Cigarette Smoke Exposure Triggers the Autophagic Cascade via Activation of the AMPK Pathway in Mice1
Bibliographic record
Abstract
We previously demonstrated that cigarette smoke (CS) exposure decreases primordial follicle counts and induces autophagy in ovarian granulosa cells in preference to apoptosis. Therefore, the objective of this study was to investigate molecular targets underlying smoke-induced activation of the reparative autophagy pathway in the ovary. Briefly, ovarian homogenates were prepared from adult female mice exposed to mainstream CS twice daily for 8 wk, using a whole-body exposure system. A gene array revealed that CS exposure induced a greater than 2-fold significant increase in the expression of proautophagic genes Cdkn1b, Map1lc3a, Bad, and Sqstm1/p62. A significant increase in Prkaa2, Pik3c3, and Maplc31b expression, as well as a significant decrease in Akt1 and Mtor expression, was detected by quantitative PCR. The 5'-AMP-activated protein kinase catalytic subunit (AMPK) alpha1 + alpha2 and ATG7 protein expression was significantly increased, whereas AKT1, mTOR, CDKN1B/p27, and CXCR4 proteins were significantly decreased in CS exposed versus control ovaries. Up-regulation of AMPK alpha1 + alpha2, a known initiator of autophagic signaling, and ATG7 further suggests activation of the autophagy cascade. Two prosurvival factors, AKT and mTOR, were decreased in expression, an outcome that favors induction of the autophagy pathway, whereas decreased levels of CDKN1B is suggestive of cell cycle dysregulation. In summary, our data suggest that CS exposure induces ovarian follicle loss through induction of the autophagic cascade via the AMPK pathway together with inhibition of antiautophagic markers AKT and mTOR. We further postulate that toxicant-induced dysregulation of reparative autophagy is a novel pathway central to impaired follicle development and subfertility.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".