Breast Cancer and Urinary Biomarkers of Polycyclic Aromatic Hydrocarbon and Oxidative Stress in the Shanghai Women's Health Study
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbon (PAH) exposure and oxidative stress from such and other exposures have been associated with breast cancer in some studies. To further evaluate the role of PAH metabolites and oxidative stress on the development of breast cancer, we conducted a nested case-control study in the Shanghai Women's Health Study. We measured urinary 1-hydroxypyrene and 2-naphthol as PAH metabolites and urinary levels of 8-hydroxy-2'-deoxyguanosine and malondialdehyde as oxidative stress biomarkers in 327 breast cancer cases and 654 controls in the Shanghai Women's Health Study. Information on demographic characteristics, past medical history, lifestyles, history of menstruation, pregnancy history, eating and drinking habit, history of residence, employment history, family history, husband's information, and physical activity were collected by a self-administered questionnaire. The mean age was 52.3 in breast cancer cases (n = 354) and 52.5 in controls (n = 708). Age at menarche (P = 0.04), months of breast-feeding the first baby (P = 0.05), and grade of education (P(trend) < 0.01) were significantly different between cases and controls. No association was observed for PAH metabolites and the oxidative stress biomarkers of urinary malondialdehyde and 8-hydroxy-2'-deoxyguanosine and risk of breast cancer. This nested case-control study provides no evidence of association between PAH exposure and oxidative stress and risk of breast cancer in Shanghai women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".