Hormonal dynamics reveal a stimulatory role for secretoneurin in zebrafish ovulation
Bibliographic record
Abstract
Abstract Surge release of luteinizing hormone (Lh) from the pituitary is essential for fertility as it triggers ovulation. While secretoneurin (SN) is a phylogenetically conserved secretogranin-2-derived peptide that stimulates Lh, its role in ovulation has not been established. To directly compare periovulatory changes in the classical hormones to the emerging reproductive neuropeptides SNa and SNb, simultaneous mass spectrometry measurement of 9 peptides and 5 steroids was conducted in female zebrafish. Regression analysis indicated that levels of SNa1–34 in the brain peaked when type 3 gonadotropin-releasing hormone (Gnrh3) increased (R2 = 0.71) at the time of the Lh surge, 3.5 h before ovulation. Levels of the naturally occurring derivative SNa1–14 were highest at ovulation, while SNb1–31 was invariable. The bioactivities of SNa1–34 and SNa1–14 were investigated. After injection of SNa1–34 in females that had been isolated from males, 61% (11/18) ovulated within 6 h, which was like the effects of the Lh analog human chorionic gonadotropin (72%; 13/18 females). SNa1–34 injection induces ovulation by increasing time-dependent expression of gnrh3 in the brain, a likely direct stimulation of chorionic gonadotropin alpha (cga) and luteinizing hormone b (lhb) subunit in pituitary, and via the subsequent time-dependent increase in nuclear progesterone receptor (npr) in ovaries. In contrast, SNa1–14 exhibited far fewer effects on gene expression and did not induce ovulation. Our results support the proposal that SN is a reproductive hormone.
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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 | 0.001 |
| 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".