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ACS Nano

Title:		Modular Assembly of MXene Frameworks for Noninvasive Disease Diagnosis via Urinary Volatiles
Author(s):		Ding X; Zhang Y; Zhang Y; Ding X; Zhang H; Cao T; Qu ZB; Ren J; Li L; Guo Z; Xu F; Wang QX; Wu X; Shi G; Haick H; Zhang M;
Address:		"School of Chemistry and Molecular Engineering, Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, Engineering Research Centre for Nanophotonics and Advanced Instrument (Ministry of Education), East China Normal University, Shanghai 200241, China. College of Architecture and Art, Hefei University of Technology, Hefei 230601, China. Bengbu Medical University, Anhui Provincial Hospital, Bengbu 233030, China. School of Mechanical Engineering, Hefei University of Technology, Hefei 230601, China. Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China. Department of Infectious Disease, The First Affiliated Hospital, University of Science and Technology of China, Hefei 230001, China. Department of Pharmacy, Sixth People's Hospital South Campus, Shanghai Jiao Tong University, Shanghai 201499, China. College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China. School of Communication and Electronic Engineering, East China Normal University, Shanghai 200241, China. Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion - Israel Institute of Technology, 320003 Haifa, Israel"
Journal Title:		ACS Nano
Year:		2022
Volume:		20221013
Issue:		10
Page Number:		17376 - 17388
DOI:		10.1021/acsnano.2c08266
ISSN/ISBN:		1936-086X (Electronic) 1936-0851 (Linking)
Abstract:		"Volatile organic compounds (VOCs) in urine are valuable biomarkers for noninvasive disease diagnosis. Herein, a facile coordination-driven modular assembly strategy is used for developing a library of gas-sensing materials based on porous MXene frameworks (MFs). Taking advantage of modules with diverse composition and tunable structure, our MFs-based library can provide more choices to satisfy gas-sensing demands. Meanwhile, the laser-induced graphene interdigital electrodes array and microchamber are laser-engraved for the assembly of a microchamber-hosted MF (MHMF) e-nose. Our MHMF e-nose possesses high-discriminative pattern recognition for simultaneous sensing and distinguishing of complex VOCs. Furthermore, with the MHMF e-nose being a plug-and-play module, a point-of-care testing (POCT) platform is modularly assembled for wireless and real-time monitoring of urinary volatiles from clinical samples. By virtue of machine learning, our POCT platform achieves noninvasive diagnosis of multiple diseases with a high accuracy of 91.7%, providing a favorable opportunity for early disease diagnosis, disease course monitoring, and relevant research"
Keywords:		*Volatile Organic Compounds *Graphite Electronic Nose Biomarkers *Smart Materials MXene frameworks e-nose machine learning noninvasive disease diagnosis urinary volatiles;
Notes:		"MedlineDing, Xuyin Zhang, Yecheng Zhang, Yue Ding, Xufa Zhang, Hanxin Cao, Tian Qu, Zhi-Bei Ren, Jing Li, Lei Guo, Zhijun Xu, Feng Wang, Qi-Xian Wu, Xing Shi, Guoyue Haick, Hossam Zhang, Min eng Research Support, Non-U.S. Gov't 2022/10/14 ACS Nano. 2022 Oct 25; 16(10):17376-17388. doi: 10.1021/acsnano.2c08266. Epub 2022 Oct 13"