Extra‐pituitary function of GnRH‐I and GnRH‐II in human reproduction
Bibliographic record
Abstract
Recent studies have indicated that both the classical form of mammalian GnRH (GnRH‐I) and its novel isoform (GnRH‐II) are potent autocrine regulators in several non‐pituitary tissues, including the ovary, endometrium and placenta. In human granulosa‐luteal cells, we have demonstrated the expression of GnRH‐I and GnRH‐II, as well as GnRH receptor (GnRH‐R). GnRH‐II, like GnRH‐I, directly inhibits progesterone production in human granulosa‐luteal cells. In normal ovarian surface epithelium (OSE) and in 80% of human ovarian epithelial tumors, GnRHR is expressed. A direct anti‐proliferative effect has been observed following treatment with GnRH‐I or GnRH‐II in different ovarian cancer cell lines, presumably via a common GnRHR (the type I GnRH‐R). In human endometrial stromal cells and in the first‐trimester trophoblast, GnRH‐I and GnRH‐II are expressed. These peptides differentially regulate the balance between the urokinase‐type plasminogen activator (uPA) and plasminogen activator inhibitor (PAI‐1) levels in the human decidua. GnRH‐I and GnRH‐II are potent regulators of matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) that are important for the overall proteolytic activity of trophoblasts during human implantation. Together, these findings strongly support a multi‐faceted role of the GnRH/GnRH‐R system in the control of reproduction. [This research was supported by the Canadian Institutes of Health Research].
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".