STAT3 signaling stimulates miR-21 expression in bovine cumulus cells during in vitro oocyte maturation
Bibliographic record
Abstract
MicroRNAs are potent regulators of gene expression that have been widely implicated in reproduction and embryo development. Recent studies have demonstrated that miR-21, a microRNA extensively studied in the context of disease, is important in multiple facets of reproductive biology including folliculogenesis, ovulation, oocyte maturation and early mammalian development. Surprisingly, little is known about the mechanisms that regulate miR-21 and no studies have characterized these regulatory pathways in cumulus-oocyte complexes (COCs). We therefore investigated miR-21 in an in vitro model of bovine oocyte maturation. Levels of the primary transcript of miR-21 (pri-miR-21) and mature miR-21 increased markedly in COCs over the maturation period. Cloning of the bovine pri-miR-21 gene and promoter by 5'3'RACE (rapid amplification of cDNA ends) revealed a highly conserved region immediately upstream of the transcription start site and two alternatively-spliced variants of pri-miR-21. The promoter region contained several putative transcription factor binding sites, including two for signal transducer and activator of transcription 3 (STAT3). Mutation of these sites significantly decreased both the intrinsic activity of pri-miR-21 promoter-luciferase constructs and the response to leukemia inhibitory factor (LIF) (a STAT3 activator) in cultured MCF7 cells. In COCs, treatment with a STAT3 pathway inhibitor markedly decreased pri-miR-21 expression and prevented cumulus expansion. Pri-miR-21 expression was also inhibited by the protein synthesis inhibitor cycloheximide, suggesting that a protein ligand or signaling cofactor synthesized during maturation is necessary for transcription. Together these studies represent the first investigation of signaling pathways that directly influence miR-21 expression in bovine oocytes and cumulus cells.
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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 | 0.001 |
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".