Inhibition of Premature Oocyte Maturation: A Role for Bone Morphogenetic Protein 15 in Zebrafish Ovarian Follicles
Bibliographic record
Abstract
Bone morphogenetic protein-15 (BMP-15) is a member of the TGF-beta superfamily known to regulate ovarian functions in mammals. Recently, we cloned zebrafish BMP-15 (zfBMP-15) cDNA and demonstrated that it may play a role in oocyte maturation. In this study, we further investigated the role of BMP-15 in zebrafish follicular development and oocyte maturation using an antiserum developed for zfBMP-15 and by microinjection of follicles with antisense zfBMP-15 N-morpholino oligonucleotides or an expression construct containing zfBMP-15 cDNA. Injection with antiserum caused a significant decrease in maturation-incompetent [insensitive to maturation-inducing hormone (MIH)] early growth phase follicles and a concomitant increase in mature follicles in vivo. In vitro maturation assays showed that incubation with antiserum resulted in a significant increase in oocyte maturation as compared with follicles incubated in preimmune serum or media control. Next, early growth phase follicles were collected and preincubated with either antiserum, preimmune serum, or medium control before treatment with MIH or human chorionic gonadotropin (hCG). Antiserum significantly increased oocyte maturation in response to MIH, but not to hCG, and enhanced basal maturation rate in longer-term incubations. Knockdown of BMP-15 in early growth stage follicles with a BMP-15 antisense oligonucleotide resulted in increased oocyte maturation, whereas microinjection of BMP-15 cDNA into oocytes significantly reduced MIH- and hCG-induced oocyte maturation in normally competent, mid-growth-phase follicles. Collectively, these findings suggest that BMP-15 modulates follicular growth and prevents premature oocyte maturation in zebrafish, in part, by suppressing the sensitivity of follicles to MIH.
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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".