Pituitary gonadotropin‐releasing hormone <scp>II</scp> as a possible mediator of positive estrogen feedback
Bibliographic record
Abstract
It has previously been shown that rhesus macaques express two forms of gonadotropin-releasing hormone (GNRH1 and GNRH2) in the hypothalamus and that both forms can stimulate the release of luteinizing hormone (LH) in vivo. However, while much has been published about the role of GNRH1 in reproduction, very little is known about the hypophysiotropic function of GNRH2. To shed light on this issue, we studied the expression pattern of these two genes in different parts of the monkey hypothalamus and pituitary gland under controlled conditions of circulating estrogen levels, using qPCR, liquid chromatography with tandem mass spectrometry and RNAscope. GNRH1/GNRH1 expression was found throughout the hypothalamus and was largely unaffected by circulating estradiol levels. In contrast, GNRH2/GNRH2 expression was found to be enhanced by long-term treatment with estradiol and during the late follicular phase of the menstrual cycle, especially in the arcuate nucleus and pituitary gland. Together these findings suggest that pituitary GNRH2/GNRH2 (but not GNRH1/GNRH1) is induced by positive feedback-like levels of estradiol. This novel finding raises the possibility that GNRH2 plays a major role in triggering the preovulatory LH surge in primates, not only at the level of the hypothalamus but also the pituitary gland.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".