<i>In Utero</i> Exposure to Benzo[<i>a</i>]pyrene Induces Ovarian Mutations at Doses That Deplete Ovarian Follicles in Mice
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons like benzo[a]pyrene (BaP) are ubiquitous environmental contaminants formed during incomplete combustion of organic materials. Our prior work showed that transplacental exposure to BaP depletes ovarian follicles and increases prevalence of epithelial ovarian tumors later in life. We used the MutaMouse transgenic rodent model to address the hypothesis that ovarian mutations play a role in tumorigenesis caused by prenatal exposure to BaP. Pregnant MutaMouse females were treated with 0, 10, 20, or 40 mg/(kg day) BaP orally on gestational days 7-16, covering critical windows of ovarian development. Female offspring were euthanized at 10 weeks of age; some ovaries with oviducts were processed for follicle counting; other ovaries/oviducts and bone marrow were processed for determination of lacZ mutant frequency (MF). Mutant plaques were pooled within dose groups and sequenced to determine the mutation spectrum. BaP exposure caused highly significant dose-related decreases in ovarian follicles and increases in ovarian/oviductal and bone marrow mutant frequencies at all doses. Absence of follicles, cell packets, and epithelial tubular structures were observed with 20 and 40 mg/(kg day) BaP. Depletion of ovarian germ cells was inversely associated with ovarian MF. BaP induced primarily G > T and G > C transversions and deletions in ovaries/oviducts and bone marrow cells and produced a mutation signature highly consistent with that of tobacco smoking in human cancers. Overall, our results show that prenatal BaP exposure significantly depletes ovarian germ cells, causes histopathological abnormalities, and increases the burden of ovarian/oviductal mutations, which may be involved in pathogenesis of epithelial ovarian tumors. Environ. Mol. Mutagen. 60:410-420, 2019. © 2018 Her Majesty the Queen in Right of Canada.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".