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Letter to the Editor | Open Access

Development of Exhaled Breath Diagnosis Sensors for Rapid Identification of COVID-19 Patients

Cuili Xue1Amin Zhang1Yunsheng Chen2Hui Liang3Jing Tian3Jingpu Zhang4Chen Zhou3Jian Ni1,3Han Jin1,3( )Daxiang Cui1,3( )
Institute of Nano Biomedicine and Engineering, Shanghai Engineering Center for Intelligent Diagnosis and Treatment Instrument, Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, School of Medicine Shanghai Jiao Tong University, 639 Zhizaoju Road, Shanghai 200011, China
National Engineering Research Center for Nanotechnology, 28 Jiangchuan Road, Shanghai 200241, China
Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Jinshan District, Shanghai 201508, China
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Abstract

The novel coronavirus pneumonia, a global pandemic disease named as coronavirus disease 2019, has caused enormous losses on the health and economies of people all over the world, while there is still a lack of quick and sensitive diagnostic method and effective therapy. Developing rapid diagnostic method for coronavirus disease 2019 has become exceptional urgent. Herein we report a rapid diagnostic method for the novel coronavirus through monitoring the volatile biomarkers in human exhaled breath. The breath volatile biomarkers are derived from the metabolism of novel coronavirus, including acetoin, 2,4,6-trimethylpyridine, 3-methyl tridecane, tetradecane, isooctyl alcohol, pentadecane, hexadecane, 1-methylene-1H-indene. By comparing the types and concentrations of the volatile biomarkers in human exhaled breath combined with SERS sensor, we could distinguish between the healthy person and the patients with coronavirus disease 2019. This work confirms that various volatile organic compounds metabolized by novel coronavirus can be employed for rapidly screening of patients with coronavirus disease 2019, and has broad application prospects in the prevention and control of the epidemic.

References

[1]

B.A. Resnick, P.C. Mui, J. Bowie, et al., The COVID-19 Pandemic: An Opportunity to Transform Higher Education in Public Health. Public Health Reports. 2021, 136(1): 23-26.

[2]

A.B. Gussow N. Auslander, Y.I. Wolf, et al., Prediction of the incubation period for COVID-19 and future virus disease outbreaks. Bmc Biology, 2020, 18(1): 1-12.

[3]

A. Higham, A. Mathioudakis, J. Vestbo, et al., COVID-19 and COPD: a narrative review of the basic science and clinical outcomes. European respiratory review, 2020, 29(158).

[4]

A. Natarajan, H.W. Su, and C. Heneghan, Assessment of physiological signs associated with COVID-19 measured using wearable devices. Npj Digital Medicine, 2020, 3(1): 1-8.

[5]

K.G. Aghila Rani, M.A. Hamad, D.M. Zaher, et al., Drug development post COVID-19 pandemic: toward a better system to meet current and future global health challenges. Expert opinion on drug discover, 2021, 16(4): 365-371.

[6]

J.K. Schubert, W. Miekisch, K. Geiger, et al., Breath Analysis in Critically Ill Patients: Potential and Limitations. Expert Review of Molecular Diagnostics, 2004, 4(5): 619-629.

[7]

W.Q. Cao, Y.X. Duan. Breath analysis: Potential for clinical diagnosis and exposure assessment. Clinical Chemistry, 2006, 52(5): 800-811.

[8]

N.J.W. Rattray, Z. Hamrang, D.K. Trivedi, et al., Taking your breath away: metabolomics breathes life in to personalized medicine. Trends Biotechnol, 2014, 32(10): 538-548.

[9]

A.S. Modak, Breath biomarkers for personalized medicine. Pers Med, 2010, 7(6): 643-653.

[10]

P.M. van Oort, P. Povoa, R. Schnabel, et al., The potential role of exhaled breath analysis in the diagnostic process of pneumonia-a systematic review. J Breath Res, 2018, 12(2): 024001.

[11]

J. Pang, J. Feldman, V. Liberman, et al., Don't Waste Your Breath: A Study of Inhaler Disposal at Hospital Discharge for Copd Patients with Acute Exacerbations. Journal of General Internal Medicine, 2015, 30: 144.

[12]

W. Miekisch, J.K. Schubert, and G.F. Noeldge-Schomburg, Diagnostic potential of breath analysis - focus on volatile organic compounds. Clinica chimica acta, 2004, 347(1-2): 25-39.

