Molecular Actions of Polyhalogenated Arylhydrocarbons (PAHs) in Female Reproduction
Bibliographic record
Abstract
Polyhalogenated aromatic arylhydrocarbons (PAHs) such as polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), the polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are persistent lipophilic pollutants, which affect female fertility resulting in severe reproductive dysregulation, including anovulation, reduced conception rates, abortion, menstrual abnormalities and developmental defects of female reproductive tissues. Many PAHs exert their effects by activating a family of basic helix-loop-helix (bHLH) transcription factors, the arylhydrocarbon receptor (AhR) and the arylhydrocarbon receptor nuclear translocator (ARNT), which result in the expression of AhR target molecules. Complex interactions between PAH-mediated AhR activation and ER signalling pathways have been discovered which may contribute to the developmental malformations, impact on reproductive dysfunctions and promote carcinogenic dedifferentiation of tissues within the female reproductive tract. This review will focus on the multifaceted roles of PAHs in key organs of the female reproductive tract, the ovary, uterus/ endometrium and the mammary gland. The complexity and diversity of actions unleashed by PAHs in these female reproductive tissues identify these environmental pollutants as important endocrine disrupting toxicants impacting on female fertility.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".