Exposure to Polycyclic Aromatic Hydrocarbons and adverse reproductive outcomes in women: current status and future perspectives
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
OBJECTIVES: Polycyclic Aromatic Hydrocarbons (PAHs) are ubiquitous, toxic environmental chemicals that can cause adverse reproductive health effects. The objectives of this mini-review are to highlight the adverse reproductive outcomes due to PAH exposure with the main focus on polycystic ovary syndrome (PCOS) and premature ovarian failure (POF) and to provide perspectives on future research needs. CONTENT: We reviewed studies that have reported the adverse reproductive outcomes associated with PAHs exposures in women through a comprehensive search of bibliographic databases and gray literature sources. In addition, potentially modifiable sources of exposure to PAHs and associated reproductive outcomes were also investigated. SUMMARY: A total of 232 papers were retrieved through a comprehensive search of bibliographic databases, out of which three studies met the eligibility criteria and were included in the review. Results showed that exposure to PAHs is associated with adverse reproductive outcomes defined as PCOS, POF, and reproductive hormone imbalance. Sources of PAH exposure associated with adverse reproductive outcomes include active and passive tobacco smoking, specific cooking methods, and pesticides. OUTLOOK: Future studies are warranted to examine the mechanisms by which PAHs result in adverse reproductive endpoints in women. Further, environmental exposures that are potentially modifiable such as exposure to tobacco smoke, may contribute to PAH exposure, and these exposures should be targeted in future policies and interventions.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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