Rapid Effect of GNRH1 on Follicle-Stimulating Hormone Beta Gene Expression in LbetaT2 Mouse Pituitary Cells Requires the Progesterone Receptor1
Bibliographic record
Abstract
Gonadotropin-releasing hormone (GNRH) activates the progesterone receptor (PGR) in pituitary cells and accentuates gonadotropin expression. We show that GNRH1 increases Fshb mRNA levels in LbetaT2 mouse pituitary cells within 8 h and is three times more effective than GNRH2. By contrast, GNRH1 and GNRH2 do not affect Lhb gene expression in these cells. Within the same time frame, small interfering RNA (siRNA) knockdown of the PGR in LbetaT2 cells reduced GNRH1 activation of a PGR response element (PRE)-driven luciferase reporter gene and Fshb mRNA levels by >50%. Chromatin immunoprecipitation (ChIP) assays also demonstrated that PGR loading on the PRE within the Fshb gene promoter in LbetaT2 cells occurred within 8 h after GNRH1 treatment and was lost by 24 h. While the GNRH1-induced upregulation of the PRE reporter gene and Fshb mRNA levels was attenuated by cotreatment with protein kinase A (H-89) and protein kinase C (GF109203X) inhibitors, only GF109203X inhibited PGR phosphorylation at Ser249 in LbetaT2 cells. Immunoprecipitation assays also showed a progressive increase in the interaction between the PGR and its coactivator NCOA3 that peaked at 8 h coincident with the increase in Fshb mRNA after GNRH1 treatment. The siRNA-mediated knockdown of NCOA3 in LbetaT2 cells also reduced Fshb mRNA levels after GNRH1 treatment and loading of NCOA3 on the Fshb promoter PRE in a ChIP assay. We conclude that the rapid effect of GNRH1 on Fshb expression in LbetaT2 cells is mediated by PGR phosphorylation and loading at the PRE within the Fshb promoter together with NCOA3.
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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".