Degree Type

Thesis

Date of Award

2019

Degree Name

Master of Science

Department

Electrical and Computer Engineering

Major

Electrical Engineering

First Advisor

Long Que

Abstract

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

Language

en

File Format

application/pdf

File Size

49 pages

Share

COinS