Impacts of endocrine-disrupting chemicals on prostate function and cancer
Bibliographic record
Abstract
Because of their historical mode of action, endocrine-disrupting chemicals (EDCs) are associated with sex-steroid receptors, namely the two estrogen receptors (ERα and ERβ) and the androgen receptor (AR). Broadly, EDCs can modulate sex-steroid receptor functions. They can also indirectly impact the androgen and estrogen pathways by influencing steroidogenesis, expression of AR or ERs, and their respective activity as transcription factors. Additionally, many of these chemicals have multiple cellular targets other than sex-steroid receptors, which results in a myriad of potential effects in humans. The current article reviews the association between prostate cancer and the endocrine-disrupting functions of four prominent EDC families: bisphenols, phthalates, phytoestrogens, and mycoestrogens. Results from both in vitro and in vivo models are included and discussed to better assess the molecular mechanisms by which EDCs can modify prostate biology. To overcome the heterogeneity of results published, we established common guidelines to properly study EDCs in the context of endocrine diseases. Firstly, the expression of sex-steroid receptors in the models used must be determined before testing. Then, in parallel to EDCs, pharmacological compounds acting as positive (agonists) and negative controls (antagonists) have to be employed. Finally, EDCs need to be used in a precise range of concentrations to modulate sex-steroid receptors and avoid off-target effects. By adequately integrating molecular endocrinology aspects in EDC studies and identifying their underlying molecular mechanisms, we will truly understand their impact on prostate cancer and distinguish those that favor the progression of the disease from those that slow down tumor development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".