Detection of serum antimüllerian hormone in women approaching menopause using sensitive antimüllerian hormone enzyme-linked immunosorbent assays
Bibliographic record
Abstract
OBJECTIVE: Current antimüllerian hormone (AMH) immunoassays are insufficiently sensitive to detect circulating AMH levels in ovulatory women approaching menopause. The aim of this study was to detect serum AMH levels across the menstrual cycle with age, using two new AMH enzyme-linked immunosorbent assay (ELISA) kits with increased sensitivity and differing specificity. METHODS: Serum AMH levels were determined every 2 to 3 days across the interovulatory interval of menstrual cycles among women of early-mid reproductive age (18-35 y; n = 10) and late reproductive age (45-55 y; n = 17). Two highly sensitive AMH ELISAs (designated 24/32 and 24/37) with differing sensitivities were developed and applied to sera using a recombinant human pro-mature AMH preparation as reference. A third AMH ELISA (Gen II AMH ELISA kit; Beckman Coulter, Brea, CA) used was directed on mature-pro regions of AMH. RESULTS: AMH levels in all cycles were detectable with the 24/32 and 24/37 AMH ELISAs. AMH levels across the menstrual cycle were highly correlated (r = 0.98) between the 24/32 and 24/37 AMH ELISAs and the Gen II AMH ELISA (r = 0.94), but with large intracycle variations observed in older women. In late reproductive age, more than 95% of AMH values were detectable with the 24/32 and 24/37 AMH ELISAs, whereas only 36% of AMH values were detectable with the Gen II AMH ELISA. AMH levels were detected in cycles with lower antral follicle count and at a later age using the 24/32 and 24/37 AMH ELISAs compared with the Gen II AMH ELISA. AMH level correlated with antral follicle count in younger women, but not in older women. CONCLUSIONS: The new 24/32 and 24/37 AMH ELISAs have the sensitivity to monitor ovarian follicle profiles in late reproductive age.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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 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".