Issue 24, 2022

Smartphone surface plasmon resonance imaging for the simultaneous and sensitive detection of acute kidney injury biomarkers with noninvasive urinalysis

Abstract

A surface plasmon resonance imaging (SPRi) platform integrated with a smartphone was constructed for the simultaneous and sensitive detection of acute kidney injury (AKI) biomarkers. The smartphone SPRi platform was developed without the requirement of additional light and power sources. The LED flash of the smartphone was used as the light source for the excitation of surface plasmon resonance of a gold sensor chip based on the Kretschmann configuration, while the reflected light was collected by the camera of the smartphone. This smartphone SPRi system was conveniently fabricated by 3D printing and showed a sensitivity of 1.78 × 10−5 refractive index unit (RIU). In addition, based on a magnetic nanoparticle-enhanced sandwich immunoassay, the smartphone SPRi system with a gold array chip was employed for the detection of multiple AKI biomarkers, with a low limit of detection (LOD) of 0.19 ng ml−1, 0.51 ng ml−1 and 0.7 ng ml−1 for the simultaneous detection of neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18) and retinol-binding protein (RBP) in urine, respectively. The biosensors demonstrated high specificity and sensitivity for the simultaneous detection of multiple AKI biomarkers in PBST and urine. The smartphone SPRi system provided a portable and cost-effective platform for point-of-care diagnosis, in-field healthcare and environmental monitoring.

Graphical abstract: Smartphone surface plasmon resonance imaging for the simultaneous and sensitive detection of acute kidney injury biomarkers with noninvasive urinalysis

Supplementary files

Article information

Article type
Paper
Submitted
07 May 2022
Accepted
09 Nov 2022
First published
14 Nov 2022

Lab Chip, 2022,22, 4941-4949

Smartphone surface plasmon resonance imaging for the simultaneous and sensitive detection of acute kidney injury biomarkers with noninvasive urinalysis

Q. Zhang, Y. Li, Q. Hu, R. Xie, W. Zhou, X. Liu and Y. Wang, Lab Chip, 2022, 22, 4941 DOI: 10.1039/D2LC00417H

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