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一种用于支气管扩张症选择性检测的智能手机接口低成本比色生物传感器及人工神经网络。

A smartphone-interfaced, low-cost colorimetry biosensor for selective detection of bronchiectasis an artificial neural network.

作者信息

Sha Mizaj Shabil, Maurya Muni Raj, Chowdhury Muhammad E H, Muthalif Asan G A, Al-Maadeed Somaya, Sadasivuni Kishor Kumar

机构信息

Center for Advanced Materials, Qatar University P.O. Box 2713 Doha Qatar

Department of Electrical Engineering, Qatar University P.O. Box 2713 Doha Qatar.

出版信息

RSC Adv. 2022 Aug 26;12(37):23946-23955. doi: 10.1039/d2ra03769f. eCollection 2022 Aug 22.

DOI:10.1039/d2ra03769f
PMID:36128540
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9414259/
Abstract

Exhaled breath (EB) contains several macromolecules that can be exploited as biomarkers to provide clinical information about various diseases. Hydrogen peroxide (HO) is a biomarker because it indicates bronchiectasis in humans. This paper presents a non-invasive, low-cost, and portable quantitative analysis for monitoring and quantifying HO in EB. The sensing unit works on colorimetry by the synergetic effect of eosin blue, potassium permanganate, and starch-iodine (EPS) systems. Various sampling conditions like pH, response time, concentration, temperature and selectivity were examined. The UV-vis absorption study of the assay showed that the dye system could detect as low as ∼0.011 ppm levels of HO. A smart device-assisted detection unit that rapidly detects red, green and blue (RGB) values has been interfaced for practical and real-time application. The RGB value-based quantification of the HO level was calibrated against NMR spectroscopy and exhibited a close correlation. Further, we adopted a machine learning approach to predict HO concentration. For the evaluation, an artificial neural network (ANN) regression model returned 0.941 suggesting its great prospect for discrete level quantification of HO. The outcomes exemplified that the sensor could be used to detect bronchiectasis from exhaled breath.

摘要

呼出气体（EB）中含有多种大分子物质，可作为生物标志物用于提供有关各种疾病的临床信息。过氧化氢（HO）就是一种生物标志物，因为它可指示人类的支气管扩张症。本文介绍了一种用于监测和定量分析EB中HO的非侵入性、低成本且便携的定量分析方法。传感单元通过曙红蓝、高锰酸钾和淀粉碘（EPS）系统的协同作用进行比色法工作。研究了各种采样条件，如pH值、响应时间、浓度、温度和选择性。该检测方法的紫外可见吸收研究表明，该染料系统能够检测低至约0.011 ppm水平的HO。一个可快速检测红、绿、蓝（RGB）值的智能设备辅助检测单元已连接用于实际和实时应用。基于RGB值对HO水平进行的定量分析已针对核磁共振光谱进行校准，并显示出密切相关性。此外，我们采用机器学习方法来预测HO浓度。为进行评估，人工神经网络（ANN）回归模型得出的结果为0.941，表明其在HO离散水平定量分析方面具有巨大前景。这些结果表明该传感器可用于从呼出气体中检测支气管扩张症。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feae/9414259/b15ecdfa31d2/d2ra03769f-f10.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feae/9414259/b15ecdfa31d2/d2ra03769f-f10.jpg
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