Neurokinin B Acts via the Neurokinin-3 Receptor in the Retrochiasmatic Area to Stimulate Luteinizing Hormone Secretion in Sheep
Bibliographic record
Abstract
Recent data have demonstrated that mutations in the receptor for neurokinin B (NKB), the NK-3 receptor (NK3R), produce hypogonadotropic hypogonadism in humans. These data, together with reports that NKB expression increases after ovariectomy and in postmenopausal women, have led to the hypothesis that this tachykinin is an important stimulator of GnRH secretion. However, the NK3R agonist, senktide, inhibited LH secretion in rats and mice. In this study, we report that senktide stimulates LH secretion in ewes. A dramatic increase in LH concentrations to levels close to those observed during the preovulatory LH surge was observed after injection of 1 nmol senktide into the third ventricle during the follicular, but not in the luteal, phase. Similar increases in LH secretion occurred after insertion of microimplants containing this agonist into the retrochiasmatic area (RCh) in anestrous or follicular phase ewes. A low-dose microinjection (3 pmol) of senktide into the RCh produced a smaller but significant increase in LH concentrations in anestrous ewes. Moreover, NK3R immunoreactivity was clearly evident in the RCh, although it was not found in A15 dopaminergic cell bodies in this region. These data provide evidence that NKB stimulates LH (and presumably GnRH) secretion in ewes and point to the RCh as one important site of action. Based on these data, and the effects of NK3R mutations in humans, we hypothesize that NKB plays an important stimulatory role in the control of GnRH and LH secretion in nonrodent species.
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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".