[13]

M. Alonso, J.M. Sanchez. Analytical challenges in breath analysis and its application to exposure monitoring. Trac-Trend Anal Chem, 2013, 44: 78-89.

[14]

L. Fleming, D. Gibson, D. Hutson, et al., Breath emulator for simulation and modelling of expired tidal breath carbon dioxide characteristics. Computer methods and programs in biomedicine, 2020, 200: 105826.

[15]

P.J. Chien, T. Suzuki, M. Ye, et al., Ultra-Sensitive Isopropanol Biochemical Gas Sensor (Bio-Sniffer) for Monitoring of Human Volatiles. Sensors, 2020, 20(23): 6827.

[16]

L. Andre, N. Desbois, C.P. Gros, et al., Porous materials applied to biomarker sensing in exhaled breath for monitoring and detecting non-invasive pathologies. Dalton T. 2020, 49(43): 15161-15170.

[17]

S.M. Aghaei, A. Aasi, S. Farhangdoust, et al., Graphene-like BC6N nanosheets are potential candidates for detection of volatile organic compounds (VOCs) in human breath: A DFT study. Appl Surf Sci, 2021, 536: 147756.

[18]

A. Aasi, S.M. Aghaei, and B. Panchapakesan, A density functional theory study on the interaction of toluene with transition metal decorated carbon nanotubes: a promising platform for early detection of lung cancer from human breath. Nanotechnology, 2020, 31(41): 415707.

[19]

V. Shestivska, K. Dryahina, J. Nunvar, et al., Quantitative analysis of volatile metabolites released in vitro by bacteria of the genus Stenotrophomonas for identification of breath biomarkers of respiratory infection in cystic fibrosis. J Breath Res, 2015, 9(2): 027104.

[20]

M. Phillips, J.P. Boehmer, R.N. Cataneo, et al., Heart allograft rejection: Detection with breath alkanes in low levels (the HARDBALL study). J Heart Lung Transpl, 2004, 23: 701-708.

[21]

B.J. Novak, D.R. Blake, S. Meinardi, et al., Exhaled methyl nitrate as a noninvasive marker of hyperglycemia in type 1 diabetes. P Natl Acad Sci USA, 2007, 104: 15613-15618.

[22]

M.A. Kamboures, D.R. Blake, D.M. Cooper, et al., Breath sulfides and pulmonary function in cystic fibrosis. P Natl Acad Sci USA, 2005, 102: 15762-15767.

[23]

M. Khoubnasabjafari, V. Jouyban-Gharamaleki, R. Ghanbari, et al., Exhaled breath condensate as a potential specimen for diagnosing COVID-19. Bioanalysis, 2020, 12: 1195-1197.

[24]

B. Shan, Y. Y. Broza, W. J. Li, et al., Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath. ACS Nano, 2020, 14: 12125-12132.

[25]

Y.S. Chen, Y.X. Zhang, F. Pan, et al., Breath Analysis Based on Surface-Enhanced Raman Scattering Sensors Distinguishes Early and Advanced Gastric Cancer Patients from Healthy Persons. ACS Nano, 2016, 10: 8169-8179.

[26]

Y.S. Chen, S.L. Cheng, A.M. Zhang, et al., Salivary Analysis Based on Surface Enhanced Raman Scattering Sensors Distinguishes Early and Advanced Gastric Cancer Patients from Healthy Persons. Journal of Biomedical Nanotechnology, 2018, 14: 1773-1784.

[27]

M.A. Aslam, C.L. Xue, Y.S. Chen, et al., Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network. Scientific reports, 2021, 11: 4014.

Nano Biomedicine and Engineering
Pages 225-228
Cite this article:
Xue C, Zhang A, Chen Y, et al. Development of Exhaled Breath Diagnosis Sensors for Rapid Identification of COVID-19 Patients. Nano Biomedicine and Engineering, 2021, 13(3): 225-228. https://doi.org/10.5101/nbe.v13i3.p225-228

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Received: 23 February 2021
Accepted: 05 August 2021
Published: 06 August 2021
© Cuili Xue, Amin Zhang, Yunsheng Chen, Hui Liang, Jing Tian, Jingpu Zhang, Chen Zhou, Jian Ni, Han Jin, and Daxiang Cui.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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