Detection and Monitoring of Pathogens in Animal and Human Environment by a Handheld Immunosensor and CFD Simulation

Abstract

This research demonstrates technology for detection of pathogens and environmental monitoring using a handheld optofluidic immunosensor and CFD simulation. The current methods such as ELISA and PCR require few hours for identification which means it is unavailable for early-monitoring. The use of a near-real-time, handheld biosensor device in a real animal/human environment is the key to monitoring the spread of dangerous pathogens. A 3-D computational fluid dynamics (CFD) simulation is needed to track the pathogens within an environment.This dissertation has four papers that demonstrate technologies for the detection and monitoring of pathogens and the miniaturization of these detection systems for in field applications with a handheld immunosensor and CFD simulation.In the first paper, an environmental prediction model was developed for optimal ventilation in a mushroom house by using sensible heat balance and 3-D CFD method. It is shown that the models can be used for farmers to predict the environmental conditions over different locations in a mushroom house.In the second paper, a field lab-on-a-chip system was constructed to detect mouse immunoglobulin G and Escherichia coli by using light scattering detection of particle immunoagglutination. Antibody-conjugated particles were able to be stored in a 4°C refrigerator for at least 4 weeks and to be lyophilized as a powder form for the storage in room temperature.In the third paper, rapid monitoring of the spreads of porcine reproductive and respiratory syndrome virus (PRRSV) was attempted using samples collected from nasal swabs of pigs and air samplers within an experimental swine building. An optofluidic device containing liquid-core waveguides was used to detect. It is shown that the developed optofluidic device and 3-D CFD model can serve as a good model for monitoring the spread of airborne viruses within animal and human environments.In the fourth paper, a handheld optofluidic immunosensor was developed for rapid detection of H1N1/2009 virus inside a 1:10 scale mock classroom. Both miniature spectrometer and cell phone camera were used as detector. A 3-D computational fluid dynamics (CFD) model was developed to track the transport/distribution of H1N1/2009 viruses, and corresponded very well with immunosensor readings.