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At-Home Diagnostics

<< 2014 Projects

 Using Fluorescence Imaging to Diagnose Tuberculosis


Need: A cost effective way to diagnose Tuberculosis within a day at home in a non-clinical setting for those with little/no access to physicians.

 

Abstract

Tuberculosis, commonly referred to as TB, is an infectious disease caused by the bacterium Mycobacterium Tuberculosis (Mtb) that primarily harms the lungs. TB currently affects nearly 13 million people globally. People with suppressed immune systems are much more susceptible to contracting TB and most cases occur in developing countries and areas with limited health care.

The most common diagnostic method, the skin test, consists of inserting a small amount of tuberculin into a patient’s lower arm. After two to three days, the patient returns to the hospital to get his or her arm checked for swelling, which indicates a positive result. This current diagnostic scheme holds a consumer cost of $50, requires clinical care, and lacks consumer efficiency for those living far from hospitals.

Our project is to develop a cost effective method of diagnosing Tuberculosis within a day in a non-clinical setting for those who do not have the benefits of easilyaccessible healthcare. Dr. Jianghong Rao’s lab has developed a method for Mtb detection using the fluorescent probe, CDG-oME, and the enzyme BlaC (naturally occurring in Mtb) as a marker. Based on this detection method, we created a light-imaging device that mimics the function of a fluorescence detector but provides the affordability and ease of an at-home diagnostic. In light of simplicity and limitedresources, fluorescein, a dye with similar emission and excitation wavelengths as CDG-oME, was used as substitute for testing the success and accuracy of our device. With a light-sensing LED for fluorescent detection, this device would be suitable for use in third world countries; nonetheless, after further testing, a detection device utilizing an iPhone application proved to be more accurate in detecting fluorescence. Despite these drawbacks, directions towards a stronger light sensor seem viable in the near future.

(Left to right) Jack Murphy, Soham More, Mansi Shah, and Christina Chen worked on diagnosing tuberculosis infections at home without the use of a skin test by developing a light box integrated with an iPhone for image capture. This light box is able to measure fluorescent signals from a probe developed by Dr. Jianghong Rao’s lab on campus which senses a naturally occurring enzyme produced by tuberculosis bacteria.

 

Click here to see the group's poster.