Paper Microfluidics and Tailored Gold Nanoparticles for Nonenzymatic, Colorimetric Multiplex Biomarker Detection

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Abstract

The plasmonic properties of gold nanoparticles (AuNPs) are a promising tool to develop sensing alternatives to traditional, enzyme-catalyzed reactions. The need for sensing alternatives, especially in underdeveloped areas of the world, has given rise to the application of nonenzymatic sensing approaches paired with cellulosic substrates to biochemical analysis. Herein, we present three individual, low-step, wet-chemistry, colorimetric assays for three target biomarkers, namely, glucose, uric acid, and free cholesterol, relevant in diabetes control and their translation into paper-based assays and microfluidic platforms for multiplexed analysis. For glucose determination, an in situ AuNPs synthesis approach was applied into the developed μPAD, giving semiquantitative measures in the physiologically relevant range. For uric acid and cholesterol determination, modified AuNPs were used to functionalize paper with a gold-on-paper approach with the optical properties changing based on different aggregation degrees and hydrophobic properties of particles dependent on analyte concentration. These paper-based assays show sensitivity ranges and limits of detection compatible for target analyte level determination and detection limits comparable to those of similar enzymatic, colorimetric systems, relying only on plasmonic transduction without the need for enzymatic activity or other chromogenic substrates. The resulting paper-based assays were integrated into a single 3D, multiplex paper-based device using paper microfluidics, showing the capability for performing different colorimetric assays with distinct requirements in terms of sample flow and sample uptake in test zones using a combination of both horizontal and vertical flows inside the same device. The presented device allows for multiparametric, colorimetric measures of different metabolite levels from a single complex sample matrix drop using digital color analysis, showing the potential for development of low-cost, low-complexity tools for diagnostics toward the point-of-care.

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