Cigarette smoke causes follicle loss in mice ovaries at concentrations representative of human exposure
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
BACKGROUND: Cigarette smoke is a documented reproductive toxicant associated with infertility and ovarian failure. However, the underlying mechanism(s) regulating the toxic effects of cigarette smoke are unknown. Therefore, we tested the hypothesis that mainstream cigarette smoke and a cigarette smoke constituent, benzo[a]pyrene (BaP), induce apoptosis in ovarian follicles. METHODS: Mice were exposed to mainstream cigarette smoke and the ovaries were analysed for follicle loss and markers of apoptosis (TUNEL, Caspase 3, Caspase 8, Bax, Bcl-2, Fas and FasL). Isolated ovaries from female pups were cultured in media containing increasing concentrations of BaP (1-10 000 ng ml(-1)), and markers of apoptosis were quantified. RESULTS: Cigarette smoke exposure induced a significant reduction in the number of primordial follicles, but not growing or antral follicles compared with controls. Mainstream cigarette smoke exposure had no effect on any marker of apoptosis measured. Exposure of ovaries to BaP in vitro resulted in an increase in the pro-survival marker Bcl-2, but no change in apoptosis. CONCLUSIONS: Our data suggest that cigarette smoke-induced follicle loss is not mediated via BaP-induced apoptosis.
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) | 0.000 | 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 it