Faculty Bibliography

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.

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.

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.

The use of E-cigarettes, often considered a safer alternative to traditional smoking, has been associated with high rates of cellular toxicity, genetic alterations, and inflammation. Neuroinflammatory impacts of cigarette smoking during pregnancy have been associated with increased risks of adverse childhood health outcomes; however, it is still relatively unknown if the same propensity is conferred on offspring by maternal vaping during gestation. Results from our previous mouse inhalation studies suggest such a connection. In this earlier study, pregnant C57BL/6 mice were exposed daily to inhaled E-cig aerosols (i.e., propylene glycol and vegetable glycerin, [PG/VG]), with or without nicotine (16 mg/mL) by whole-body inhalation throughout gestation (3 h/d; 5 d/week; total ~3-week) and continuing postnatally from post-natal day (PND) 4-21. As neuroinflammation is involved in the dysregulation of glucose homeostasis and weight gain, this study aimed to explore genes associated with these pathways in 1-mo.-old offspring (equivalent in humans to 12-18 years of age). Results in the offspring demonstrated a significant increase in glucose metabolism protein levels in both treatment groups compared to filtered air controls. Gene expression analysis in the hypothalamus of 1 mo. old offspring exposed perinatally to E-cig aerosols, with and without nicotine, revealed significantly increased gene expression changes in multiple genes associated with neuroinflammation. In a second proof-of-principal parallel study employing the same experimental design, we shifted our focus to the hippocampus of the postpartum mothers. We targeted the mRNA levels of several neurotrophic factors (NTFs) indicative of neuroinflammation. While there were suggestive changes in mRNA expression in this study, levels failed to reach statistical significance. These studies highlight the need for ongoing research on E-cig-induced alterations in neuroinflammatory pathways.