COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections

Abstract The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able t...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	C. Carlomagno, D. Bertazioli, A. Gualerzi, S. Picciolini, P. I. Banfi, A. Lax, E. Messina, J. Navarro, L. Bianchi, A. Caronni, F. Marenco, S. Monteleone, C. Arienti, M. Bedoni
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/edeb1e804d3a438fb72f366b4dc48322
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:edeb1e804d3a438fb72f366b4dc48322
record_format	dspace
spelling	oai:doaj.org-article:edeb1e804d3a438fb72f366b4dc483222021-12-02T15:54:06ZCOVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections10.1038/s41598-021-84565-32045-2322https://doaj.org/article/edeb1e804d3a438fb72f366b4dc483222021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84565-3https://doaj.org/toc/2045-2322Abstract The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89–92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.C. CarlomagnoD. BertazioliA. GualerziS. PiccioliniP. I. BanfiA. LaxE. MessinaJ. NavarroL. BianchiA. CaronniF. MarencoS. MonteleoneC. ArientiM. BedoniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q C. Carlomagno D. Bertazioli A. Gualerzi S. Picciolini P. I. Banfi A. Lax E. Messina J. Navarro L. Bianchi A. Caronni F. Marenco S. Monteleone C. Arienti M. Bedoni COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
description	Abstract The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89–92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.
format	article
author	C. Carlomagno D. Bertazioli A. Gualerzi S. Picciolini P. I. Banfi A. Lax E. Messina J. Navarro L. Bianchi A. Caronni F. Marenco S. Monteleone C. Arienti M. Bedoni
author_facet	C. Carlomagno D. Bertazioli A. Gualerzi S. Picciolini P. I. Banfi A. Lax E. Messina J. Navarro L. Bianchi A. Caronni F. Marenco S. Monteleone C. Arienti M. Bedoni
author_sort	C. Carlomagno
title	COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
title_short	COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
title_full	COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
title_fullStr	COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
title_full_unstemmed	COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections
title_sort	covid-19 salivary raman fingerprint: innovative approach for the detection of current and past sars-cov-2 infections
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/edeb1e804d3a438fb72f366b4dc48322
work_keys_str_mv	AT ccarlomagno covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT dbertazioli covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT agualerzi covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT spicciolini covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT pibanfi covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT alax covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT emessina covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT jnavarro covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT lbianchi covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT acaronni covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT fmarenco covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT smonteleone covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT carienti covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections AT mbedoni covid19salivaryramanfingerprintinnovativeapproachforthedetectionofcurrentandpastsarscov2infections
_version_	1718385486200832000

COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections

Ejemplares similares