Bisphenol S and Bisphenol A disrupt morphogenesis of MCF-12A human mammary epithelial cells
Bibliographic record
Abstract
Breast cancer is one of the most common cancers diagnosed in women worldwide. Genetic predisposition, such as breast cancer 1 (BRCA1) mutations, account for a minor percentage of the total breast cancer incidences. And thus, many life style factors have also been linked to the disease such as smoking, alcohol consumption and obesity. Emerging studies show that environmental pollutants may also play a role. Bisphenol-A (BPA) has been suspected to contribute to breast cancer development, and has been shown to affect mammary gland development amongst other effects. This prompted its replacement with other bisphenol analogs such as, bisphenol-S (BPS). In this study we used the human mammary epithelial cells, MCF-12A, grown in extracellular matrix to investigate the ability of BPA and BPS to disrupt mammary epithelial cells organization. We show that both BPA and BPS were equipotent in disrupting the organization of the acinar structures, despite BPS being less oestrogenic by other assays. Further, treatment with both compounds enabled the cells to invade the lumen of the structures. This study shows that BPS and BPA are environmental pollutants that may affect mammary development and may contribute to the development of breast cancer.
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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 | 0.000 |
| 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) | 0.001 | 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".