Gut microbiota dysbiosis in polycystic ovary syndrome: association with obesity — a preliminary report
Bibliographic record
Abstract
The objective was to explore if and how the microbiota changed in polycystic ovary syndrome (PCOS) women compared with healthy women. Eight obese PCOS (PO group), 10 nonobese PCOS (PN group), and nine healthy normal weight women (control) (C group) were enrolled. Insulin (INS), testosterone (T), follicle-stimulating hormone (FSH), luteinizing hormone (LH), estrogen (E2), and dehydroepiandrosterone (DHEA) were detected with radioimmunoassay. Antimullerian hormone (AMH), fasting glucose, and hemoglobin A1c (HbA1c) were determined by a chemiluminescence immunoassay, glucose oxidase method, and HPLC, respectively. Gut microbiota composition was evaluated by PCR. Alpha diversity was assessed using Chao1 and the Shannon index. PCOS women showed significantly higher T, LH, and LH/FSH and lower FSH levels than the C group (p < 0.05). The AMH level was significantly higher in the PO than in the PN group (p < 0.05). The PO group presented a significantly higher fasting INS level and HMOA-IR scores than the other groups, lower observed SVs and alpha diversity than the C group, higher beta diversity than the PN group (p < 0.05), and decreased abundances of genera (mainly butyrate producers). Regression analysis showed that decreased abundances of several genera were correlated with higher circulating T and impaired glucose metabolism. PCOS is associated with changes in the gut microbiota composition. Obesity has a driving role in the development of dysbiotic gut microbiota in 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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".