期刊
TALANTA
卷 260, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.talanta.2023.124538
关键词
Nanomaterials; Glucose; Non-enzymatic detection; Microfluidic paper-based analytical device (mu PAD); Point of care diagnostics (POC)
In this study, nanomaterials were integrated into microfluidic paper-based analytical devices (mu PADs) for enzyme-free glucose quantification and colorimetric readout. Gold and silver nanoparticles were used as a peroxidase-like nanozyme and colorimetric probe to detect glucose. The device achieved clinically relevant glucose monitoring with a linear range of 0.50-10.0 mmol L-1 and a detection limit of 340.0 mu mol L-1. The method is rapid (20 min), selective, and potentially suitable for point-of-care diagnostics in resource-limited settings.
In this study, nanomaterials capable of enzyme-free glucose quantification and colorimetric readout are integrated into a microfluidic paper-based analytical devices (mu PADs). Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were utilized as a peroxidase-like nanozyme and a colorimetric probe to achieve glucose monitoring. In this developed device, glucose is oxidized by AuNPs to generate hydrogen peroxide (H2O2), which flows in the paper microchannels toward detection zones. H2O2 then etches the immobilized AgNPs to induce a color change. The intensity of color change is easily monitored using a smartphone application. Following method optimization, we obtained a linear range from 0.50 to 10.0 mmol L-1 (R-2 = 0.9921) and a detection limit (LOD) of 340.0 mu mol L-1. This falls in the clinically relevant range for glucose monitoring and diabetes diagnosis in humans. In addition, the total analysis time is just 20 min, which is significantly less than the same experiment performed in the solution phase. Also, our method is markedly selective; other substrates do not interfere. The recovery test in human control samples was in the range of 98.47-102.34% and the highest relative standard deviation (RSD) was 3.58%. The enzyme-free approach for glucose sensing is highly desirable for diabetes diagnosis as it replaces the more expensive enzyme with cheaper nanomaterials. Furthermore, since nanomaterials are more environmentally stable compared to enzymes, it has the potential for widespread deployment as point-of-care diagnostics (POC) in resource-limited settings.
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