Regulation of AKT Signaling in Mouse Uterus
Bibliographic record
Abstract
17β-estradiol (E2) treatment of ovariectomized adult mice stimulates the uterine PI3K-AKT signaling pathway and epithelial proliferation through estrogen receptor 1 (ESR1). However, epithelial proliferation occurs independently of E2/ESR1 signaling in neonatal uteri. Similarly, estrogen-independent uterine epithelial proliferation is seen in adulthood in mice lacking Ezh2, critical for histone methylation, and in wild-type (WT) mice treated neonatally with estrogen. The role of AKT in estrogen-independent uterine epithelial proliferation was the focus of this study. Expression of the catalytically active phosphorylated form of AKT (p-AKT) and epithelial proliferation were high in estrogen receptor 1 knockout and WT mice at postnatal day 6, when E2 concentrations were low, indicating that neither ESR1 nor E2 are essential for p-AKT expression and epithelial proliferation in these mice. However, p-AKT levels and proliferation remained estrogen responsive in preweaning WT mice. Expression of p-AKT and proliferation were both high in uterine luminal epithelium of mice estrogenized neonatally and ovariectomized during adulthood. Increased expression of phosphorylated (inactive) EZH2 was also observed. Consistent with this, Ezh2 conditional knockout mice show ovary-independent uterine epithelial proliferation and high epithelial p-AKT. Thus, adult p-AKT expression is constitutive and E2/ESR1 independent in both model systems. Finally, E2-induced p-AKT expression and normal uterine proliferation did not occur in mice lacking membrane (m)ESR1, indicating a key role for membrane ESR1 in AKT activation. These findings emphasize the importance of AKT activation in promoting uterine epithelial proliferation even when that proliferation is not E2/ESR1 dependent and further indicate that p-AKT can be uncoupled from E2/ESR1 signaling in several experimental scenarios.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".