ArticleToxics2023
Characterization of an Electronic Nicotine Delivery System (ENDS) Aerosol Generation Platform to Determine Exposure Risks.
Article in Toxics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- The impact of vaping behavior on functional changes within the subgingival microbiome.Scientific reports · 2025Article
- Effects of combustible cigarettes and electronic nicotine delivery systems on the regenerative properties of mesenchymal stem cells derived from periodontal ligament (PDL-MSCs).Histology and histopathology · 2025Article
- Multi-Omics Assessment of Puff Volume-Mediated Salivary Biomarkers of Metal Exposure and Oxidative Injury Associated with Electronic Nicotine Delivery Systems.Environmental health perspectives · 2025Article
- The role of puff volume in vaping emissions, inhalation risks, and metabolic perturbations: a pilot study.Scientific reports · 2024Article
- Electronic Cigarette Harms: Aggregate Evidence Shows Damage to Biological Systems.International journal of environmental research and public health · 2023Review
- Toxicological Assessment of Particulate and Metal Hazards Associated with Vaping Frequency and Device Age.Toxics · 2023Article
- Puffing topography: a tool to evaluate vaping behavior and exposure risks.Inhalation toxicologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Evaluating vaping parameters that influence electronic nicotine delivery system (ENDS) emission profiles and potentially hazardous exposure levels is essential to protecting human health. We developed an automated multi-channel ENDS aerosol generation system (EAGS) for characterizing size-resolved particle emissions across pod- and mod-type devices using real-time monitoring instruments, an exposure chamber, and vaping parameters including different ventilation rates, device type and age, e-liquid formulation, and atomizer setup. Results show the ENDS device type, e-liquid flavoring, and nicotine content can affect particle emissions. In general, pod-type devices have unimodal particle size distributions and higher number emissions, while mod-type devices have bimodal size distributions and higher mass emissions. For pod-type devices, later puff fractions emit lower aerosols, which is potentially associated with the change of coil resistance and power during ageing. For a mod-type device, an atomizer with a lower resistance coil and higher power generates larger particle emissions than an atomizer with a greater resistance coil and lower power. The unventilated scenario produces higher particle emission factors, except for particle mass emission from pod-type devices. The data provided herein indicate the EAGS can produce realistic and reproducible puff profiles of pod- and mod-type ENDS devices and therefore is a suitable platform for characterizing ENDS-associated exposure risks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.