Evidence that γ-Aminobutyric Acid Is Part of the Neural Circuit Mediating Estradiol Negative Feedback in Anestrous Ewes
Bibliographic record
Abstract
Seasonal anestrus in ewes is driven by an increase in response to estradiol (E2) negative feedback. Compelling evidence indicates that inhibitory A15 dopaminergic (DA) neurons mediate the increased inhibitory actions of E2 in anestrus, but these neurons do not contain estrogen receptors. Therefore, we have proposed that estrogen-responsive afferents to A15 neurons are part of the neural circuit mediating E2 negative feedback in anestrus. This study examined the possible role of afferents containing gamma-aminobutyric acid (GABA) and nitric oxide (NO) in modulating the activity of A15 neurons. Local administration of NO synthase inhibitors to the A15 had no effect on LH, but GABA receptor ligands produced dramatic changes. Administration of either a GABA A or GABA B receptor agonist to the A15 increased LH secretion in ovary-intact ewes, suggesting that GABA inhibits A15 neural activity. In ovariectomized anestrous ewes, the same doses of GABA receptor agonist had no effect, but combined administration of a GABA A and GABA B receptor antagonist to the A15 inhibited LH secretion. These data are consistent with the hypothesis that endogenous GABA release within the A15 is low in ovary-intact anestrous ewes and elevated after ovariectomy. Using dual immunocytochemistry, we observed that GABAergic varicosities make close contacts on to A15 neurons and that A15 neurons contain both the GABA A-alpha1 and the GABA B-R1 receptor subunits. Based on these data, we propose that in anestrous ewes, E2 inhibits release of GABA from afferents to A15 DA neurons, increasing the activity of these DA neurons and thus suppressing episodic secretion of GnRH and LH.
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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".