MicroRNA-378 regulates oocyte maturation via the suppression of aromatase in porcine cumulus cells
Bibliographic record
Abstract
We sought to investigate whether miR-378 plays a role in cumulus cells and whether the manipulation of miRNA levels in cumulus cells influences oocyte maturation in vitro. Cumulus-oocyte complexes (COCs) from ovarian follicles had significantly lower levels of precursor and mature miR-378 in cumulus cells surrounding metaphase II (MII) oocytes than cumulus cells surrounding germinal vesicle (GV) oocytes, suggesting a possible role of miR-378 during COC maturation. Overexpression of miR-378 in cumulus cells impaired expansion and decreased expression of genes associated with expansion (HAS2, PTGS2) and oocyte maturation (CX43, ADAMTS1, PGR). Cumulus cell expression of miR-378 also suppressed oocyte progression from the GV to MII stage (from 54 ± 2.7 to 31 ± 5.1%), accompanied by a decrease of growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15), zona pellucida 3 (ZP3), and CX37 in the oocytes. Subsequent in vitro fertilization resulted in fewer oocytes from COCs overexpressing miR-378 reaching the blastocyst stage (7.3 ± 0.7 vs. 16.6 ± 0.5%). miR-378 knockdown led to increased cumulus expansion and oocyte progression to MII, confirming a specific effect of miR-378 in suppressing COC maturation. Aromatase (CYP19A1) expression in cumulus cells was also inhibited by miR-378, leading to a significant decrease in estradiol production. The addition of estradiol to IVM culture medium reversed the effect of miR-378 on cumulus expansion and oocyte meiotic progression, suggesting that decreased estradiol production via suppression of aromatase may be one of the mechanisms by which miR-378 regulates the maturation of COCs. Our data suggest that miR-378 alters gene expression and function in cumulus cells and influences oocyte maturation, possibly via oocyte-cumulus interaction and paracrine regulation.
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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".