Distinct sex differences in the production of steroids and neuropeptides in the adult zebrafish brain-pituitary gonadal axis
Bibliographic record
Abstract
Abstract Zebrafish are increasingly used as experimental models in studies of human disease, environmental toxicology, and reproductive biology. However, sex differences in hormone production are rarely examined, despite evidence from gene mutation studies indicating differential effects in females and males. The emerging reproductive peptide secretoneurin (SN) has not been quantitatively compared between sexes in any species. Here, we employed a newly developed extraction and LC-MS method to simultaneously quantify and compare levels of five steroids and thirteen peptides in brain, pituitary, and gonads. As expected, testosterone (T) and 11-ketotestosterone (11-KT) were higher in male tissues, while estrone (E1) and estradiol (E2) were elevated in the female pituitary/ovary and brain, respectively. Estriol (E3) was more abundant in testes. Gonadotropin-releasing hormones Gnrh2 and Gnrh3 were notably higher in testes. Oxytocin (isotocin) and vasopressin (vasotocin) were elevated in the female brain and in testes. Kisspeptins 1 and 2 also showed higher levels in testes. Similarly, SNa and SNb were more abundant in the female brain and pituitary, and markedly higher in testes than ovaries. Several smaller SN fragments were detected at low levels, with patterns suggesting sex-specific enzymatic processing. These findings reveal pronounced sex differences in both classical and emerging reproductive hormones and identify the SN peptide family as a new component of the brain–pituitary–gonadal axis. This dataset provides a foundation for future studies on sexually differentiated neuropeptide production and function across tissues.
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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".