Interactions of Estradiol with Gonadotropin-Releasing Hormone and Thyrotropin-Releasing Hormone in the Control of Growth Hormone Secretion in the Goldfish
Bibliographic record
Abstract
The effects of testosterone (T) and estradiol (E2) on serum growth hormone (GH) concentrations were investigated throughout the seasonal reproductive cycle of the female goldfish. Gonad-intact female goldfish were implanted intraperitoneally for 5 days with silastic pellets containing no steroid (blank), T(100 micrograms/g) or E2 (25-100 micrograms/g). In blank-implanted females, seasonal variations in serum GH were evident; maximal serum GH levels were found in spring while minimal GH levels were found in summer and early autumn. Implantation of E2-containing silastic capsules stimulated increases (2-4 times control) in serum GH levels throughout the reproductive cycle. Implantation of T did not affect serum GH at any time of the year. One possible mechanism by which E2 could exert its effects may be through alteration of pituitary sensitivity to GH-releasing factors. The decapeptide salmon gonadotropin-releasing hormone (sGnRH) is found in the brain and pituitary of goldfish and stimulates gonadotropin (GTH) and GH secretion. In contrast, thyrotropin-releasing hormone (TRH) stimulates GH, but not GTH, release from pars distalis fragments obtained from sexually regressed (ED50 = 5.7 +/- 3.8 nM; August) or sexually mature (ED50 = 0.53 +/- 0.28 nM; March) fish; in vivo E2 treatment resulted in a 3-fold increase in the in vitro GH response to TRH. Furthermore, E2 treatment increased sGnRH-stimulated GH release by approximately 4-fold. These results demonstrate that E2 but not T stimulates GH secretion throughout the reproductive cycle of female goldfish. Furthermore, sGnRH and TRH stimulate GH release in a teleost, and these stimulatory responses are enhanced by physiological levels of E2.
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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".