Steroid Receptor Coactivator-3 Is Required for Progesterone Receptor Trans-activation of Target Genes in Response to Gonadotropin-releasing Hormone Treatment of Pituitary Cells
Bibliographic record
Abstract
Regulation of gonadotropin production involves interplay between steroids and neuropeptides, and we have examined the effects of gonadotropin-releasing hormones (GnRH I and GnRH II) on progesterone receptor (PR) activation in alphaT3-1 pituitary cells. Treatment with GnRHs activated a progester-one response element (PRE)-luciferase reporter gene, and this was blocked by protein kinase C and protein kinase A inhibitors but not by RU486. Treatment with GnRHs phosphorylated the PR at Ser(294) and increased PR translocation to the nucleus within 1 h. Interactions between the PR and several coactivators were examined, and treatment with GnRHs specifically induced PR-steroid receptor coactivator-3 (SRC-3) interactions within 8 h. In chromatin immunoprecipitation assays, recruitment of PR and SRC-3 by the PREs of the luciferase reporter gene or the gonadotopin alpha-subunit gene promoter was also increased by GnRHs within 8 h, while progesterone-induced recruitment of PR to the PREs occurred in association with much less SRC-3. A small interfering RNA knockdown of type I GnRH receptor levels reduced PR activation by GnRHs, while progesterone-dependent PR activation was unaffected. Moreover, small interfering RNA knockdown of SRC-3 abolished PRE-luciferase trans-activation by the PR in response to GnRHs. Collectively, these data indicate that PR activation by GnRHs in alphaT3-1 cells is type I GnRH receptor-mediated and that trans-activation of PR-responsive genes requires SRC-3 in this context.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".