Mechanistic target of rapamycin (MTOR) signaling during ovulation in mice
Bibliographic record
Abstract
A complex network of endocrine/paracrine signals regulates granulosa-cell function in ovarian follicles. Mechanistic target of rapamycin (MTOR) has recently emerged as a master intracellular integrator of extracellular signals and nutrient availability. The objectives of the present study were to characterize the expression pattern and kinase activity of MTOR during follicular and corpus luteum development, and to examine how inhibition of MTOR kinase activity affects preovulatory maturation of ovarian follicles. MTOR expression was constitutive throughout follicular and corpus luteum development. Gonadotropins induced MTOR kinase activity in the ovary, which was inhibited by rapamycin treatment (10 µg/g body weight, intraperitoneal injection). Inhibition of human chorionic gonadotropin (hCG)-induced MTOR activity during preovulatory follicle maturation did not change key events of ovulation. Granulosa cells of rapamycin-treated mice showed reduced MTOR kinase activity at 1 and 4 hr post-hCG and overexpression of hCG-induced ovulation genes at 4 hr post-hCG. Overexpression of these ovulatory genes was associated with hyper-activation of extracellular signal-regulated kinase 1/2 (ERK1/2), which occurred in response to inhibition of MTOR with rapamycin and suggested that MTOR may function as a negative regulator of the mitogen-activated protein kinase (MAPK) pathway. Indeed, simultaneous inhibition of MTOR and ERK1/2 activities during preovulatory follicle maturation caused anovulation. Inhibition of hCG-induced ERK1/2 activity alone suppressed MTOR kinase activity, indicating that MAPK pathway is upstream of MTOR. Thus, normal ovulation appears to be a result of complex interactions between MTOR and MAPK signaling pathways in granulosa cells of ovulating follicles in mice.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".