TY - JOUR
T1 - Label-free laser spectroscopy for respiratory virus detection
T2 - A review
AU - Kistenev, Yury V.
AU - Das, Anubhab
AU - Mazumder, Nirmal
AU - Cherkasova, Olga P.
AU - Knyazkova, Anastasia I.
AU - Shkurinov, Alexander P.
AU - Tuchin, Valery V.
AU - Lednev, Igor K.
N1 - Funding Information:
The research was carried out with the support of a grant under the Decree of the Government of the Russian Federation No. 220 of April 9, 2010 (Agreement No. 075‐15‐2021‐615 of June 4, 2021). NM thank the Department of Science and Technology (DST), India (Project Number‐ SERB/MTR/2020/000058) and the Indian Council of Medical Research (ICMR) (Project Number‐ITR/Ad‐hoc/43/2020‐21, ID No. 2020‐3286) Government of India, India for financial support. Additionally, some sections were also funded by the Ministry of Science and Higher Education under Agreement No. 075‐15‐2019‐1950; the Ministry of Science and Higher Education of the Russian Federation within the State Assignment FSRC “Crystallography and Photonics” RAS; and the Interdisciplinary Scientific and Educational School of Moscow University “Photonic and Quantum Technologies Digital Medicine.”
Funding Information:
Department of Science and Technology, India, Grant/Award Number: SERB/MTR/2020/000058; the Government of the Russian Federation, Grant/Award Number: 075‐15‐2021‐615; the Ministry of Science and Higher Education of the Russian Federation, Grant/Award Number: 075‐15‐2019‐1950; Tomsk State University; Ministry of Science and Higher Education of the Russian Federation; Indian Council of Medical Research Funding information
Publisher Copyright:
© 2022 Wiley-VCH GmbH.
PY - 2022/10
Y1 - 2022/10
N2 - Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.
AB - Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.
UR - http://www.scopus.com/inward/record.url?scp=85135609296&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135609296&partnerID=8YFLogxK
U2 - 10.1002/jbio.202200100
DO - 10.1002/jbio.202200100
M3 - Review article
AN - SCOPUS:85135609296
SN - 1864-063X
VL - 15
JO - Journal of Biophotonics
JF - Journal of Biophotonics
IS - 10
M1 - e202200100
ER -
