The Genotoxicity of Mainstream and Sidestream Marijuana and Tobacco Smoke Condensates
Bibliographic record
Abstract
While the prevalence of tobacco use has decreased in Canada over the past decade, that of marijuana use has increased, particularly among youth. However, the risks of adverse health effects from marijuana smoke exposure, specifically as compared to tobacco, are currently not well understood. The objectives of this study were to evaluate the relative ability of matched marijuana and tobacco condensates to induce (geno)toxic responses in three in vitro test systems. This study provides comparative data for matched sidestream and mainstream condensates, as well as condensates prepared under both a standard and an extreme smoking regime designed to mimic marijuana smoking habits. The results indicate that tobacco and marijuana smoke differ substantially in terms of their cytotoxicity, Salmonella mutagenicity, and ability to induce chromosomal damage (i.e., micronucleus formation). Specifically, the marijuana condensates were all found to be more cytotoxic and more mutagenic in the presence of S9 than the matched tobacco condensates. In contrast, the tobacco condensates appeared to induce cytogenetic damage in a concentration-dependent manner, whereas the matched marijuana condensates did not. In addition, when corrected for total particulate matter yield, little difference was observed in the mutagenic activity of samples smoked under the extreme vs the standard regime for both tobacco and marijuana condensates.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".