Influence of Tobacco Variety and Curing on Free Radical Production in Cigarette Smoke
Bibliographic record
Abstract
INTRODUCTION: Cigarette smoke contains highly reactive free radicals thought to play an important role in tobacco smoke-induced harm. Previously, large variations in free radical and toxicant output have been observed in commercial cigarettes. These variations are likely because of cigarette design features (paper, filter, and additives), tobacco variety (burley, bright, oriental, etc.), and tobacco curing methods (air, sun, flue, and fire). Previous reports show that tobacco varieties and curing methods influence the production of tobacco smoke constituents like the tobacco-specific carcinogen nicotine-derived nitrosamine ketone (NNK). AIMS AND METHODS: We evaluated free radical, nicotine, and NNK production in cigarette smoke from cigarettes produced with 15 different types of tobacco. Gas-phase free radicals were captured by spin trapping with N-tert-butyl-α-phenylnitrone and particulate-phase radicals were captured on a Cambridge Filter pad (CFP). Both types of radicals were analyzed using electron paramagnetic resonance spectroscopy. Nicotine and NNK were extracted from the CFP and analyzed by gas chromatography flame ionization detection and liquid chromatography-mass spectrometry, respectively. RESULTS: Gas-phase radicals varied nearly 8-fold among tobacco types with Saint James Perique tobacco producing the highest levels (42 ± 7 nmol/g) and Canadian Virginia tobacco-producing the lowest levels (5 ± 2 nmol/g). Nicotine and NNK levels in smoke varied 14-fold and 192-fold, respectively, by type. Gas-phase free radicals were highly correlated with NNK levels (r = 0.92, p < .0001) and appeared to be most impacted by tobacco curing method. CONCLUSIONS: Altogether, these data suggest that tobacco types used in cigarette production may serve as a target for regulation to reduce harm from cigarette smoking. IMPLICATIONS: Variations in cigarette free radical and NNK levels vary based on the tobacco variety and curing method. Reducing the ratio of high-producing free radical and NNK tobacco types offer a potential tool for regulators and producers looking to reduce toxicant output from cigarettes.
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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".