The induction of cyclooxygenase-1 by a tobacco carcinogen in U937 human macrophages is correlated to the activation of NF-κB
Why this work is in the frame
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Bibliographic record
Abstract
The nicotine-derived 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), present in tobacco smoke, is most likely involved in lung carcinogenesis in smokers. We demonstrated previously that non-steroidal anti-inflammatory drugs (NSAIDs) inhibit NNK-induced lung tumorigenesis, although the mechanism(s) is unknown. The present study demonstrates that, in U937 human macrophages, cyclooxygenase (COX)-1 and -2 are involved in the bioactivation of NNK to electrophilic mutagenic intermediates. We observed that acetylsalicylic acid and NS-398 decrease COX-dependent NNK activation in U937 cells by 66 and 37%, respectively. NSAIDs also decrease prostaglandin E(2) (PGE(2)) synthesis, which is induced in a dose-dependent manner, reaching a 7-fold increase, in NNK-treated human U937 cells. We observed that NNK induces COX-1 expression and activates the nuclear factor-kappaB (NF-kappaB), in U937 cells. N:-acetyl-L-cysteine and pyrrolidinedithiocarbamate, two inhibitors of reactive oxygen species (ROS), inhibit NNK-induced PGE2 synthesis by 41 and 44%, respectively. These data suggest that ROS, generated during pulmonary metabolism of NNK could act as signal transduction messengers and activate NF-kappaB, which will subsequently induce COX-1 activity and increase PGE(2) synthesis. These results reveal a novel aspect of tobacco carcinogenesis, and give us insight into the mechanisms of chemoprevention by NSAIDs. Accordingly, inhibition of NF-kappaB activation, leading to the inhibition of COX, offers a new approach in lung cancer prevention.
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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 | 0.001 |
| 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