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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".