Seminal plasma nerve growth factor signaling on the reproductive physiology of female llamas
Bibliographic record
Abstract
The ovulation mechanism is one of the fascinating physiological processes in reproductive biology in mammals. From the reproductive point of view, the species have been classified as spontaneous or induced ovulators. Although the release of GnRH followed by the preovulatory LH surge is shared between both types of ovulation, the stimulus to initiate GnRH release varies between both categories. In spontaneous ovulators, ovulation depends on the systemic concentration of ovarian steroids, however, in induced ovulators, different stimuli such as copulation, environmental, and social cues can facilitate or induce ovulation regardless of the increases in systemic estradiol concentration. In this review, we document evidence that a male-derived protein is the main factor responsible for inducing ovulation and also modulating the ovarian function in the domestic South American camelid, the llama. The neurotrophin beta-Nerve Growth Factor (β-NGF) is the principal factor present in the semen of llamas responsible for inducing ovulation in this species. After the intrauterine deposit of semen during mating, β-NGF is absorbed through the endometrium to reach the circulatory system, where it reaches the hypothalamus and stimulates GnRH release. The potential site of action of this neurotrophin at the brain has not been elucidated, however, hypotheses are raised that the factor may cross the blood-brain barrier and stimulate upstream neuronal networks that lead to the stimulation of GnRH-secreting neurons. It is possible that β-NGF could be sensed at the median eminence without crossing the blood-brain barrier. Finally, it has been observed that this factor is not only a powerful stimulator of ovulation but also has a luteotrophic effect, resulting in the development of a corpus luteum capable of secreting more progesterone when compared to other ovulation-stimulating analogues.
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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) | 0.002 | 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".