The emerging concern about chemicals in electronic cigarettes, even those without nicotine, demands the development of advanced criteria for their exposure and risk assessment. This study aims to highlight the sensitivity of lung nuclear receptors (NRs) to electronic cigarette e-liquids, independent of nicotine presence, and the influence of the sex variable on these effects. Adult male and female C57BL/6J mice were exposed to electronic cigarettes with 0%, 3%, and 6% nicotine daily (70 mL, 3.3 s, 1 puff per min/30 min) for 14 days, using the inExpose full body chamber (SCIREQ). Following exposure, lung tissues were harvested, and RNA extracted. The expression of 84 NRs was determined using the RT2 profiler mRNA array (Qiagen). Results exhibit a high sensitivity to e-liquid exposure irrespective of the presence of nicotine, with differential expression of NRs, including one (females) and twenty-four (males) in 0% nicotine groups compared to non-exposed control mice. However, nicotine-dependent results were also significant with seven NRs (females), fifty-three NRs (males) in 3% and twenty-three NRs (female) twenty-nine NRs (male) in 6% nicotine groups, compared to 0% nicotine mice. Sex-specific changes were significant, but sex-related differences were not observed. The study provides a strong rationale for further investigation.

E-liquids contain combinations of chemicals, with many enhancing the sensory attractiveness of the product. Studies are needed to understand and characterize e-liquid ingredients, particularly flavorings, to inform future research and regulations of these products. We identified common flavor ingredients in a convenience sample of commercial e-liquids using gas chromatography-mass spectrometry. E-liquid flavors were categorized by flavor descriptors provided on the product packaging. A Flavor Ingredient Wheel was developed to link e-liquid flavor ingredients with flavor categories. An analysis of 109 samples identified 48 flavor ingredients. Consistency between the labeled flavor and ingredients used to produce such flavor was found. Our novel Flavor Ingredient Wheel organizes e-liquids by flavor and ingredients, enabling efficient analysis of the link between ingredients and their flavor profiles and allowing for quick assessment of an e-liquid ingredient\'s flavor profile. Investigating ingredient profiles and identifying and classifying commonly used chemicals in e-liquids may assist with future studies and improve the ability to regulate these products.

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BACKGROUND: Part of the appeal of e-cigarettes lies in their available flavors. To achieve attractive flavors, e-liquids contain many different flavoring agents, which allow many flavoring combinations. To advance our knowledge of e-liquid flavors and compositions and to evaluate the effect of legislation, we determined whether there are ingredient combinations that are frequently used together.
METHODS: We used e-cigarette ingredient data from the European Common Entry Gate system (EU-CEG) as available on 31 December 2022.
RESULTS: In e-liquids, we found 214 ingredient pairs with a co-occurrence odds ratio greater than 10. Together, these consisted of 62 unique ingredients. Network analysis revealed that ingredients were grouped together based on their flavor and/or chemical structure. We identified two densely connected regions (clusters) in the network. One consisted of six ingredients with sweet-vanilla-creamy flavors. The second cluster consisted of 13 ingredients. While some of these have fruity flavors, others, such as alkyl carboxylic acids and dimethyl sulfide, are known to have unpleasant flavors. Additional data and literature analyses indicated that alkyl carboxylic acids can contribute to a creamy and sweet-fruity taste, whereas dimethyl sulfide can contribute to a more refined fruity taste.
CONCLUSIONS: These results exemplify that the flavor of e-liquids is not just the sum of its parts. Big data analyses on product data can be used to detect such patterns, but expert knowledge and additional data are needed for further interpretation. Monitoring of e-liquid flavors as well as ingredients will remain important to regulate e-liquid product attractiveness.

The widespread use of flavored e-cigarettes has led to a significant rise in teenage nicotine use. In e-liquids, the flavor carbonyls can form acetals with unknown chemical and toxicological properties. These acetals can cause adverse health effects on both smokers and nonsmokers through thirdhand exposure. This study aims to explore the impacts of these acetals formed in e-cigarettes on indoor partitioning and thirdhand exposure. Specifically, the acetalization reactions of commonly used flavor carbonyls in laboratory-made e-liquids were monitored using proton nuclear magnetic resonance (1H NMR) spectroscopy. EAS-E Suite and polyparameter linear free energy relationships (PP-LFERs) were employed to estimate the partitioning coefficients for species. Further, a chemical two-dimensional partitioning model was applied to visualize the indoor equilibrium partitioning and estimate the distribution of flavor carbonyls and their acetals in the gas phase, aerosol phase, and surface reservoirs. Our results demonstrate that a substantial fraction of carbonyls were converted into acetals in e-liquids and their chemical partitioning was significantly influenced. This study shows that acetalization is a determinant factor in the exposure and toxicology of harmful carbonyl flavorings, with its impact extending to both direct exposure to smokers and involuntary exposure to nonsmokers.

