Epigenetic Regulation of the Melatonin Receptor
Bibliographic record
Abstract
The multiple physiological effects of the indoleamine hormone melatonin, are mediated primarily by its two G protein-coupled MT1 and MT2 receptors. Our group has shown an upregulation of melatonin receptors following treatment with histone deacetylase (HDAC) inhibitors, including valproic acid (VPA) and Trichostatin A, in cultured cells and/or in the rat brain. VPA increases histone H3 acetylation at the MT1 gene promoter region in rat C6 glioma cells, indicating that this epigenetic mechanism underlies its upregulation of MT1 expression. Since HDAC inhibitors can also alter DNA methylation, the possible involvement of this second major epigenetic mechanism in the regulation of MT1 expression, was examined. C6 cells were treated with the DNA demethylating agent, azacytidine (AZA, 1 - 25 µM), for 24 or 48 hours. Treatment of C6 cells with AZA caused a significant upregulation of MT1 mRNA expression, as compared with controls (DMSO 0.05%). Moreover, treatment with AZA (10 or 20 µM) for 24 or 48 hours, suppressed or abolished DNMT1 protein expression, and inhibited DNMT1 mRNA expression, which indicates inhibition of the DNMT1 enzyme activity. A combination of VPA and AZA caused a trend toward additive upregulation of the MT1 receptor. These results show that DNA demethylation plays a role in the regulation of the MT1 receptor, consistent with the well-known effects of this epigenetic mechanism on gene transcription. Epigenetic regulation of melatonin receptor expression could provide a novel strategy for modulating the therapeutic effects of this hormone and its clinically relevant agonists, such as agomelatine, and could also provide avenues for enhancing the antioxidant, neuroprotective, oncostatic and other benefits of this hormone and its agonists.
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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".