Regulatory Effects of Gonadotropin-Releasing Hormone (GnRH) I and GnRH II on the Levels of Matrix Metalloproteinase (MMP)-2, MMP-9, and Tissue Inhibitor of Metalloproteinases-1 in Primary Cultures of Human Extravillous Cytotrophoblasts
Bibliographic record
Abstract
An intricate balance between the production of matrix metalloproteinases (MMPs) and their endogenous inhibitors, tissue inhibitors of metalloproteinases (TIMPs), modulates the overall proteolytic activity of trophoblasts during human implantation. In these studies we have examined the ability of classical GnRH I and the second form of this hormone (GnRH II) to regulate MMP-2, MMP-9, and TIMP-1 mRNA and protein levels in extravillous cytotrophoblasts propagated from explants of first trimester chorionic villi. GnRH I and GnRH II were found to increase MMP-2 and MMP-9 mRNA and protein levels in these primary cell cultures in a dose- and time-dependent manner using quantitative competitive-PCR and ELISA. In contrast, these two hormones decreased trophoblastic TIMP-1 mRNA and protein levels. Cetrorelix, a GnRH receptor antagonist, inhibited the regulatory effects of GnRH I, but not GnRH II, on MMP-2, MMP-9, and TIMP-1 expression in these cells. Collectively, these observations suggest that GnRH I and GnRH II differentially regulate MMP-2, MMP-9, and TIMP-1 expression in human trophoblasts, possibly via distinct receptor-mediated intracellular signaling pathways.
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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) | 0.001 | 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".