Molecular Basis for the Activation of Gonadotropin-Inhibitory Hormone Gene Transcription by Corticosterone
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Bibliographic record
Abstract
The inhibitory effect of stress on reproductive function is potentially mediated by high concentrations of circulating glucocorticoids (GCs) acting via the GC receptor (GR). Gonadotropin-inhibitory hormone (GnIH) is a hypothalamic neuropeptide that inhibits gonadotropin secretion. GnIH may mediate stress-induced reproductive dysfunction. However, it is not yet known whether GC-bound GR is directly involved in GnIH transcription. Here, we demonstrated the localization of GR mRNA in GnIH neurons in the paraventricular nucleus of quail, suggesting that GC can directly regulate GnIH transcription. We next showed that 24 hours of treatment with corticosterone (CORT) increase GnIH mRNA expression in the quail diencephalon. We further investigated the mechanism of activation of GnIH transcription by CORT using a GnIH-expressing neuronal cell line, rHypoE-23, derived from rat hypothalamus. We found the expression of GR mRNA in rHypoE-23 cells and increased GnIH mRNA expression by 24 hours of CORT treatment. We finally characterized the promoter activity of rat GnIH gene stimulated by CORT. Through DNA deletion analysis, we identified a CORT-responsive region at 2000-1501 bp upstream of GnIH precursor coding region. This region included 2 GC response elements (GREs) at -1665 and -1530 bp. Mutation of -1530 GRE abolished CORT responsiveness. We also found CORT-stimulated GR recruitment at the GnIH promoter region containing the -1530 GRE. These results provide a putative molecular basis for transcriptional activation of GnIH under stress by demonstrating that CORT directly induces GnIH transcription by recruitment of GR to its promoter.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it