Clinical, physiological, imaging and molecular responses to cannabis smoking: the Canadian Users of Cannabis Smoke (CANUCK) study
Bibliographic record
Abstract
Background The growing popularity of cannabis smoking in an era of legalisation has prompted concerns about respiratory health. Objective To investigate clinical and airway epithelial transcriptomic features associated with cannabis smoking. Methods This cross-sectional study analysed data from 139 cannabis-smoking participants categorised by joint-year exposure (low: ≤5; moderate: >5–20; high: >20 joint-years) and 57 never-smokers. We evaluated respiratory symptom questionnaire scores, lung function measurements, chest computed tomography and hyperpolarised 129 Xenon pulmonary magnetic resonance imaging measurements across groups. We compared the expression of immune response signatures and mucin genes in airway epithelial brushings collected from bronchoscopy. Using air–liquid interface cell cultures, we quantified epithelial mucin 5AC (MUC5AC) protein and correlated its expression with clinical outcomes. Results Among cannabis-smoking participants (48% male, median age of 27 years), 84% reported current or former cigarette smoking or vaping. Cannabis-smoking groups reported worse respiratory symptoms than never-smokers. High joint-year cannabis-smoking participants showed lower pre-bronchodilator forced expiratory volume in 1 s to forced vital capacity ratio, lower forced expiratory flow at 25–75% of the forced vital capacity, more radiographic emphysema and more ventilation abnormalities than never-smokers. Airway epithelial brushings from cannabis-smoking participants demonstrated an increased type 2 immune response, decreased type 17 immune response and higher MUC5AC gene expression than non-cannabis-smoking participants. Epithelial MUC5AC protein expression in cell cultures correlated with worse clinical outcomes and imaging abnormalities. Conclusions Cannabis smoking, particularly at high exposures, is associated with worse respiratory symptoms, lower lung function, functional imaging abnormalities and dysregulated immune responses in the airway epithelium. These observations suggest respiratory harm associated with cannabis smoking and underscore the concerns for future respiratory morbidities related to persistent cannabis use.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".