Altered expression of miRNAs in a dihydrotestosterone-induced rat PCOS model
Bibliographic record
Abstract
BACKGROUND: The polycystic ovary syndrome (PCOS) is a complex and heterogeneous endocrine condition characterized by hyperandrogenism, hyperinsulinemia, insulin resistance and chronic anovulation. Regulation and interaction of a multitude of genes required for follicular development are found to be altered in PCOS. MicroRNAs (miRNAs) mediate posttranscriptional gene regulation by binding to the 3´ untranslated region of mRNAs to either inhibit or enhance translation. However, the extent and regulation of miRNA expression in PCOS is poorly understood and the current study is the first to describe altered expression of miRNAs in PCOS. METHODS: A chronically androgenized [5α-dihydrotestosterone (DHT)-treated] rat model which recapitulates many of the phenotypes of human PCOS, and miRNA PCR array was used to investigate the expression of 349 miRNAs in DHT treated rat ovaries. The ovarian expression of several selected miRNAs was also analyzed by in situ localization experiment. RESULTS: DHT-treated rats exhibit increased body weight, disrupted estrus cyclicity, decreased insulin sensitivity and decreased ovarian weight, with the latter phenomenon readily rescued by gonadotropin treatment in vivo. In general, 24% of the 349 miRNAs investigated were found to be differentially expressed between DHT-treated and control rats. Most of the differentially expressed miRNAs were found to be predominantly localized in the theca cells of the follicles. In silico analysis of the potential target genes of dysregulated miRNAs revealed their possible involvement in various pathways in the regulation of ovarian function. CONCLUSION: Our current findings suggest that miRNAs are differentially regulated in hyperandrogenism, a condition possibly involved in the dysregulation of steroid hormone receptors and intra-ovarian factors, and that miRNAs may be involved in the etiology of PCOS.
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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 | 0.001 | 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".