Flexible Wearable Microfluidic Colorimetric Sensor for Multiplex Bioenzyme-Free Detection of Creatinine, Urea, and Magnesium Ions in Sweat

材料科学 多路复用 微流控 尿素 可穿戴计算机 离子 汗水 肌酐 纳米技术 分析化学(期刊) 光电子学 色谱法 计算机科学 生物化学 有机化学 化学 生物信息学 冶金 生物 海洋学 地质学 嵌入式系统
作者
Fang Li,Limin Zhang,Chen Yang,Nuotong Shen,Junhao Gao,Zijun Ma,Weijun Kong,Lifu Liu,Bing Li,Jianbo He
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:17 (25): 36444-36454 被引量:13
标识
DOI:10.1021/acsami.5c05611
摘要

Wearable microfluidic detection devices for noninvasive sweat analysis are highly desirable for human health monitoring. Herein, we present a bioenzyme-free microfluidic colorimetric detection device for simultaneous detection of creatinine (Cre), urea, and Mg2+ in sweat, enabling comprehensive kidney function and mental stress assessment. The device leverages a ternary catalytic system composed of H2MoO5 nanomaterial, Cu2+, and Cre, which exhibits significantly enhanced oxidase-like activity. This system directly catalyzes the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) to generate a blue product (ox-TMB), providing a robust platform for Cre detection without the need for bioenzymes. For urea and Mg2+ detection, 4-dimethylaminobenzaldehyde and chromium black T were employed as effective chromogenic reagents, respectively. A flexible multichannel microfluidic chip was fabricated, incorporating specific colorimetric reagent-modified paper chips into the corresponding reaction reservoirs. This design allows for the simultaneous detection of Cre, urea, and Mg2+ in sweat with linear ranges of 10–100 μM, 10–70 mM, and 0.5–8 mM, respectively. The device’s performance was validated using actual sweat samples, with detection results analyzed via a smartphone application, demonstrating high accuracy and reliability. This work introduces a simple, low-cost, and stable bioenzyme-free microfluidic colorimetric detection device, offering significant potential for in situ and intelligent sweat analysis. The integration of smartphone technology further enhances its practicality, making it a promising tool for real-time health monitoring and point-of-care testing.
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