Electronic nicotine delivery system design and aerosol toxicants: A systematic review
Bibliographic record
Abstract
BACKGROUND: Electronic nicotine delivery systems (ENDS; e-cigarettes), consisting of a battery, heating element and e-liquid, have evolved significantly with wide variation in design, components, operating powers, and chemical constituents. Generated aerosols have been reported to contain potentially toxic substances. We conducted a systematic review to assess what is known about the presence of toxicants in ENDS aerosols in order to inform how system design could mitigate risk. METHODS: Articles reporting on or evaluating design characteristics of ENDS and aerosol constituents were included and summarized. RESULTS: The search identified 2,305 articles, of which 92 were included after full-text review. Findings were grouped into 6 major categories of potentially harmful chemicals: carbonyls, volatile organic chemicals, trace elements, reactive oxygen species and free radicals, polycyclic aromatic hydrocarbons, and tobacco-specific nitrosamines. In general, higher concentrations of aerosol toxicants are associated with increased power or voltage. Aerosol toxicants are also associated with e-liquid flavoring agents existing as primary ingredients or as products of thermal degradation. CONCLUSIONS: Improved ENDS design can reduce toxicant levels. Additional research is needed to develop a framework for optimizing system characteristics to minimize exposure, especially with respect to heating power and e-liquids. Both manufacturers and regulatory agencies have roles in reducing toxicants and potential health risks from ENDS.
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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) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".