A preliminary investigation of tobacco co-use on endocannabinoid activity in people with cannabis use
Bibliographic record
Abstract
Tobacco is commonly co-used with cannabis. This is unfortunate because tobacco co-use exacerbates select clinical consequences associated with cannabis use. Evidence demonstrates that low levels of anandamide, a prominent endocannabinoid, correlate with worse clinical outcomes. Fatty acid amide hydrolase (FAAH) degrades anandamide, and greater FAAH levels may underlie poorer clinical outcomes in people who co-use relative to those who use only cannabis. Therefore, we tested whether tobacco co-use increases FAAH levels beyond those associated with cannabis use alone. Cannabis-using participants (N=13) were parsed into individuals with daily tobacco use (CT, n=5) and no current tobacco use (CAN, n=8). We evaluated group differences in FAAH, quantified using positron emission tomography and [ 11 C]CURB, while controlling for sex and FAAH genotype in the prefrontal cortex, hippocampus, thalamus, sensorimotor striatum, substantia nigra, and cerebellum. A significant group x ROI interaction for [ 11 C]CURB λk 3 [F(5, 45)=3.15, p=0.016] emerged. Bonferroni-corrected post-hoc tests indicated greater FAAH levels in CT compared to CAN in the substantia nigra (p=0.023, d=1.54) and cerebellum (p=0.003, d=1.76), while a trend emerged in the sensorimotor striatum (p=0.054, d=1.33). Preliminary findings suggest that tobacco co-use is associated with elevated FAAH activity relative to cannabis-only use, which may underlie poorer clinical outcomes associated with co-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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".