Determinants of breast tissue composition in young women
Bibliographic record
Abstract
B153 Background . Variations in breast tissue composition in middle life, as shown by the extent of radiologically dense (fibroglandular) breast tissue, are strongly associated with differences in risk of breast cancer. Although dense breast tissue is most common at early ages, and decreases in frequency with increasing age, little is known about the factors that influence breast density at early ages. > Methods. Recruitment of healthy young women (aged 15-30 years) and their mothers took place at local schools and mammography clinics. We used magnetic resonance (MR) imaging to generate quantitative estimates of the fat and water content of breast tissue in young women. We examined factors likely to be associated with variation in these measurements, in particular the relationship with lifestyle factors and hormones and growth factors that influence the growth and development of breast tissue. All MR studies were carried out during the follicular phase of the menstrual cycle, and blood was taken for hormone assays on the day of the study. Mammograms from the mothers of the young women examined were obtained and measured for density, and a subset of mothers also had MR studies. > Results. To date 254 young women have been examined. The water content of the breast on MR is shown to be highly variable and correlated with blood levels of growth hormone and sex hormone binding globulin. No correlation is seen for total estradiol, testosterone, progesterone, prolactin or insulin-like growth factor-I. The water content of the breast in young women is also correlated with the measured dense tissue in the mammograms of their mothers. Among mothers, mammographic density and water content by MR are also strongly correlated. Further, environmental factors, including current use of oral contraceptives and use of soy-based infant formula are associated with variations in breast water content. > Conclusion. The tissue composition of the breast in young women is highly variable and associated with variations in circulating levels of growth hormone, a breast mitogen. The mother-daughter correlation is consistent with a genetic influence. The environmental findings suggest potential mechanisms for effects of these environmental factors on breast cancer risk.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".