Faculty Bibliography

Electronic nicotine delivery systems (ENDS), commonly known as e-cigarettes, are battery-operated devices that produce aerosols by vaporizing e-liquids, which typically contain propylene glycol and/or vegetable glycerin, nicotine, and flavorings. Since their launch in the U.S. in 2007, ENDS have evolved significantly to meet consumer demands, prompting federal regulation in 2016 under the Family Smoking Prevention and Tobacco Control Act. The first ENDS resembled conventional tobacco cigarettes and were initially marketed as smoking cessation tools. While their smoking cessation efficacy under advantageous conditions has been supported by randomized clinical trials, observational cohort studies have raised doubt about their utility for smoking cessation under more typical real-world use conditions. In 2018, the U.S. Surgeon General declared youth vaping a national epidemic as prevalence of current ENDS use rose to 27.5% among high school. The youth vaping trend alongside injury reports and deaths related to e-cigarette or vaping product use-associated lung injury (EVALI) raised public health alarms in 2019. Although youth vaping has since declined, over 1.6 million high school students and 410, 000 middle school students reported ENDS usage in 2024. Thus, the ongoing challenges surrounding vaping including adolescent usage and smoking cessation efficacy continue to attract public health concern and debate. Within this section of the Special Issue "Science Education and Research on Vaping and Interventions for Community Engagement", an overview of the history of the vaping epidemic, current formats and ENDS generations, usage statistics across various demographics along with market trends and regulatory guidelines will be discussed.

The objective of this study is to investigate the potential mutagenic effects of the exposure of mice to aerosols produced from the component liquids of an electronic nicotine delivery system (ENDS). The use of electronic cigarettes (e-cigs) and ENDSs has increased tremendously over the past two decades. From what we know to date, ENDSs contain much lower levels of known carcinogens than tobacco smoke. While conventional tobacco smoke is a well-established mutagen, little is known about the mutagenicity of ENDS aerosols. Here, we report the mutagenic effects of a 3-month whole body exposure of C57 lacI mice (BigBlue^TM) to filtered air (AIR) or ENDS aerosols in several tissues. Aerosols were generated from a 50/50 vegetable glycerin (VG)/propylene glycol (PG) mixture with and without nicotine. The results revealed that in the lung, bladder urothelial tissue, and tongue, mutagenesis was significantly greater in the VG/PG/nicotine group than in the AIR group. In all organs except the bladder, mutagenesis in the VG/PG only group was similar to those exposed to AIR. In the bladder, mutagenesis in the VG/PG group was elevated compared to that in the AIR group. In the liver, mutagenesis was modestly elevated in the VG/PG/nicotine group, but the elevation failed to reach statistical significance. Overall, there were no consistent differences in mutagenesis between the sexes. The results of this study suggest that exposure to e-cig aerosols containing nicotine represents a risk factor for carcinogenesis in several organ systems, and exposure to VG/PG alone may be a risk factor for bladder cancer.

Those undergoing pregnancy are often excluded from clinical drug trials due to the risk that participation would pose. However, they often require pharmaceuticals to manage health conditions that, if gone untreated, could harm themselves or the fetus. This can mean that such individuals take one or more pharmaceuticals during pregnancy, many of which have unknown reproductive effects. Machine learning models have been used to successfully predict a number of reproductive toxicological outcomes for pharmaceuticals, including transplacental transfer, US Food and Drug Administration safety rating, and drug interactions. Models use quantitative chemical and structural features of active compounds to make predictions concerning the outcome of interest using computational algorithms. Results from these models can be a potential source of valuable information for pregnant people and their medical providers when making decisions regarding therapeutic drug use. This review summarizes current machine learning applications to make predictions about risk and toxicity of medication use during pregnancy. Our review of the recent literature revealed that machine learning quantitative structure-activity relationship models can be used successfully to predict the transplacental transfer and the US Food and Drug Administration pregnancy safety category of pharmaceuticals; such models have also been employed to predict drug interactions, though not specifically during pregnancy. This latter topic is a potential area for future research. In this review, no single algorithm or descriptor-calculation software emerged as the most widely used, and their performances depend on a variety of factors, including outcome of interest and combination of such algorithms and software.

OBJECTIVES/UNASSIGNED:Marginalized communities are exposed to higher levels of traffic-related air pollution (TRAP) than the general population. TRAP exposure is linked to pulmonary toxicity, neurotoxicity, and cardiovascular toxicity often through mechanisms of inflammation and oxidative stress. Early life exposure to TRAP is also implicated in higher rates of asthma in these same communities. There is a critical need for additional epidemiological, in vivo, and in vitro studies to define the health risks of TRAP exposure affecting the most vulnerable groups to set strict, protective air pollution standards in these communities. MATERIALS AND METHODS/UNASSIGNED:A literature review was conducted to summarize recent findings (2010-2024) concerning TRAP exposure and toxic mechanisms that are relevant to the most affected underserved communities. CONCLUSIONS/UNASSIGNED:Guided by the perspectives of NYC community scientists, this contemporary review of toxicological and epidemiological studies considers how the exposome could lead to disproportionate exposures and health effects in underserved populations.