Gamma-Aminobutyric Acid Is not Likely a Physiological Prolactin-Inhibiting Factor
Bibliographic record
Abstract
Basal plasma prolactin concentration is controlled by tonic inhibition. The major prolactin-inhibiting factor (PIF) is believed to be dopamine. Factors other than dopamine have also been suggested as possible physiological PIF. One of the major candidates for the nondopaminergic PIF is considered to be gamma-aminobutyric acid (GABA). We have carefully examined the possible physiological role of GABA by monitoring, at every 2 min, the circulating prolactin concentration after GABA administration, in conscious freely moving rats. GABA (0.1 or 1 g/kg) had no significant direct effect on plasma prolactin in rats in which the dopaminergic receptors were completely blocked by pimozide, nor in hypophysectomized rats in which a pituitary had been grafted under the kidney capsule and was therefore removed from any hypothalamic influence. The effects of bicuculline, a GABA-receptor-blocking agent, was examined in order to find out whether a tonic inhibition is exerted by GABA after elimination of tonic dopaminergic inhibition on prolactin secretion. The pimozide-treated rat in which the dopaminergic tone is completely eliminated did not show any prominent elevation of plasma prolactin concentration after bicuculline (300 micrograms/kg) administration. However, GABA did have an inhibitory effect in a primary pituitary cell monolayer culture system. Therefore, we conclude that GABA does not play a significant role as a physiological PIF and that the inhibitory effect of GABA in vitro is of a pharmacological nature.
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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".