Characterization of a novel oronasal-restricted nicotine vaping self-administration model in mice
Abstract
Nicotine use remains one of the leading causes of preventable deaths in the United States and, while the prevalence of combustible cigarette use has declined over the past few years, the popularity of electronic nicotine delivery systems continues to rise. Vaping is not without risks, and its long-term effects, particularly in vulnerable populations, remain largely unknown. This study introduces a novel, oronasal-restricted, nicotine vapor self-administration mouse model to investigate the impact of nicotine concentration, genotype, sex, and age on self-administration and behavioral response to nicotine. Our studies show that male and female young adult mice respond to nicotine, demonstrating notable sex-related differences in intake, locomotor sensitization, and somatic withdrawal signs. In addition, we characterized intake in adolescent mice, showing sex differences as well. Finally, we showed genotype-related differences when using β2 knock-out mice, emphasizing the role of the β2 nAChR in nicotine reward and nicotine intake. This new model offers a more targeted approach to studying the potential risks of nicotine vaping in a more relevant and face-valid model compared to traditional whole-body nicotine vapor exposure in rodents.
Read the paper
Related studies
- Tobacco and COPD: presenting the World Health Organization (WHO) Tobacco Knowledge Summary
- Comparative effects of e-cigarette smoking on periodontal status, salivary pH, and cotinine levels
- Association between exposure to environmental pollutants and increased oral health risks, a comprehensive review
- Influence of gestational window on offspring vascular health in rodents with in utero exposure to electronic cigarettes
- Natural products as kinase inhibitors in lung cancer: molecular mechanisms, therapeutic potential, and clinical trials
- Nicotine in electronic cigarettes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.