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Photonics enabled intelligence system to identify SARS-CoV 2 mutations
ABSTRACT: The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effe...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050350/ https://www.ncbi.nlm.nih.gov/pubmed/35484414 http://dx.doi.org/10.1007/s00253-022-11930-1 |
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author | Taha, Bakr Ahmed Al-Jubouri, Qussay Al Mashhadany, Yousif Zan, Mohd Saiful Dzulkefly Bin Bakar, Ahmad Ashrif A. Fadhel, Mahmoud Muhanad Arsad, Norhana |
author_facet | Taha, Bakr Ahmed Al-Jubouri, Qussay Al Mashhadany, Yousif Zan, Mohd Saiful Dzulkefly Bin Bakar, Ahmad Ashrif A. Fadhel, Mahmoud Muhanad Arsad, Norhana |
author_sort | Taha, Bakr Ahmed |
collection | PubMed |
description | ABSTRACT: The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effect of the SARS-CoV-2 mutation, on the other hand, has been characterized by worrying variations that modify viral characteristics in response to the changing resistance profile of the human population. The repeated transmission of virus mutation indicates that epidemics are likely to occur. Therefore, an early identification system of ongoing mutations of SARS-CoV-2 will provide essential insights for planning and avoiding future outbreaks. This article discussed the following highlights: First, comparing the omicron mutation with other variants; second, analysis and evaluation of the spread rate of the SARS-CoV 2 variations in the countries; third, identification of mutation areas in spike protein; and fourth, it discussed the photonics approaches enabled with artificial intelligence. Therefore, our goal is to identify the SARS-CoV 2 virus directly without the need for sample preparation or molecular amplification procedures. Furthermore, by connecting through the optical network, the COVID-19 test becomes a component of the Internet of healthcare things to improve precision, service efficiency, and flexibility and provide greater availability for the evaluation of the general population. KEY POINTS: • A proposed framework of photonics based on AI for identifying and sorting SARS-CoV 2 mutations. • Comparative scatter rates Omicron variant and other SARS-CoV 2 variations per country. • Evaluating mutation areas in spike protein and AI enabled by photonic technologies for SARS-CoV 2 virus detection. |
format | Online Article Text |
id | pubmed-9050350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-90503502022-04-29 Photonics enabled intelligence system to identify SARS-CoV 2 mutations Taha, Bakr Ahmed Al-Jubouri, Qussay Al Mashhadany, Yousif Zan, Mohd Saiful Dzulkefly Bin Bakar, Ahmad Ashrif A. Fadhel, Mahmoud Muhanad Arsad, Norhana Appl Microbiol Biotechnol Mini-Review ABSTRACT: The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effect of the SARS-CoV-2 mutation, on the other hand, has been characterized by worrying variations that modify viral characteristics in response to the changing resistance profile of the human population. The repeated transmission of virus mutation indicates that epidemics are likely to occur. Therefore, an early identification system of ongoing mutations of SARS-CoV-2 will provide essential insights for planning and avoiding future outbreaks. This article discussed the following highlights: First, comparing the omicron mutation with other variants; second, analysis and evaluation of the spread rate of the SARS-CoV 2 variations in the countries; third, identification of mutation areas in spike protein; and fourth, it discussed the photonics approaches enabled with artificial intelligence. Therefore, our goal is to identify the SARS-CoV 2 virus directly without the need for sample preparation or molecular amplification procedures. Furthermore, by connecting through the optical network, the COVID-19 test becomes a component of the Internet of healthcare things to improve precision, service efficiency, and flexibility and provide greater availability for the evaluation of the general population. KEY POINTS: • A proposed framework of photonics based on AI for identifying and sorting SARS-CoV 2 mutations. • Comparative scatter rates Omicron variant and other SARS-CoV 2 variations per country. • Evaluating mutation areas in spike protein and AI enabled by photonic technologies for SARS-CoV 2 virus detection. Springer Berlin Heidelberg 2022-04-29 2022 /pmc/articles/PMC9050350/ /pubmed/35484414 http://dx.doi.org/10.1007/s00253-022-11930-1 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Mini-Review Taha, Bakr Ahmed Al-Jubouri, Qussay Al Mashhadany, Yousif Zan, Mohd Saiful Dzulkefly Bin Bakar, Ahmad Ashrif A. Fadhel, Mahmoud Muhanad Arsad, Norhana Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title | Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title_full | Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title_fullStr | Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title_full_unstemmed | Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title_short | Photonics enabled intelligence system to identify SARS-CoV 2 mutations |
title_sort | photonics enabled intelligence system to identify sars-cov 2 mutations |
topic | Mini-Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050350/ https://www.ncbi.nlm.nih.gov/pubmed/35484414 http://dx.doi.org/10.1007/s00253-022-11930-1 |
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