Long non-coding RNA-X-inactive specific transcript inhibits cell viability, and induces apoptosis through the microRNA-30c-5p/Bcl2-like protein 11 signaling axis in human granulosa-like tumor cells
Bibliographic record
Abstract
The role of long noncoding RNAs (lncRNAs) is being actively explored in polycystic ovary syndrome (PCOS). Recent research has shown that long non-coding RNA (lncRNA) X–inactive Specific Transcript (XIST) is overexpressed in patients with PCOS and is associated with poor pregnancy outcomes. However, the precise function and mechanism of action of lncRNA XIST in PCOS are unknown. We aimed to determine whether lncRNA XIST contributes to PCOS by modulating ovarian granulosa cell physiology. We also investigated any potential molecular regulatory mechanisms. In this study, we discovered that the lncRNA XIST was significantly downregulated in human ovarian granulosa-like tumor (KGN) cells. Notably, overexpression of lncRNA XIST decreased miR-30c-5p expression in KGN cells, inhibited proliferation, and induced apoptosis in KGN cells. However, cotransfection with amiR-30c-5p mimic significantly reduced these effects. Additionally, we discovered that the miR-30c-5p mimic effectively inhibited Bcl2-like protein 11 (BCL2L11) expression, a critical apoptotic promoter, whereas silencing of miR-30c-5p increased BCL2L11 expression, inhibited KGN cell proliferation, and induced apoptosis. In contrast, cotransfection of BCL2L11 with siRNA significantly reversed these effects. In conclusion, this study established that lncRNA XIST plays a critical role in PCOS by modulating the miR-30c-5p/BCL2L11 signaling axis and regulating ovarian granulosa cell physiology.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".