Serum Concentrations of GDF9 and BMP15 Across the Menstrual Cycle
Bibliographic record
Abstract
Abstract Growth differentiation factor-9 (GDF9) and bone morphogenetic protein-15 (BMP15) are TGF-β proteins that regulate key processes throughout folliculogenesis and are determinants of mammalian fecundity (1). They are uniquely produced predominantly by the oocyte and have potential clinical application as markers of oocyte quality and quantity (2). However, no studies have been conducted to assess whether serum concentrations alter across the different phases of the menstrual cycle, and thus if assessment should be confined to specific cycle stages. The aim of this study was to measure serum concentrations of these proteins during the menstrual cycle in women at different stages of reproductive life. Serum was collected every 1-3 days throughout the menstrual cycle from 41 healthy ovulatory women from three cohorts: menses to late luteal phase (21-29 years of age; n=16; University of Otago) and across one interovulatory interval (18-35 years of age; n=10; and 45-50 years of age; n=15; University of Saskatchewan), with simultaneous ultrasound scans confirming ovulation. Serum concentrations of GDF9, BMP15, estradiol, FSH, LH, progesterone, inhibin A and B and AMH were measured. GDF9 and BMP15 were detectable in 54% and 73% of women and varied 236- and 52-fold between women, respectively. To detect changes, mean concentrations and variances across the cycle were statistically modelled using a generalized additive model of location, shape and scale (GAMLSS). Across the menstrual cycle, there were minimal changes in serum GDF9 or BMP15 within a woman for all cohorts, with no significant differences detected in modelled mean concentrations. However, modelled variances were highest in the luteal phases of all women for BMP15 immediately following ovulation, regardless of age, suggesting a possible underlying cyclic pattern. These results suggest that serum BMP15 and GDF9 are not overtly affected by menstrual cycle dynamics but may be more stable in the follicular phase. Larger studies with more frequent sampling should establish if BMP15 and presumably GDF9 demonstrate clinically relevant cyclic variation. References: (1) Gilchrist RB et al., HRU 2008; 14:159-77. (2) Riepsamen AH et al., Endocrinol 2019; 160:2298-313.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".