Discipline: Technology and Engineering
Subcategory: Electrical Engineering
Session: 2
Room: Virginia C
Kyle Liang - UCLA
Co-Author(s): Jonathan W. Snow, Hatice Ceylan Koydemir, Doruk Kerim Karinca, Derek Tseng, Aydogan Ozcan
The Western Honey Bee plays critical role for maintaining agricultural and ecological stability. However, due to habitat destruction, pesticides, and infectious pathogens, the honey bee’s population has been dwindling over the past years. Some of these infectious microorganisms, Nosema ceranae and Nosema apis, have been identified to contribute greatly to the loss of bee colonies. These microsporidians can be treated, but current technologies to detect these infections require a lab setting and an expert to operate the analytical devices. We propose a cost-effective, portable smartphone-based fluorescence microscope to rapidly scan and diagnose bee tissue samples at the point-of-care.
Our solution utilizes a smartphone coupled with a 3D printed attachment unit to adjust and illuminate the sample. The smartphone based microscope comes with an application that allows users to take images and send them to our local or remote servers to perform image processing. Such analysis returns a count of the Nosema spores, informing the user about the presence of Nosema microorganisms. The procedure takes almost an hour to complete, from the start of the preparation to the displayed spore count on the cellphone.
Comparable in performance to other standard detection methods, our device has a limit of detection of 0.5×10?6 spores per bee. This mobile instrument can be used in-field settings to rapidly detect Nosema ceranae spores in a much shorter time compared to traditional methods. It can also be used by untrained technicians with minimal training requirement. Due to the smartphone design being sample agnostic, the device can be easily reconfigured to handle other samples.
Funder Acknowledgement(s): NSF EFRI (PI: Ozcan)
Faculty Advisor: Aydogan Ozcan, ozcan@ucla.edu
Role: I helped create the server that accepts images from the cellphone. The server then performs image processing and returns a spore count of Nosema found in the sample.