Cytokine production by alveolar macrophages is down regulated by the -methylhydroxylation pathway of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)
Bibliographic record
Abstract
NNK, a nicotine-derived nitrosamine, is a potent lung carcinogen that generates electrophilic intermediates capable of damaging DNA. The effects of NNK on the immune response, which may facilitate lung carcinogenesis, are poorly understood. Alveolar macrophages (AM), a key cell in the maintenance of lung homeostasis, metabolize NNK via two major metabolic activation pathways: alpha-methylhydroxylation and alpha-methylenehydroxylation. We have shown previously that NNK inhibits the production of interleukin-12 (IL-12) and tumor necrosis factor (TNF), but stimulates the production of IL-10 and prostaglandin E(2) (PGE(2)) by AM. In the present study, we investigated the contribution of each activation pathway in the modulation of AM function. We used two precursors, 4-[(acetoxymethyl)-nitrosamino]-1-(3-pyridyl)-1-butanone (NNKOAc) and N-nitro(acetoxymethyl)methylamine (NDMAOAc), which generate the reactive electrophilic intermediates [4-(3-pyridyl)-4-oxo-butanediazohydroxide and methanediazohydroxide, respectively] in high yield and exclusively. Rat AM cell line, NR8383, was stimulated and treated with different concentrations of NNKOAc or NDMAOAc (12, 25 and 50 microM). Mediator release was measured in cell-free supernatants. NNKOAc significantly inhibited the production of IL-10, IL-12, TNF and nitric oxide but increased the release of PGE(2) and cyclooxygenase-2 expression suggesting that the alpha-methylhydroxylation pathway might be responsible for NNK modulation of AM cytokine release. In contrast, NDMAOAc did not modulate AM mediator production. However, none of these precursors, alone or in combination, could explain the stimulation of AM IL-10 production by NNK. Our results suggest that the alpha-methylhydroxylation of NNK leading to DNA pyridyloxobutylation also modulates cytokine production in NNK-treated AM.
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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) | 0.001 | 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".