Kim Hyungi, Choi Sang-Kee, Ahn Jungmo, Yu Hojeong, Min Kyoungha, Hong Changgi, Shin Ik-Soo, Lee Sanghee, Lee Hakho, Im Hyungsoon, Ko JeongGil, Kim Eunha
Department of Molecular Science and Technology, Ajou University, Suwon, 16499, Korea.
Department of Computer Engineering, Ajou University, Suwon, 16499, Korea.
Sens Actuators B Chem. 2021 Feb 15;329. doi: 10.1016/j.snb.2020.129248. Epub 2020 Dec 1.
Multiplexed analysis allows simultaneous measurements of multiple targets, improving the detection sensitivity and accuracy. However, highly multiplexed analysis has been challenging for point-of-care (POC) sensing, which requires a simple, portable, robust, and affordable detection system. In this work, we developed paper-based POC sensing arrays consisting of kaleidoscopic fluorescent compounds. Using an indolizine structure as a fluorescent core skeleton, named Kaleidolizine (KIz), a library of 75 different fluorescent KIz derivatives were designed and synthesized. These KIz derivatives are simultaneously excited by a single ultraviolet (UV) light source and emit diverse fluorescence colors and intensities. For multiplexed POC sensing system, fluorescent compounds array on cellulose paper was prepared and the pattern of fluorescence changes of KIz on array were specific to target chemicals adsorbed on that paper. Furthermore, we developed a machine-learning algorithm for automated, rapid analysis of color and intensity changes of individual sensing arrays. We showed that the paper sensor arrays could differentiate 35 different volatile organic compounds using a smartphone-based handheld detection system. Powered by the custom-developed machine-learning algorithm, we achieved the detection accuracy of 97% in the VOC detection. The highly multiplexed paper sensor could have favorable applications for monitoring a broad-range of environmental toxins, heavy metals, explosives, pathogens.
多重分析允许同时测量多个目标，提高检测灵敏度和准确性。然而，对于即时检测（POC）传感来说，高度多重分析一直具有挑战性，即时检测需要一个简单、便携、坚固且经济实惠的检测系统。在这项工作中，我们开发了由万花筒状荧光化合物组成的基于纸的POC传感阵列。使用中氮茚结构作为荧光核心骨架，命名为万花筒中氮茚（KIz），设计并合成了75种不同的荧光KIz衍生物库。这些KIz衍生物由单个紫外（UV）光源同时激发，并发出不同的荧光颜色和强度。对于多重POC传感系统，制备了纤维素纸上的荧光化合物阵列，并且阵列上KIz的荧光变化模式对于吸附在该纸上的目标化学物质具有特异性。此外，我们开发了一种机器学习算法，用于自动、快速分析单个传感阵列的颜色和强度变化。我们展示了纸传感器阵列可以使用基于智能手机的手持检测系统区分35种不同的挥发性有机化合物。在定制开发的机器学习算法的支持下，我们在挥发性有机化合物检测中实现了97%的检测准确率。这种高度多重的纸传感器在监测广泛的环境毒素、重金属、爆炸物、病原体方面可能具有良好的应用。
