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Journal of the Experimental Analysis of BehaviorAnimal Behavior & CognitionPeer-reviewed journal article

The Rodent Electronic Nicotine Delivery System: Apparatus for Voluntary Nose-Only E-Cigarette Aerosol Inhalation

Amy L. OdumiD, Mariah E. Willis‐MooreiD, Kiernan T. CallisteriD, Jeremy M. HaynesiD, Charles C. J. FryeiD, Lucy N. ScribneriD, David N. LegaspiiD, Daniel Santos Da SilvaiD, Aaron L. OlseniD, Tadd TruscottiD, Preston T. Alden, Rick A. BevinsiD, Adam Matthew LeventhaliD, Stephen Tomas LeeiD, Brenna GomeriD, Abby D. BenninghoffiD

PDFDOIPreprintData
Citations
2
FWCI
1.12
Field percentile
top 27%

Abstract

Tobacco use is the leading cause of death globally and in the U.S. After decades of decline, driven by decreases in combusted tobacco use, nicotine product use has increased due to Electronic Nicotine Delivery Systems, also known as e-cigarettes or vapes. Preclinical models of nicotine self-administration can serve as important lodestars in the search for effective intervention and prevention tactics. Current variants of the task have substantial limitations, however. Therefore, we created the Rodent Electronic Nicotine Delivery System, a novel low-cost non-proprietary nose-only preclinical model of nicotine aerosol self-administration. We confirmed that RENDS sequesters nicotine aerosol in the nose port by measuring fine particulate matter (PM < 2.5 microns) generated by e-cigarettes. We also showed that rats robustly self-administer flavored nicotine aerosol, resulting in high blood levels of cotinine (the major nicotine metabolite) and spontaneous somatic withdrawal symptoms. Thus, we provide strong validation of the operation and function of the RENDS, opening the door to an open-source preclinical aerosol model of nicotine self-administration that is relatively low cost. Four existing operant chambers can be retrofitted with the RENDS for less than $325/chamber. All RENDS diagrams and plans for custom designed components are on Open Science Framework (https://osf.io/x2pqf/?view_only=775b55435b8e428f98e6da384ef7889d).

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