文章基本信息

标题：Enzymatic Low Volume Passive Sweat Based Assays for Multi-Biomarker Detection
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作者：Ashlesha Bhide ; Sarah Cheeran ; Sriram Muthukumar 等
期刊名称：Biosensors
电子版ISSN：2079-6374
出版年度：2019
卷号：9
期号：1
页码：13-26
DOI：10.3390/bios9010013
出版社：MDPI Publishing
摘要：Simultaneous detection of correlated multi-biomarkers on a single low-cost platform in ultra-low fluid volumes with robustness is in growing demand for the development of wearable diagnostics. A non-faradaic biosensor for the simultaneous detection of alcohol, glucose, and lactate utilizing low volumes (1–5 μL) of sweat is demonstrated. Biosensing is implemented using nanotextured ZnO films integrated on a flexible porous membrane to achieve enhanced sensor performance. The ZnO sensing region is functionalized with enzymes specific for the detection of alcohol, glucose, and lactate in the ranges encompassing their physiologically relevant levels. A non-faradaic chronoamperometry technique is used to measure the current changes associated with interactions of the target biomarkers with their specific enzyme. The specificity performance of the biosensing platform was established in the presence of cortisol as the non-specific molecule. Biosensing performance of the platform in a continuous mode performed over a 1.5-h duration showed a stable current response to cumulative lifestyle biomarker concentrations with capability to distinguish reliably between low, mid, and high concentration ranges of alcohol (0.1, 25, 100 mg/dL), glucose (0.1, 10, 50 mg/dL), and lactate (1, 50, 100 mM). The low detection limits and a broader dynamic range for the lifestyle biomarker detection are quantified in this research demonstrating its suitability for translation into a wearable device.
关键词：wearable biosensing; enzyme-based assay; alcohol detection; glucose detection; lactate detection; chronoamperometry; sweat sensing; continuous monitoring wearable biosensing ; enzyme-based assay ; alcohol detection ; glucose detection ; lactate detection ; chronoamperometry ; sweat sensing ; continuous monitoring