Possibilities for decomposing Raman spectra of amino acids mixture by Multivariate Curve Resolution (MCR) analysis

Матвеева, И. А.; Myakinin, Oleg O.; Khristoforova, Yulia А.; Bratchenko, Ivan А.; Тупикова, Е. Н.; Zakharov, Valery P.

doi:10.1117/12.2581559

Cited by 4 publications

(10 citation statements)

References 6 publications

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“…As in our previous study [17], the concentrations of leucine, serine, cysteine, tyrosine, tryptophan are restored with lower correlation coefficients because random noise overlaps their spectra (which have a low ratio between Raman peaks and background fluorescence). 5 Correlation coefficients between obtained and true amino acid concentration values for the case of the noise added to both basis spectra (SNR = 5 for all the cases) and mixture spectra.…”

Section: Resultssupporting

confidence: 55%

“…The results of our previous study [17] show that the concentrations of amino acids are restored with lower correlation coefficients if their Raman spectra have no intense peaks. That is, the ratio between Raman peaks and background, apparently caused by fluorescence, is not high (compare the Raman spectra of cysteine, tyrosine, tryptophan with weak background fluorescence and the Raman spectra of glutamic acid, methionine, phenylalanine with strong background fluorescence in Fig.…”

Section: Resultsmentioning

confidence: 82%

“…In this study, we investigated the following combinations of a mixture and basis spectra: no noise in mixture spectra, no noise in basis spectra; no noise in mixture spectra, SNR = 10 for basis spectra; no noise in mixture spectra, SNR = 5 for basis spectra; no noise in mixture spectra, SNR = 1 for basis spectra; -SNR = 10 for mixture spectra, no noise in basis spectra [17];…”

Section: Resultsmentioning

confidence: 99%

“…-SNR = 5 for mixture spectra, no noise in basis spectra [17]; -SNR = 1 for mixture spectra, no noise in basis spectra [17]; -SNR = 5 for mixture spectra, SNR = 5 for basis spectra; -SNR = 4 for mixture spectra, SNR = 5 for basis spectra; -SNR = 3 for mixture spectra, SNR = 5 for basis spectra;…”

Section: Resultsmentioning

confidence: 99%

“…Table 3 shows the correlation coefficients for the case when the basis spectra are noisy with a different SNR, and the mixtures have no noise. For comparison, Table 4 shows the results that we obtained in the previous study, when we investigated the effect of noise in the mixture Raman spectra on the quality of unmixing spectra [17].…”

Section: Resultsmentioning

confidence: 99%

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The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis

Матвеева

Bratchenko

Myakinin

et al. 2021

J-BPE

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Changes in the concentration of free amino acids in biological tissues is a sign of impaired protein metabolism in patients with cancer. Recently, Raman spectroscopy has been used for early diagnostics of oncological diseases. The concentrations of individual components of biological tissue (for instance, the concentrations of amino acids) can be obtained by decomposing the tissue Raman spectrum. This study was designed to evaluate the effect of noise in the Raman spectra of individual amino acids on the result of the decomposition of the spectra of an amino acid mixture. As a decomposition method, we used Multivariate Curve Resolution-Alternating Least Squares (MCR–ALS) analysis and investigate experimental Raman spectra of amino acids and mathematically simulated Raman spectra of amino acid mixtures. Noise with different signal-to-noise ratios (SNR) was artificially added to both the experimental spectra of pure amino acids and the spectra of the mixtures. Concentration values for each amino acid obtained as a result of applying the MCR–ALS analysis have been compared with the corresponding true values and the correlation coefficients have been calculated. The results show a less pronounced negative effect of noise in the case when the spectra of pure amino acids (which were used as a basis for the MCR–ALS analysis) are noisy, and a more pronounced negative effect when the spectrum of the mixture is noisy. The accuracy of reconstruction of an amino acid is also negatively affected by strong background fluorescence in the amino acid spectrum. Moreover, the results indicate that using the basis spectra with a high SNR (SNR = 5) makes it possible to successfully estimate the amino acid concentrations in a mixture even when the Raman spectrum of the mixture is noisy and has a low SNR (SNR < 5).

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Section: Resultssupporting

confidence: 55%

Section: Resultsmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis

Матвеева

Bratchenko

Myakinin

et al. 2021

J-BPE

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Raman identification of single cell component and FMS‐like tyrosine kinase 3‐internal tandem duplications subtype for clinical acute myeloid leukemia

Wang

Chi

et al. 2023

J Raman Spectroscopy

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Acute myeloid leukemia (AML) is a malignant clonal blood disease of hematopoietic stem cells with poor prognosis. Traditional diagnosis of AML depends on the morphology, immunology, cytogenetics, and molecular biology (MICM) classification. As a rapid, label-free and non-destructive detection method, Raman spectroscopy can characterize the molecular information in the biochemical process at the molecular level through peak position, intensity and other information. In this paper, we collected leukemic blast cells from 19 AML patients. Firstly, it was proved that with the help of multivariate analysis methods such as principal component analysis-linear discriminant analysis (PCA-LDA) and multivariate curve resolution-alternating least squares (MCR-ALS), Raman spectroscopy could effectively distinguish AML cells from normal leukocytes, and the accuracy rate was up to 96.71%. The results showed that compared with normal leukocytes, multiple components of information decomposed by the AML spectrum represented abnormal alterations in proteins, nucleic acids, lipids and carbohydrates in leukemia cells. Secondly, the same procedure was used to further detect different types of AML and found that Raman spectroscopy could distinguish AML cells with FMS-like tyrosine kinase 3-Internal Tandem Duplications (FLT3-ITD) mutations or not, and there were differences in spectral characteristics corresponding to nucleic acids and proteins (amino acids). The above results revealed that Raman spectroscopy has great potential for clinical diagnosis and mechanistic study of AML.

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Analysis of Raman Spectra of Blood Serum by Multivariate Curve Resolution Method

Pimenova,

Bratchenko,

Matveeva

2024

2024 X International Conference on Information Technology and Nanotechnology (ITNT)

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Possibilities for decomposing Raman spectra of amino acids mixture by Multivariate Curve Resolution (MCR) analysis

Cited by 4 publications

References 6 publications

The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis

The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis

Raman identification of single cell component and FMS‐like tyrosine kinase 3‐internal tandem duplications subtype for clinical acute myeloid leukemia

Analysis of Raman Spectra of Blood Serum by Multivariate Curve Resolution Method

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