Genome-Wide Analysis of Low Dose Bisphenol-A (BPA) Exposure in Human Prostate Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Endocrine disrupting compounds (EDCs) have the potential to cause adverse effects on wild-life and human health. Two important EDCs are the synthetic estrogen 17α-ethynylestradiol (EE2) and bisphenol-A (BPA) both of which are xenoestrogens (XEs) as they bind the estrogen receptor and dis-rupt estrogen physiology in mammals and other vertebrates. In the recent years the influence of XEs on oncogenes, specifically in relation to breast and prostate cancer has been the subject of considerable study. METHODOLOGY: In this study, healthy primary human prostate epithelial cells (PrECs) were exposed to environmentally relevant concentrations of BPA (5nM and 25nM BPA) and interrogated using a whole genome microarray. RESULTS: Exposure to 5 and 25nM BPA resulted in 7,182 and 7,650 differentially expressed (DE) genes, respectively in treated PrECs. Exposure to EE2 had the greatest effect on the PrEC transcriptome (8,891 DE genes). CONCLUSION: We dissected and investigated the nature of the non-estrogenic gene signature associated with BPA with a focus on transcripts relevant to epigenetic modifications. The expression of transcripts encoding nuclear hormone receptors as well as histone and DNA methylation, modifying enzymes were significantly perturbed by exposure to BPA.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it