Pregnancy-Induced Perturbation of Urinary Androgenic Steroid Disposition
Bibliographic record
Abstract
OBJECTIVE: To investigate the excretion and conjugation profile of testosterone (T), Epitestosterone (EpiT), and other androgen metabolites in different phases of pregnancy and postpregnancy as a reflection of the "androgenic exposure." DESIGN: Consecutive recruitment of pregnant women. SETTING: Maternity outpatient low-risk pregnancy clinic. PATIENTS: Seventy-seven pregnant women. INTERVENTIONS: Collection of urine for analyses of sulfate (S) and glucuronide (G) conjugates and metabolic ratios of androgens and androgen metabolites using liquid chromatography-tandem mass spectrometry. MAIN OUTCOME MEASURES: Excretion profiles and metabolic ratios of G and S conjugates of T, EpiT, dehydroepiandrosterone (DHEA), androsterone (A), etiocholanolone (Etio), and dihydrotestosterone in relation to trimester and postpartum, body mass index, fetal sex, and ethnicity. RESULTS: -(17-fold) than the G-conjugate (1.6-fold). The preference for S over G conjugation was conspicuous for EpiT and DHEA (S/G ratio 2.1 and 4.7, respectively, in the third trimester), whereas the reverse was true for T, A, and Etio (S/G 0.6, 0.13, and 0.11, respectively). CONCLUSIONS: Pregnancy influences the androgen excretion profile, with the most profound change being an increase in EpiT excretion throughout the trimesters. EpiT may modulate the effect of T, but its exact role during pregnancy is not known. There were marked differences in the S/G conjugate ratios between androgens upstream and downstream from T in the metabolic network. These results are interesting to compare with the androgen disposition in women with endocrine disorders or abuse of steroids.
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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 | 0.000 | 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 | 0.000 |
| 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".