Degree Type


Date of Award


Degree Name

Master of Science


Electrical and Computer Engineering


Electrical Engineering

First Advisor

Long Que


This thesis reports on using label-free optical sensors for multiplexed detection of autoantibodies for Type 1 Diabetes. An autoimmune disease that occurs when the body either does not produce enough or stops producing insulin, the hormone that controls blood-sugar levels. Autoantibodies working against islet antigens such as insulin, glutamic acid decarboxylase (GAD), and insulinoma associated protein-2 (IA-2) have been well-confirmed in Type 1 Diabetes (T1D) panels. While clinical diagnosis of T1D can be performed by detecting the level of autoantibodies in a blood sample, sensitive detections are especially crucial for predictive analysis and early screening of potential diabetes victims.

The label-free optical sensor was made from Anodic Aluminum Oxide (AAO), a self-organized material formed by high-density arrays of uniform and parallel porous nanostructures, which has been widely utilized in biomedical sensing and bioanalysis area. We have demonstrated multiplexed detection of autoantibodies using label-free optical sensors that can readily detect as a small level as 0.1 U/ml of three autoantibodies in human serum. In addition, the specificity of the sensor has also been evaluated by detecting autoantibodies in a nonspecific antigen with results reflecting good specificity. Moreover, multiplexed detection of insulin, GAD, and IA-2 antibodies in serum using such chip has also been demonstrated.

Copyright Owner

Subin Mao



File Format


File Size

49 pages