<em>In vitro</em> Cannabis Exposures of Lung Epithelial Cells at the Air-Liquid Interface
Bibliographic record
Abstract
Cannabis is used by an estimated 192 million people around the world. Most people use cannabis through the inhalation of cannabis smoke, which contains combustion by-products that can negatively affect lung health. Knowledge of these risks has led to a growing interest in cannabis vaporizers, which heat the dry cannabis flower without burning. Vaporizing cannabis still releases cannabinoids for inhalation but heats the plant material at a lower temperature. There is currently no standardized in vitro model for assessing the effects of dry cannabis vapor. Therefore, we established a model for the exposure of lung cell cultures at an air-liquid interface (ALI), whereby cells are apically exposed to vaporized cannabis, thereby more accurately simulating lung epithelial cell physiology. This protocol ensures consistent and reproducible delivery of cannabis vapor to the cell surface, providing a reliable platform for investigating the cellular and molecular impacts of vaporized cannabis. This work is the first to standardize an in vitro cannabis vapor delivery method, which can serve as a benchmark for future preclinical cannabis research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".