Dual-signal output paper sensor based on coordinative self-assembly biomimetic nanozyme for point-of-care detection of biomarker

信号(编程语言) 计算机科学 辣根过氧化物酶 检测点注意事项 对偶(语法数字) 注意事项 概念证明 纳米技术 组合化学 化学 材料科学 生物化学 医学 生物 操作系统 文学类 艺术 护理部 程序设计语言 免疫学
作者
Yuanchun Du,Zhenyi Ke,Jiaheng Zhang,Guangfu Feng
出处
期刊:Biosensors and Bioelectronics [Elsevier BV]
卷期号:216: 114656-114656 被引量:30
标识
DOI:10.1016/j.bios.2022.114656
摘要

Paper-based point-of-care (POC) devices exhibit the advantages of simplicity, rapidity, trim sizes, and low cost, which are of particular importance for food safety, biological analysis, and medical diagnosis. However, the materials utilized to make paper-based POC rarely produce multiple signals, hampering further applications in diverse situations. Herein, we present an appealing approach, namely Colorimetric-Temperature Dual-Signal Output Sensor (CTDSS), and construct a CTDSS based on coordinative self-assembly biomimetic nanozymes Fe-GMP-L-His CPNs as a proof of concept. These CPNs mimic the structure of horseradish peroxidase (HRP), in which Fe (II) is the center, nucleotide GMP and histidine are chosen as ligands to simulate metal coordination of the pyrrole ring and protein function in HRP, respectively. This strategy allows CPNs to show an excellent peroxidase-like activity, efficiently converting H2O2 into •OH and oxidizing TMB to generate colorimetric-temperature dual-signal. As a proof-of-concept application, we exploited cholesterol as the target and successfully applied this CTDSS to detect cholesterol, displaying extraordinary features of rapidity, dramatic specificity, and high sensitivity. By utilizing the colorimetric test strip and temperature discoloration sticker, the paper-based POC tools were constructed to visualize the target. Meanwhile, two proposed test strip POC devices generating different signal outputs exhibited remarkable feasibility and were further employed to detect cholesterol in human serum. We anticipate that this CTDSS platform will inspire innovative concepts for future portable detection tools.
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