Expression of long noncoding RNAs in the ovarian granulosa cells of women with diminished ovarian reserve using high-throughput sequencing
Bibliographic record
Abstract
BACKGROUND: Infertility is a global reproductive-health problem, and diminished ovarian reserve (DOR) is one of the common causes of female infertility. Long noncoding RNAs (lncRNAs) are crucial regulators of numerous physiological and pathological processes in humans. However, whether lncRNAs are involved in the development of DOR remains to be elucidated. METHODS: Ovarian granulosa cells (OGCs) extracted from infertile women with DOR and from women with normal ovarian reserve (NOR) were subjected to high-throughput sequencing. Comprehensive bioinformatics analysis was conducted to identify the differential expression of messenger RNAs (mRNAs) and lncRNAs. Sequencing results were validated by the selection of lncRNAs and mRNAs using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). RESULTS: Compared with the NOR group, a total of 244 lncRNAs were upregulated (53 known and 191 novel), and 222 lncRNAs were downregulated (36 known and 186 novel) in the DOR group. Similarly, 457 mRNAs had differential expression between the two groups. Of these, 169 were upregulated and 288 were downregulated. Bioinformatics analysis revealed that the differentially expressed genes of mRNA and lncRNAs were considerably enriched in "cell adhesion and apoptosis", "steroid biosynthesis", and "immune system". A co-expression network comprising lncRNAs and their predicted target genes revealed the possible involvement of the "thyroid hormone signaling pathway" and "protein binding, digestion and absorption" in DOR pathogenesis. The expression of SLC16A10 was positively regulated by multiple lncRNAs. After RT-qPCR validation of seven differentially expressed lncRNAs and mRNAs, respectively, the expression of lncRNA NEAT1, GNG12, ZEB2-AS1, and mRNA FN1, HAS3, RGS4, SUOX were in accordance with RNA-sequencing. CONCLUSIONS: We presented the first data showing that the expression profiles of lncRNA and mRNA in OGCs between NOR and DOR patients using RNA sequencing. The lncRNAs and mRNAs that we identified may serve as novel diagnostic biomarkers for patients with DOR.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".