The Inhibitory Effects Of γ-Aminobutyric Acid (Gaba) On Growth Hormone Secretion in the Goldfish Are Modulated by SEx Steroids
Bibliographic record
Abstract
Double-labelling studies at the electron microscopic level demonstrated that gamma-aminobutyric acid (GABA)-immunoreactive nerve endings are associated with growth-hormone-secreting cells in the proximal pars distalis of the goldfish pituitary gland, suggesting that GABA may be important for the control of growth hormone release in this species. An in vitro assay for GABA-transaminase activity demonstrated that the pituitary is a site for the metabolism of GABA to succinic acid. In vitro, GABA or the GABA antagonists bicuculline and saclofen did not affect the rate of growth hormone release from dispersed pituitary cells in static incubation. In contrast, intracerebroventricular injection of GABA reduced serum growth hormone levels within 30 min. During the seasonal gonadal cycle, intraperitoneal injection of GABA was without effect in sexually regressed goldfish, but caused a significant decrease in serum growth hormone levels in sexually recrudescent animals. Intraperitoneal implantation of solid silastic pellets containing oestradiol increased serum GH levels fivefold in sexually regressed and recrudescent goldfish; in both groups, GABA suppressed the oestradiol-stimulated increase in circulating growth hormone levels. The effect of oestradiol on basal serum growth hormone levels was specific since progesterone and testosterone were without effect. However, in recrudescent animals treated with progesterone and testosterone, the inhibitory effects of GABA on serum growth hormone levels were absent, indicating a differential role for these steroids in growth hormone release. Taken together, these results demonstrate that GABA has an inhibitory effect on growth hormone release in goldfish.
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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".