Maternal exposure to polycyclic aromatic hydrocarbons diminishes murine ovarian reserve via induction of Harakiri
Bibliographic record
Abstract
Maternal smoking during pregnancy is associated with a variety of adverse neonatal outcomes including altered reproductive performance. Herein we provide molecular evidence for a pathway involved in the elimination of the female germline due to prepregnancy and/or lactational exposure to polycyclic aromatic hydrocarbons (PAHs), environmental toxicants found in cigarette smoke. We show that ovaries of offspring born to mice exposed to PAHs contained only a third of the ovarian follicle pool compared with offspring of unexposed female mice. Activation of the cell death pathway in immature follicles of exposed females was mediated by the aryl hydrocarbon receptor (Ahr), as ovarian reserve was fully rescued by maternal cotreatment with the Ahr antagonist, resveratrol, or by inactivation of the Ahr gene. Furthermore, in response to PAHs, Ahr-mediated activation of the harakiri, BCL2 interacting protein (contains only BH3 domain), was necessary for execution of cell death. This pathway appeared to be conserved between mouse and human, as xenotransplanted human ovarian cortex exposed to PAHs responded by activation of the identical cell death cascade. Our data indicate that maternal exposure to PAHs prior to pregnancy and/or during lactation compromises ovarian reserve of female offspring, raising the concern about the transgenerational impact of maternal smoking on ovarian function in the human.
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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 | 0.001 |
| 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".