Abstract

AbstractA novel integrated biosensor methodology is proposed and demonstrated. The methodology utilizes a nitrogen-containing plasma polymer to achieve linker-free binding of biorecognition molecules that allows the sensor surface to be freeze dried for long shelf life under ambient conditions. The sensor is configured for single wavelength ellipsometric detection providing a low cost, versatile, and rapid sensing and diagnosis platform suitable for a wide range of applications and end-users. The merits of the methodology were demonstrated using three antigen-antibody pairs.

Highlights

  • Biosensing using a biological recognition element is the preferred approach to identify and quantify biologically-relevant analytes

  • Sensing optimization The concept of our biosensor methodology using ellipsometry is illustrated in figure 1

  • The sensitivity near the valley is low and varies significantly ; it is necessary to choose the nitrogen-containing plasma polymer (NPP) thickness to avoid locating the valley of the Psi spectrum near the 632 nm sensing wavelength

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Summary

Introduction

Biosensing using a biological recognition element is the preferred approach to identify and quantify biologically-relevant analytes. Suitable approaches that have been demonstrated using biological recognition elements include antigen-antibody interactions[1,2], oligonucleotides[3,4], lectin-glycoprotein and hormone-receptor interactions[5, 6]. In these interactions, molecular binding or detaching is quantified or sensed using a transducer. All of the techniques suffer from at least one of the following drawbacks: lengthy and complex processing for the preparation of linkers to provide robust immobilization of the initial biological recognition layer, non-specific interactions, a short shelf life of pre-prepared sensors, and the lack of a convenient, reliable and rapid diagnosis method[14, 15]. An integrated solution is needed that brings together in the sensor design, simple and universal immobilization, storage shelf life and simple diagnosis methodology

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