Literature DB >> 14670693

The automated bioaerosol exposure system: preclinical platform development and a respiratory dosimetry application with nonhuman primates.

Justin M Hartings1, Chad J Roy.   

Abstract

INTRODUCTION: Well-characterized inhalation exposure systems are critical for preclinical testing and pathogenesis studies. The automated bioaerosol exposure system (ABES) provides a microprocessor-driven inhalation platform that provides exquisite data acquisition and control over all aspects of inhalation exposures. Because this represents a new technology, the development and characteristics of the ABES are thoroughly discussed. In addition to control over homeostatic and aerosol conditions, the ABES incorporates a dosimetry function based on respiratory performance of the test animal during inhalation.
METHODS: To test the system, rhesus macaques were initially sham-exposed using the ABES in a head-only inhalation configuration. The ABES was subsequently used under biosafety level (BSL)-III conditions in a vaccine efficacy challenge using aerosolized staphylococcal enterotoxin B (SEB) toxin, again using the real-time dosimetry function of the system.
RESULTS: Sham exposure results indicated significant departures from corresponding whole-body plethysmography (WBP) respiratory function estimates taken before the inhalation procedure. The results of the SEB exposure demonstrated the utility of using the ABES to generate consistently accurate and precise inhalation dose. DISCUSSION: Taken together, the results of the sham and toxin challenge experiments demonstrate that the dosimetry function of the ABES improves the precision and accuracy of inhaled dose delivery and calculation as compared to predictive WBP conducted before the exposure. The ABES represents a highly adaptable platform for the design of inhalation systems to suit the requirements of a variety of animal models.

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Year:  2004        PMID: 14670693     DOI: 10.1016/j.vascn.2003.07.001

Source DB:  PubMed          Journal:  J Pharmacol Toxicol Methods        ISSN: 1056-8719            Impact factor:   1.950


  71 in total

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