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10.1007/s10103-021-03488-7

http://scihub22266oqcxt.onion/10.1007/s10103-021-03488-7
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suck abstract from ncbi


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pmid35028768      Lasers+Med+Sci 2022 ; 37 (4): 2217-2226
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  • Diagnosing COVID-19 in human serum using Raman spectroscopy #MMPMID35028768
  • Goulart ACC; Silveira L Jr; Carvalho HC; Dorta CB; Pacheco MTT; Zangaro RA
  • Lasers Med Sci 2022[Jun]; 37 (4): 2217-2226 PMID35028768show ga
  • This study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC2, PC4, PC5, and PC6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free, and costless technique for diagnosing COVID-19 infection.
  • |*COVID-19/diagnosis[MESH]
  • |*Spectrum Analysis, Raman/methods[MESH]
  • |Amino Acids[MESH]
  • |Discriminant Analysis[MESH]
  • |Humans[MESH]
  • |Principal Component Analysis[MESH]


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