The Kisspeptin/Neurokinin B/Dynorphin (KNDy) Cell Population of the Arcuate Nucleus: Sex Differences and Effects of Prenatal Testosterone in Sheep
Bibliographic record
Abstract
Recent work in sheep has identified a neuronal subpopulation in the arcuate nucleus that coexpresses kisspeptin, neurokinin B, and dynorphin (referred to here as KNDy cells) and that mediate the negative feedback influence of progesterone on GnRH secretion. We hypothesized that sex differences in progesterone negative feedback are due to sexual dimorphism of KNDy cells and compared neuropeptide and progesterone receptor immunoreactivity in this subpopulation between male and female sheep. In addition, because sex differences in progesterone negative feedback and neurokinin B are due to the influence of testosterone (T) during fetal life, we determined whether prenatal T exposure would mimic sex differences in KNDy cells. Adult rams had nearly half the number of kisspeptin, neurokinin B, dynorphin, and progesterone receptor-positive cells in the arcuate nucleus as did females, but the percentage of KNDy cells colocalizing progesterone receptors remained high in both sexes. Prenatal T treatment also reduced the number of dynorphin, neurokinin B, and progesterone receptor-positive cells in the female arcuate nucleus; however, the number of kisspeptin cells remained high and at levels comparable to control females. Thus, sex differences in kisspeptin in the arcuate nucleus, unlike that of dynorphin and neurokinin B, are not due solely to exposure to prenatal T, suggesting the existence of different critical periods for multiple peptides coexpressed within the same neuron. In addition, the imbalance between inhibitory (dynorphin) and stimulatory (kisspeptin) neuropeptides in this subpopulation provides a potential explanation for the decreased ability of progesterone to inhibit GnRH neurons in prenatal T-treated ewes.
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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".