miR-106a Increases Granulosa Cell Viability and Is Downregulated in Women With Diminished Ovarian Reserve
Bibliographic record
Abstract
Context: Women with diminished ovarian reserve (DOR) have reduced fertility, cardiovascular events, and osteoporosis. Although differential microRNA (miRNA) expression has been described in several ovarian disorders, little is known about the role of miRNAs in the pathogenesis of DOR. Objective: Identify differentially expressed miRNAs in DOR and explore the role of miR-106a in human granulosa cell proliferation. Design: miRNA microarray (n = 3) and quantitative reverse transcription polymerase chain reaction (n = 30) were used to examine miRNA expression in serum and granulosa cells from normal-cycling and women with DOR. Primary human granulosa cells were treated alone or in combination with miR-106a mimic, miR-106a inhibitor, apoptosis signal-regulating kinase 1 (ASK1) small interfering RNA (siRNA), or p38 mitogen-activated protein kinase (MAPK) inhibitor (SB203580) before assessment of cell viability and apoptosis. Western blot was used to measure ASK1 protein and phosphorylation/activation of p38 MAPK. Binding of miR-106a to ASK1 mRNA was examined by 3' untranslated region (3'UTR) luciferase analysis. Results: Fifteen miRNAs were differentially expressed (n = 30), and miR-106a was downregulated in serum and granulosa cells of women with DOR. miR-106a mimic increased cell viability and attenuated apoptosis, whereas the converse occurred following treatment with miR-106a inhibitor. miR-106a suppressed ASK1 expression by directly targeting its 3'UTR. miR-106a inhibitor increased p38 MAPK phosphorylation/activation, and this effect was abolished by treatment with ASK1 siRNA. Whereas knockdown of ASK1 abolished the effects of miR-106a inhibitor on cell viability/apoptosis, pretreatment with SB203580 did not significantly alter the effects of miR-106a inhibitor. Conclusions: Downregulation of miR-106a may contribute to the pathogenesis of DOR by reducing granulosa cell viability and promoting apoptosis via enhanced ASK1 signaling.
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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 | 0.005 | 0.003 |
| 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 | 0.003 |
| 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".