Melatonin Receptor Activation Regulates GnRH Gene Expression and Secretion in GT1–7 GnRH Neurons
Bibliographic record
Abstract
Melatonin plays a significant role in the control of the hypothalamic-pituitary-gonadal axis. Using the GT1-7 cell line, an in vitro model of GnRH-secreting neurons of the hypothalamus, we examined the potential signal transduction pathways activated by melatonin directly at the level of the GT1-7 neuron. We found that melatonin inhibits forskolin-stimulated adenosine 3'-, 5'-cyclic monophosphate accumulation in GT1-7 cells through an inhibitory G protein. Melatonin induced protein kinase C activity by 1.65-fold over basal levels, increased the phosphorylation of extracellular signal-regulated kinase 1 and 2 proteins, and activated c-fos and junB mRNA expression in GT1-7 cells. Using the protein kinase A inhibitor H-89, the protein kinase C inhibitor bisindolylmaleimide, and the mitogen-activated protein kinase kinase inhibitor PD98059, we found that the melatonin-mediated cyclical regulation of GnRH mRNA expression may involve the protein kinase C and the extracellular signal-regulated kinase 1 and 2 pathways, but not the protein kinase A pathway. We found that melatonin suppresses GnRH secretion by approximately 45% in the GT1-7 neurons. However, in the presence of the inhibitors H-89, bisindolylmaleimide, and PD98059 melatonin was unable to suppress GnRH secretion. These results provide insights into the potential signal transduction mechanisms involved in the control of GnRH gene expression and secretion by melatonin.
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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".