Characterization of the mRNA expression of StAR and steroidogenic enzymes in zebrafish ovarian follicles
Bibliographic record
Abstract
The objective of this study was to investigate the levels of expression of steroid biosynthetic enzymes and steroidogenic acute regulatory protein (StAR) at different stages of ovarian follicular development in zebrafish (Danio rerio), and to investigate the sites within the steroid biosynthetic pathway that may be regulated by gonadotropins. Ovarian follicles of sexually mature fish were separated into primary, previtellogenic, vitellogenic, and mature stages and the expression of StAR, P450 side chain cleavage (P450scc), 3beta-hydroxysteroid dehydrogenase (3beta-HSD), P450 hydroxylase/lyase (P450c17), 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1), 17beta-hydroxysteroid dehydrogenase type 3 (17beta-HSD3), and P450 aromatase (P450aromA) was determined by Real time RT-PCR. The expression of all genes changed significantly as follicles grew, with a decrease in the expression of StAR, P450scc, 3beta-HSD and P450c17 with maturation, and an increase in the expression of 17beta-HSD3 during vitellogenesis and 17beta-HSD1 and P450aromA during previtellogenesis. In vitro incubation of vitellogenic follicles demonstrated that the expression of StAR, 17beta-HSD3, and P450aromA increased in response to hCG, and decreased in the absence of hCG. In contrast, the expression of P450scc, 3beta-HSD, P450c17, and 17beta-HSD1 remained constant between treatments and over time. Testosterone and estradiol production in the culture medium was stimulated by human chorionic gonadotropin (hCG). These experiments aid in the characterization of the roles and regulation of steroids throughout ovarian development, and suggest that gonadotropins play a key role in the regulation of StAR, 17beta-HSD3, and P450aromA in zebrafish.
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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".