| Diabetes is a metabolic disease caused by either insulin deficiency (type 1 diabetes, hypoglycemia) or by the presence of elevated levels of insulin (type 2 diabetes, hyperglycemia) when pancreatic beta-cells cannot metabolize sugar to maintain normal glucose levels in the body. Compared to the well-established glucometers that monitor millimolar blood glucose levels, it is relatively challenging to measure insulin present at low picomolar levels in complex clinical matrices. Due to rapidly rising rates of type 1 and prediabetic (before type 2) conditions worldwide, and, in particular, 25% of the US population, recently initiatives on the need for selective and sensitive insulin monitoring systems has gained significance.;The objective of my thesis work was to develop novel electrochemical and optical immunosensors for detection of insulin in complex clinical matrices such as serum and whole blood and categorize the type of diabetes. Clinical matrices possess huge non-specific interactions on the sensor surface (matrix interference) and hence detecting picomolar levels of insulin, a small size (5800 Da) protein, with no false positive signals was a challenge. To resolve these detection challenges, insulin was conjugated to magnetic nanoparticles (MNP) which immobilized a high density of insulin molecules from serum and detected picomolar levels by quartz crystal microbalance (QCM), electrochemical impedance spectroscopy (EIS) and square wave voltammetry (SWV). Although the feasibility of quantitatively detecting serum insulin by QCM was established and independent detection modes added reliability in detection, limitation by low-throughput with these methods makes it clinically non-advantageous. Transforming the insulin detection strategy onto a surface plasmon resonance (SPR) microarray imager was henceforth developed which diagnosed insulin levels in clinical samples with ease and also compared the different percentages of serum matrix effect in detection sensitivity. Design of high-throughput ultrasensitive SPR microarray imager for real time insulin detection in patient samples under fasting and non-fasting conditions was also brought forward.;Further advancement from a single biomarker to dual biomarker detection of insulin and glycated hemoglobin (HbA1c) in unprocessed whole blood on SPR imager was also developed to provide an additional information on the type of diabetes and advance the clinical diagnosis for better treatment outcomes. |
