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ACS Nano

Title:		Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
Author(s):		Leong SX; Leong YX; Tan EX; Sim HYF; Koh CSL; Lee YH; Chong C; Ng LS; Chen JRT; Pang DWC; Nguyen LBT; Boong SK; Han X; Kao YC; Chua YH; Phan-Quang GC; Phang IY; Lee HK; Abdad MY; Tan NS; Ling XY;
Address:		"Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore. Silver Factory Technology Pte. Ltd., Singapore 169203, Singapore. Infectious Diseases Research Laboratory, National Centre for Infectious Diseases, Singapore 308442, Singapore. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LG, U.K. Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore. School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore"
Journal Title:		ACS Nano
Year:		2022
Volume:		20220118
Issue:		2
Page Number:		2629 - 2639
DOI:		10.1021/acsnano.1c09371
ISSN/ISBN:		1936-086X (Electronic) 1936-0851 (Linking)
Abstract:		"Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes"
Keywords:		"*covid-19 Humans Mass Screening Point-of-Care Systems SARS-CoV-2 Spectrum Analysis, Raman/methods breath volatile organic compounds (BVOCs) breathomics coronavirus disease 2019 (COVID-19) surface-enhanced Raman scattering (SERS);"
Notes:		"MedlineLeong, Shi Xuan Leong, Yong Xiang Tan, Emily Xi Sim, Howard Yi Fan Koh, Charlynn Sher Lin Lee, Yih Hong Chong, Carice Ng, Li Shiuan Chen, Jaslyn Ru Ting Pang, Desmond Wei Cheng Nguyen, Lam Bang Thanh Boong, Siew Kheng Han, Xuemei Kao, Ya-Chuan Chua, Yi Heng Phan-Quang, Gia Chuong Phang, In Yee Lee, Hiang Kwee Abdad, Mohammad Yazid Tan, Nguan Soon Ling, Xing Yi eng 2022/01/19 ACS Nano. 2022 Feb 22; 16(2):2629-2639. doi: 10.1021/acsnano.1c09371. Epub 2022 Jan 18"