New Attempt to Reduce the Harm of Smoking: Reducing the Nitrosamines Level in Tobacco Smoke by Microwave Irradiation
Bibliographic record
Abstract
Abstract In order to protect the environment and public health, microwave irradiation was investigated as a means of reducing the nitrosamines level of tobacco smoke under mild conditions where the microwave energy was 1 kW and the irradiation time was shorter than 2 min. The microwave‐induced elimination of nitrosamines such as N‐nitrosopyrrolidine (NPYR) and N‐nitrosodiphenylamine (NDPA) was investigated and the impact of the presence of water and salt in the medium on the reduction was assessed in detail. The existence of water in the medium was crucial for the microwave‐induced reduction of NDPA, because the rapid movement of water molecules under the influence of microwaves strongly affects the adjacent nitrosamines leading to their decomposition. This was the first time that microwaves have been used to directly irradiate cigarettes sealed in their packaging, and the nitrosamines content of tobacco and smoke of these irradiated cigarettes were analyzed with care. Irradiation for 90 s with microwave energy of 1kW was seen to reduce 25 to 30% of the nitrosamines in tobacco and 50 to 60% of the levels present in the mainstream smoke of the cigarette. Moreover, lower mutagenic activity and higher CHO cell livability were found for the irradiated cigarettes in comparison with the control according to the results of in vitro tests.
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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".