Time- and dose-related effects of gonadotropin-releasing hormone on growth hormone and gonadotropin subunit gene expression in the goldfish pituitary
Bibliographic record
Abstract
The goldfish brain contains two molecular forms of gonadotropin-releasing hormone (GnRH): salmon GnRH (sGnRH) and chicken GnRH-II (cGnRH-II). In a preliminary report, we demonstrated the stimulation of gonadotropin hormone (GtH) subunit and growth hormone (GH) mRNA levels by a single dose of GnRH at a single time point in the goldfish pituitary. Here we extend the work and demonstrate time- and dose-related effects of sGnRH and cGnRH-II on GtH subunit and GH gene expression in vivo and in vitro. The present study demonstrates important differences between the time- and dose-related effects of sGnRH and cGnRH-II on GtH subunit and GH mRNA levels. Using primary cultures of dispersed pituitary cells, the minimal effective dose of cGnRH-II required to stimulate GtH subunit mRNA levels was found to be 10-fold lower than that of sGnRH. In addition, the magnitudes of the increases in GtH subunit and GH mRNA levels stimulated by cGnRH-II were found to be higher than the sGnRH-induced responses. However, no significant difference was observed between sGnRH and cGnRH-II-induced responses in vivo. Time-related studies also revealed significant differences between sGnRH- and cGnRH-II-induced production of GtH subunit and GH mRNA in the goldfish pituitary. In general, the present study provides novel information on time- and dose-related effects of sGnRH and cGnRH-II on GtH subunit and GH mRNA levels and provides a framework for further investigation of GnRH mechanisms of action in the goldfish pituitary.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".