Optoelectrokinetic Screening for the Biomarker Lipocalin 1 of Diabetic Retinopathy

Abstract

Disease diagnosis in incubation period and early stages faces various challenges As diseases elicit adverse effects upon diagnosis in late stages therapeutic efficiency is reduced For example diabetic retinopathy (DR) is a common complication and major cause of vision loss among patients with diabetes mellitus In clinical diagnosis DR is examined through fluorescence angiography (FA) Although this method provide information on blood vessel conformation the detection of changes in blood vessel conformation without a quantitative basis is dependent on a physician’s clinical experiences In most cases a patient’s condition has progressed to proliferative diabetic retinopathy (PDR) when abnormalities are detected As a consequence patients must undergo surgery to recover their eyesight Therefore signs and symptoms should be detected and treated in early stages to help prevent vision loss In this research a low-concentration non-invasive detection platform was developed to detect and quantify DR biomarkers in early stages Tears were used as a biological sample because they contain DR biomarkers such as lipocalin 1 (LCN1) A specific bond between an antigen and an antibody was formed through the bead-based sandwiched immunosensing Rapid electrokinetic patterning (REP) an optoelectrokinetic technology was employed to focus on immunosensed particles and enhance the fluorescence signal Results revealed that the LCN1 concentration in the tears of normal control subjects was 3150 μg/mL The LCN1 concentration in the tears of patients with DR increased with disease severity The detection limit was 15 pg/mL and this limit was sufficient to detect DR in early stages REP was also applied to sort different particle sizes cross-match different biomarkers in the tears of patients with DR and enhance the accuracy of the detection platform Our results suggested that the proposed detection platform could be used to diagnose different diseases and specimens and to detect DR by using biomarkers present in various specimens such as saliva and urine through immunosensing and signal amplification The detection platform could also be utilized to address the quantification limitations in point-of-care ophthalmologic diagnosis Further research should be conducted to protect the vision of diabetic mellitus patients

Date of Award	2016 Aug 25
Original language	English
Supervisor	Han-Sheng Chuang (Supervisor)