Scientific progress and ethical considerations are increasingly shifting the toxicological focus from in vivo animal models to in vitro studies utilizing physiologically relevant cell cultures. Consequently, we evaluated and validated a three-dimensional (3D) model of the human lung using Calu-3 cells cultured at an air-liquid interface (ALI) for 28 days. Assessment of seven essential genes of differentiation and transepithelial electrical resistance (TEER) measurements, in conjunction with mucin (MUC5AC) staining, validated the model. We observed a time-dependent increase in TEER, genetic markers of mucus-producing cells (muc5ac, muc5b), basal cells (trp63), ciliated cells (foxj1), and tight junctions (tjp1). A decrease in basal cell marker krt5 levels was observed. Subsequently, we utilized this validated ALI-cultured Calu-3 model to investigate the adversity of the aerosols generated from three flavored electronic cigarette (EC) e-liquids: cinnamon, vanilla tobacco, and hazelnut. These aerosols were compared against traditional cigarette smoke (3R4F) to assess their relative toxicity. The aerosols generated from PG/VG vehicle control, hazelnut and cinnamon e-liquids, but not vanilla tobacco, significantly decreased TEER and increased lactate dehydrogenase (LDH) release compared to the incubator and air-only controls. Compared to 3R4F, there were no significant differences in TEER or LDH with the tested flavored EC aerosols other than vanilla tobacco. This starkly contrasted our expectations, given the common perception of e-liquids as a safer alternative to cigarettes. Our study suggests that these results depend on flavor type. Therefore, we strongly advocate for further research, increased user awareness regarding flavors in ECs, and rigorous regulatory scrutiny to protect public health.

Recently, synthetic cannabinoids (SCs) have emerged as new psychoactive substances (NPS) and have been frequently added to e-liquids, leading to their abuse. In order to detect SCs in e-liquids quickly and accurately, a thermal-assisted carbon fiber ionization mass spectrometry technique has been developed. The introduction of a heat source helps to reduce the matrix effects. The results indicate that the ratio of the slope of the matrix curve (e-liquids matrix) and the standard curve (methanol solution) for SCs analysis is close to 1, indicating a minimized matrix effect of this method. Furthermore, this method exhibits good quantitative ability when applied to real samples. It does not require sample pretreatment and is sensitive enough to directly quantify SCs in e-liquids. Our method is characterized by the ability to achieve rapid and direct quantitative analysis with minimized matrix effects. It provides a rapid and simple method for analyzing SCs in e-liquids.

Electronic nicotine delivery systems (ENDS), which are becoming increasingly popular in many parts of the world, have recently become more sophisticated in terms of their more active content and better controlled vaporisation. This review begins by describing how cigarette smoking led to the development of ENDS as a means of combatting nicotine addiction. ENDS are usually categorised as belonging to one of only three main generations, but a fourth has been added in order to differentiate the latest, most powerful, most advanced and innovative that have improved heating efficiency. Descriptions of the principal substances contained in ENDS are followed by considerations concerning the risk of toxicity due to the presence of albeit low concentrations of such a variety of compounds inhaled over a long time, and the increasingly widespread use of ENDS as a means of smoking illicit drugs. We also review the most widely used pharmacotherapeutic approaches to smoking cessation, and recent epidemiological data showing that ENDS can help some people to stop smoking. However, in order to ensure their appropriate regulation, there is a need for higher-quality evidence concerning the health effects and safety of ENDS, and their effectiveness in discouraging tobacco smoking.

Exposure to e-cigarette liquids, whether intentional or accidental, might lead to adverse events. This study aimed to describe the prevalence and characteristics of exposures to e-liquids reported to French Poison Control Centers.
All e-liquids exposure cases reported to French Poison Control Centers from July 1, 2019, to December 31, 2020, were reviewed. Information was collected about the patient\'s characteristics, exposure circumstances, management and outcome.
About 919 cases of exposure to e-liquids were reported. Ages ranged from one month to 89 years, with a mean age of 16.6 ± 18.6 years and a median age of 4 years. The highest number of exposures-50.7%-concerned infants (0-4 years), 3.1% children (5-11 years), 5.9% adolescents (12-17 years), and 40.1% of cases concerned adults. The majority of cases were accidental (95.0%). Intentional exposures (4.9%) were mainly observed in patients older than 12 years of age (P < 0.001). The route of exposure was ingestion in 73.7% of the cases. A total of 455 exposures showed no symptoms or signs related to poisoning. High nicotine concentration in e-liquids was associated with an increase in hospital management (Odds-ratio from 1.77 to 2.60).
Involuntary exposures to e-liquids occurred more often in children under the age of five, mainly by ingestion. Unlike intentional ingestions, unintentional ingestions rarely resulted in severe adverse events. These findings highlight the importance of ongoing surveillance to prevent such exposures and associated injuries, emphasizing the need for effective regulation of these products.

The consumption of electronic cigarettes is a habit with an increasing prevalence, particularly among youths. Knowing the composition of e-liquids used in these devices represents the first step to understand the potential impact of e-smoking in the health of consumers. Herein, a non-target screening methodology was applied to the identification of volatile and semi-volatile compounds in a set of e-liquids from different suppliers, with different flavors, and containing different kinds of additives, such as nicotine or cannabidiol. To this end, samples were characterized by gas chromatography accurate mass spectrometry, using a time-of-flight mass analyzer. Combination of deconvoluted electronic ionization mass spectra with linear retention index values, obtained for two columns with different selectivity, permitted the identification of more than 250 chemicals with different confidence levels. Among them, respiratory pro-inflammatory compounds, acetals of propylene glycol and glycerin with aldehydes, nicotine-related and non-related alkaloids, and psychoactive cannabinoids were confirmed as concerning compounds in e-liquid samples. Concentration ratios between propylene glycol acetals and parent aldehydes varied in the range from 2% (ethyl vanillin) to more than 80% (case of benzaldehyde). The ratios between the concentrations of delta-9-tetrahydrocannabinol and cannabidiol in e-liquids stayed in the range from 0.02% to 0.3%.