Stimulation of Mitogen-Activated Protein Kinase by Gonadotropin-Releasing Hormone in Human Granulosa-Luteal Cells**This work was supported grants from the Medical Research Council of Canada.
Bibliographic record
Abstract
The present study investigated the activation of mitogen-activated protein kinases (MAPKs) by a GnRH agonist (GnRHa) in human granulosa-luteal cells (hGLCs). The phosphorylation state of p44 and p42 MAPK was examined using antibodies that distinguish phospho-p44/42 MAPK (Thr(202)/Tyr(204)) from total p44/42 MAPK (activated plus inactivated). Activation of MAPK by GnRHa was observed within 5 min and was sustained for 60 min after treatment. GnRHa stimulated MAPK activation in a dose-dependent manner, with maximum stimulation (6.7-fold over basal levels) at 10(-7) M. Pretreatment with a protein kinase C (PKC) inhibitor, GF109203X, completely blocked GnRHa-induced MAPK activation. In addition, pretreatment with a PKC activator, phorbol-12-myristate 13-acetate, potentiated GnRH-induced MAPK activation. These results indicate that GnRHa stimulates MAPK activation through a PKC-dependent pathway in hGLCs, possibly coupled to G(q)alpha protein. MAPK activation was also observed in response to 8-bromo-cAMP or cholera toxin, but not pertussis toxin. Forskolin (50 microM) substantially stimulated a rapid cAMP accumulation, whereas GnRHa (10(-7) M) or pertussis toxin (100 mg/ml) did not affect basal intracellular cAMP levels. Cotreatment of GnRHa (10(-7) M) did not attenuate forskolin- or hCG-stimulated cAMP accumulation. These results suggest that the GnRH receptor is probably not coupled to G(s)alpha or G(i)alpha in hGLCs. Finally, GnRHa (10(-7) M) stimulated a significant increase in Elk-1 phosphorylation and c-fos messenger RNA expression, as revealed by an in vitro kinase assay and Northern blot analysis, respectively. These results clearly demonstrate that GnRH activates the MAPK cascade through a PKC-dependent pathway in the human ovary.
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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 | 0.001 |
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".