Molecular regulation of miR-378 on the development of mouse follicle and the maturation of oocyte in vivo
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small, endogenous, non-coding RNAs which can bind to completely or partially complementary sequences in the 3'UTR of target mRNAs, therefore degrading the mRNA or repressing translation. We previously reported that miR-378 played a role in estradiol production via suppression of aromatase translation in porcine granulosa cells and could affect oocyte maturation in vitro by inhibiting cumulus cell expansion. However, the role of miR-378 on ovary development in vivo is unknown. The current study aimed to uncover the molecular mechanism of miR-378 in regulating mouse follicular development via micro-injection of CMV-miR-378 lentivirus into the bursa of mouse ovary. The results showed that CMV-miR-378 lentivirus transduction in the mouse ovaries resulted in reduced ovary size, extended oestrous cycle (6-7 d in miR-378 overexpression group and 4-5 dyas in GFP control group) due to continuous oestrum, decreased percentage of oocytes in vitro maturation rate (IVM 60.8% vs. 89.4% in GFP control), increased apoptosis rate (Bax/Bcl2 in mRNA and protein level), decreased expression of genes associated with gap junction, such as connexin 43 (Cx-43) and connexin (Cx-37) and decreased expression of genes associated with follicular development, such as BMP15 and GDF9. Moreover, the number of pups/litter was consistently lower in the miR-378 group in each batch of the paired breeding. Our data suggest that miR-378 alters gene expression in cumulus cells and indirectly influences oocyte maturation competency, possibly via inhibition of oocyte-cumulus interaction or induction of apoptosis.
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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".