Altered D-<i>Chiro</i>-Inositol Urinary Clearance in Women With Polycystic Ovary Syndrome
Bibliographic record
Abstract
OBJECTIVE: Evidence suggests that some actions of insulin are effected by inositolphosphoglycan (IPG) mediators. We hypothesize that a deficiency in D-chiro-inositol (DCI) and/or a DCI-containing IPG (DCI-IPG) may contribute to insulin resistance in humans. RESEARCH DESIGN AND METHODS: To assess this possibility in polycystic ovary syndrome (PCOS), we determined insulin sensitivity (Si by frequently sampled intravenous glucose tolerance test), plasma and urinary DCI and myo-inositol (MYO) levels (by gas chromatography/mass spectrometry), and the release of insulin and DCI-IPG during the oral glucose tolerance test (area under the curve [AUC]) in 23 women with PCOS and 26 normal women. RESULTS: Women with PCOS were heavier than control subjects (P = 0.002 for BMI), but also had decreased Si (P < 0.001) and increased AUC(insulin) (P < 0.001) compared with normal women, even when corrected for BMI. The urinary clearance of DCI (uCl(DCI)) was increased almost sixfold in PCOS compared with normal women (P = 0.001), but not MYO clearance (P = 0.10). uCl(DCI) correlated inversely with Si when all women were analyzed together (n = 49, r = -0.50, P < 0.001) and was one of the three best independent parameters predicting Si. Finally, the ratio of AUC(DCI-IPG) to AUC(insulin) was decreased threefold in women with PCOS (P < 0.001). CONCLUSIONS: uCl(DCI) is inversely correlated with insulin sensitivity in women and is a strong independent predictor of insulin resistance in multivariate models. PCOS, which is characterized by insulin resistance, is associated with a selective increase in uCl(DCI) and impaired DCI-IPG release in response to insulin. These findings are consistent with a defect in tissue availability or utilization of DCI in PCOS that may contribute to the insulin resistance of the syndrome.
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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 | 0.002 |
| 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".