MicroRNA-21 enhances estradiol production by inhibiting WT1 expression in granulosa cells
Bibliographic record
Abstract
In antral follicles, the transition of proliferative granulosa cells to estradiol-producing is critical for proper oocyte maturation. MicroRNAs are noncoding RNAs that play important roles in ovarian follicular development; however, this has yet to be fully characterized. MicroRNA-21 is significantly higher in granulosa cells isolated from large antral follicles compared to those from small antral follicles. To investigate the function of miR-21, porcine granulosa cells were transfected with miR-21 mimic or miR-21 targeted siRNA. Cells with the miR-21 mimic had higher aromatase expression and estradiol production but decreased WT1 expression. Conversely, cells with the miR-21 siRNA secreted less estradiol and had higher WT1 expression. We hypothesized that miR-21 promotes estradiol production by inhibiting WT1 protein synthesis. We found a potential miR-21 binding site in the 3'UTR of the WT1 transcript and performed a dual-luciferase reporter assay using the WT and mutated 3'UTR. Compared to the negative control, the miR-21 mimic induced a significant decrease in luciferase activity in the WT 3'UTR. This decrease was reversed when the 3'UTR was mutated, suggesting miR-21 targets this site to inhibit WT1 expression. We next transfected porcine granulosa cells with WT1 targeted siRNA and observed a significant increase in aromatase expression and estradiol secretion. We propose that miR-21 represses WT1 expression in granulosa cells to potentially promote aromatase expression and estradiol production. This study offers the first report of a microRNA regulating WT1 expression in granulosa cells and reveals the role of miR-21 in WT1's regulation of estradiol production.
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 | 0.001 |
| 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 | 0.001 |
| 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".