Cigarette smoke components inhibited intercellular communication and differentiation in human pancreatic ductal epithelial cells
Bibliographic record
Abstract
Smoking is a well-documented risk factor for the development of pancreatic adenocarcinoma. Although the most abundant polycyclic aromatic hydrocarbons (PAHs) in cigarette smoke are methylated anthracenes and phenanthrenes, the epigenetic toxicity of these compounds has not been extensively studied. We previously showed that methylanthracenes, which possess a bay-like structure, affect epigenetic events such as an induced release of arachidonic acid, inhibition of gap junctional intercellular communication (GJIC) and induction of mitogen-activated protein kinases in a pluripotent rat liver epithelial stem cell line. Anthracenes with no bay-like structures were inactive. These biological effects are all molecular events associated with the promotional phase of cancer. A human immortalized, nontumorigenic pancreatic ductal epithelial cell line, H6c7, was examined to study the epigenetic toxicity of PAHs related to pancreatic cancer by using scrape-loading dye transfer, immunostaining, RT-PCR and telomerase assay methods. H6c7 cells were GJIC-incompetent and exhibited high telomerase activity when grown in growth factor and hormone-supplemented medium. In the presence of the cAMP elevating drugs (forskolin and IBMX) the cells became GJIC competent and expressed connexins. Telomerase activity was also decreased by cAMP elevating drug treatment. After induction of cAMP, 1-methylanthracene with bay-like structures inhibited GJIC, whereas the 2-methylanthracene lacking a bay-like structure had no effect on GJIC. Telomerase activity remained high in 1-methylanthracene treatment but not with 2-methylanthracene. These results indicate that a prominent component of cigarette smoke, namely methylanthracenes with distinct structural configurations, could be a potential etiological agent contributing to the epigenetic events of pancreatic cancer.
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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".