| Autor: |
Artem Tabarov, Vladimir Vitkin, Olga Andreeva, Arina Shemanaeva, Evgeniy Popov, Alexander Dobroslavin, Valeria Kurikova, Olga Kuznetsova, Konstantin Grigorenko, Ivan Tzibizov, Anton Kovalev, Vitaliy Savchenko, Alyona Zheltuhina, Andrey Gorshkov, Daria Danilenko |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Biosensors, Vol 12, Iss 12, p 1065 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2079-6374 |
| DOI: |
10.3390/bios12121065 |
| Popis: |
We demonstrate the possibility of applying surface-enhanced Raman spectroscopy (SERS) combined with machine learning technology to detect and differentiate influenza type A and B viruses in a buffer environment. The SERS spectra of the influenza viruses do not possess specific peaks that allow for their straight classification and detection. Machine learning technologies (particularly, the support vector machine method) enabled the differentiation of samples containing influenza A and B viruses using SERS with an accuracy of 93% at a concentration of 200 μg/mL. The minimum detectable concentration of the virus in the sample using the proposed approach was ~0.05 μg/mL of protein (according to the Lowry protein assay), and the detection accuracy of a sample with this pathogen concentration was 84%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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