Mammalian Target of Rapamycin Is Activated in Association with Myometrial Proliferation during Pregnancy
Bibliographic record
Abstract
The adaptive growth of the uterus during gestation involves gradual changes in cellular phenotypes from the early proliferative to the intermediate synthetic phase of cellular hypertrophy, ending in the final contractile/labour phenotype. The mammalian target of rapamycin (mTOR) signaling pathway regulates cell growth and proliferation in many tissues. We hypothesized that mTOR was a mediator of hormone-initiated myometrial hyperplasia during gestation. The protein expression and phosphorylation levels of mTOR, its upstream regulators [insulin receptor substrate-1, phosphoinositide-3-kinase (PI3K), Akt], and downstream effectors [S6-kinase-1 (S6K1) and eI4FE-binding protein 1 (4EBP1)] were analyzed throughout normal pregnancy in rats. In addition, we used an ovariectomized (OVX) rat model to analyze the modulation of the mTOR pathway and proliferative activity of the uterine myocytes by estradiol alone and in combination with the mTOR-specific inhibitor rapamycin. Our results demonstrate that insulin receptor substrate-1 protein levels and the phosphorylated (activated) forms of PI3K, mTOR, and S6K1 were significantly up-regulated in the rat myometrium during the proliferative phase of pregnancy. Treatment of the OVX rats with estradiol caused a transient increase in IGF-I followed by an up-regulation of the PI3K/mTOR pathway, which became apparent by a cascade of phosphorylation reactions (P-P85, P-Akt, P-mTOR, P-S6K1, and P-4EBP1). Rapamycin blocked activation of P-mTOR, P-S6K1, and P-4EBP1 proteins and significantly reduced the number of proliferating cells in the myometrium of OVX rats. Our in vivo data demonstrate that estradiol was able to activate the PI3K/mTOR signaling pathway in uterine myocytes and suggest that this activation is responsible for the induction of myometrial hyperplasia during early gestation.
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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".