from Part VII - Lab-on-a-chip
Published online by Cambridge University Press: 05 September 2015
Introduction
Biomolecular detection is crucial from various perspectives, such as quality control of our food and water, identification of biological terrorist agents, and diagnosis of diseases. Early detection of disease is important for effective treatment and for prognostic assessment of disease progression; in addition, the trend of ageing societies leads to an increasing requirement for biomarker diagnoses for personalized healthcare monitoring. This results in more stress on the social healthcare system [1, 2]. As a consequence, researchers have focused on developing biomolecular detection devices and systems. Over the past decade, emerging methods to address the above needs have bloomed because of developments in micro/nanotechnologies. To enhance throughputs and reduce costs, moreover, these detection devices and systems are evolving from label-based to label-free technologies.
Traditionally, label-based molecular diagnosis techniques have been used as a useful fundamental concept for the detection of potential disease biomarkers or pathogen nucleic acids. In general, the detection signal comes from the usage of a specific tag for a target molecule. The tags can be conventional fluorescent dyes or radioisotopes. To fulfill the requirements of different applications, a number of conventional label-based techniques, such as polymerase chain reaction (PCR), DNA or protein microarrays, and enzyme-linked immunosorbent assay (ELISA), have been developed and implemented. Some of them have been used to form a versatile platform for many diverse applications with promising results and represent the gold standards of biomedical diagnosis [3–5]. However, these techniques require trained staff and expensive equipment, and are time-consuming. Moreover, the detection of such low-abundance biomarkers in biological fluids (e.g. blood, urine, saliva) requires large quantities of the sample and complicated sample preparation. Consequently, these label-based techniques encounter problems of cost-effectiveness and throughput under modern circumstances.
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