Sex Differences in Estrogen-Dependent Transcription of Gonadotropin-Releasing Hormone (GnRH) Gene Revealed in GnRH Transgenic Mice
Bibliographic record
Abstract
The mechanisms through which gonadal steroids exert feedback actions on the activity of the GnRH neurons are not understood. Using a series of GnRH-LacZ transgenic mice we have examined the manner in which gonadal steroids suppress GnRH mRNA expression in male and female mice. The long-term gonadectomy of 5.5-GNZ-3.5 transgenic mice resulted in significant increases in cellular GnRH mRNA expression (P < 0.05) and plasma LH concentrations (P < 0.01) in both sexes. However, cellular levels of LacZ mRNA and beta-galactosidase, which provide an index of GnRH gene transcription, were only elevated in males after gonadectomy. This sexually differentiated response was also observed in mice gonadectomized for 2 wk. Estrogen replacement in gonadectomized males returned transgene expression to intact levels. Experiments in transgenic mice with 3' and 5' deleted GnRH-LacZ constructs revealed that the suppressive influence of estrogen on LacZ transcription in the male required a critical element located between -5.2 and -1.7 kb of the GnRH promoter. These studies show that the suppression of GnRH mRNA expression by estrogen in the male involves a decrease in GnRH gene transcription that is dependent on a distal GnRH promoter element. The same mechanism does not exist in females, indicating that gonadal steroids suppress GnRH mRNA levels in a sexually dimorphic manner.
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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) | 0.003 | 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".