RANKL and OPG and their influence on breast volume changes during pregnancy in healthy women
Bibliographic record
Abstract
Breast cancer risk is reduced by number of pregnancies and breastfeeding duration, however studies of breast changes during or after pregnancy are rare. Breast volume changes - although not linked to breast cancer risk - might be an interesting phenotype in this context for correlative studies, as changes of breast volume vary between pregnant women. Serum receptor activator of nuclear factor kappa B ligand (RANKL) and its antagonist osteoprotegerin (OPG) were measured prospectively before gestational week 12, and three-dimensional breast volume assessments were performed. A linear regression model including breast volume at the start of pregnancy, RANKL, OPG, and other factors was used to predict breast volume at term. The mean breast volume was 413 mL at gestational week 12, increasing by a mean of 99 mL up to gestational week 40. In addition to body mass index and breast volume at the beginning of pregnancy, RANKL and OPG appeared to influence breast volume with a mean increase by 32 mL (P = 0.04) and a mean reduction by 27 mL (P = 0.04), respectively. Linking the RANKL/RANK/OPG pathway with breast volume changes supports further studies aiming at analysing breast changes during pregnancy with regard to breast cancer risk.
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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 | 0.000 | 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".