Exploring the Impact of Inflammation on Gas Exchange Efficiency in Cannabis-smoking Individuals Using 129XeMRI
Bibliographic record
Abstract
Abstract RATIONALE: As recreational use of cannabis increases globally, the structure-function changes underlying the increased respiratory symptom burden1 must be investigated. Current literature is dominated by case reports of severe lung injury in subjects with significant exposure to both cannabis and tobacco, which do not capture early changes in young smokers nor cannabis-specific effects.1 Imaging such as computed tomography (CT) and 129Xe magnetic resonance imaging (129XeMRI) provide quantitative structural and functional measurements respectively. We hypothesize that the effects of cannabis smoking in the lungs are measurable as functional changes in 129XeMRI. METHODS: Current cannabis smoking participants with <5 pack-years of cigarette smoking, and age-matched never-smoking participants completed pulmonary function tests (PFTs), COPD Assessment Test (CAT), St. George's Respiratory Questionnaire (SGRQ), chest CT, 129XeMRI, and bronchoscopic bronchial brush for RNA sequencing. CT was quantitatively analyzed (VIDA Insights) for lung density measurements, 129XeMRI was performed per guidelines2 to measure ventilation defect percent (VDP), ratios of membrane (Mem)/Gas, red blood cell (RBC)/Mem, RBC/Gas and apparent diffusion coefficient (ADC). Total RNA were sequenced (Illumina NovaSeq6000), quality controlled (FastQC), aligned to the human genome (Salmon V1, GENCODE GRCh37v.45) and normalized to Log2 transcripts-per-million. Mean gene signature scores were quantified and compared with two-sided independent t-tests or correlated with Spearman's rank-order coefficient. RESULTS: We evaluated 16 cannabis-smoking (31±10yrs, 10 female) and 6 never-smoking participants (29±7yrs, 2 female). Median joint-years was 13.4 (range 0.25-75) and years smoking was 6 (range 2-45). The cannabis-smoking group was symptomatic, with greater SGRQ (14.4±9.2 vs 3.6±6.3, p=0.012) and CAT scores (10.0±5.6 vs 1.7±1.5, p=0.023). PFT, CT lung density, and 129XeMRI measurements were not different between groups. Type 1 inflammation correlated negatively with RBC/Gas (ρ=-0.430, p=0.046) and RBC/Mem (ρ=-0.509, p=0.016) while Type 2 inflammation correlated positively with Mem/Gas (ρ=0.481, p=0.024) (Figure 1). CAT and SGRQ activity scores correlated negatively with RBC/Mem (ρ=-0.568, p=0.011; ρ=-0.457, p=0.032). CONCLUSIONS: These findings suggest that Type 1 and 2 inflammation pathways, potentially activated by inhalation of cannabis smoke, could impair gas-exchange function as measured by 129XeMRI in synergistic ways. Further investigation of the relationships between cannabis smoking, inflammation pathways, and compartmental gas-exchange deficits may lead to better understanding of the pathophysiology and treatment options for cannabis-related lung injury. REFERENCES: 1Ribeiro&Ind.npjPrimCareRespMed(2016).2Niedbalski.MRM(2021).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".