Investigation of the Role of Lipoxygenase in Bioactivation of 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in Human Lung
Bibliographic record
Abstract
4-Methylnitrosamino-1-(3-pyridyl)-1-butanone (NNK) is a potent tobacco-specific carcinogen believed to play a role in human lung cancer. Bioactivation of NNK involves alpha-carbon hydroxylation that could be catalyzed by cytochrome P450, hemoglobin, and lipoxygenases (LOX). In the present study, the role of LOX in NNK bioactivation was investigated. Formation of keto acid, the endpoint metabolite of alpha-methylene NNK hydroxylation, was observed in human lung cytosols incubated with 4.2 microM [5-(3)H]NNK (N = 6). Following concanavalin A affinity chromatography to enrich human lung lipoxygenase (HLLO), the fraction containing cytosolic components less LOX (fraction 1) retained the ability to bioactivate NNK. Although enriched HLLO exhibited the characteristic dioxygenase and hydroperoxidase activities, it did not bioactivate NNK. The LOX inhibitor nordihydroguaiaretic acid inhibited dioxygenase activity of HLLO by 83 +/- 19% (P < 0.05, N = 6), but did not inhibit keto acid formation in the crude cytosols (N = 6, P > 0.05). Failure of soybean LOX to catalyze NNK bioactivation supported the results observed in human lung cytosols, and failure of chemically generated alkylperoxyl radicals to bioactivate NNK further suggested that the dioxygenase activity of LOX is not likely to be involved in NNK bioactivation. Horseradish peroxidase and myeloperoxidase catalyzed NNK bioactivation were also nondetectable. Our results demonstrate that, although human lung cytosols can bioactivate NNK to form keto acid, LOX is not involved. We have attributed the ability of crude human lung cytosols to bioactivate NNK to hemoglobin. The inhibitory effect of 1-aminobenzotriazole and arachidonic acid on keto acid formation in the crude cytosols and in fraction 1, respectively (P < 0.05, N = 6), is consistent with hemoglobin-catalyzed NNK bioactivation.
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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 | 0.000 |
| 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".