However, it is still unclear whether activation of the mTOR pathway is increased in obesity and if it could be involved in the promotion of insulin resistance. In this paper we show that basal (fasting state) activation of mTOR and its downstream target S6K1 is markedly elevated in liver and skeletal muscle of obese rats fed a high fat diet compared with chow-fed, lean controls. Time-course studies also revealed that mTOR and S6K1 activation by insulin was accelerated in tissues of obese rats, in association with increased inhibitory phosphorylation of insulin receptor substrate-1 (IRS-1) on Ser636/Ser639 and impaired Akt activation. The relationship between mTOR/S6K1 overactivation and impaired insulin signaling to Akt was also examined in hepatic cells in vitro. Insulin caused a time-dependent activation of mTOR and S6K1 in HepG2 cells. This was associated with increased IRS-1 phosphorylation on Ser636/Ser639. Inhibition of mTOR/S6K1 by rapamycin blunted insulin-induced Ser636/Ser639 phosphorylation of IRS-1, leading to a rapid (approximately 5 min) and persistent increase in IRS-1-associated phosphatidylinositol 3-kinase activity and Akt phosphorylation. These results show that activation of the mTOR pathway is increased in liver and muscle of high fat-fed obese rats. In vitro studies with rapamycin suggest that mTOR/S6K1 overactivation contributes to elevated serine phosphorylation of IRS-1, leading to impaired insulin signaling to Akt in liver and muscle of this dietary model of obesity.
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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 | 0.001 | 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 | 0.000 |
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".