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Analysis and classification of 1H-NMR spectra by multifractal analysis

The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing...

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Autores principales: Kim, Jongphil, Woo, Hin Kyeol, Vimalajeewa, Dixon, Vidakovic, Brani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249796/
https://www.ncbi.nlm.nih.gov/pubmed/37289702
http://dx.doi.org/10.1371/journal.pone.0286205
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author Kim, Jongphil
Woo, Hin Kyeol
Vimalajeewa, Dixon
Vidakovic, Brani
author_facet Kim, Jongphil
Woo, Hin Kyeol
Vimalajeewa, Dixon
Vidakovic, Brani
author_sort Kim, Jongphil
collection PubMed
description The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing procedures, have been criticized as not being fully informative, as well as inappropriate for translation of methodology. Rather than focusing on particular biomarkers, our proposed methodology involves the multifractal analysis that measures the inhomogeneity of regularity of the proton nuclear magnetic resonance ((1)H-NMR) spectrum by wavelet-based multifractal spectrum. With two different statistical models (Model-I and Model-II), three different geometric features of the multifractal spectrum of each (1)H-NMR spectrum (spectral mode, left slope, and broadness) are employed to evaluate the effect of SAA and discriminate (1)H-NMR spectra associated with different treatments. The investigated effects of SAA include group effect (high and low doses of SAA), depletion/repletion effect, and time over data effect. The (1)H-NMR spectra analysis outcomes show that group effect is significant for both models. The hourly variation in time and depletion/repletion effects does not show noticeable differences for the three features in Model-I. However, these two effects are significant for the spectral mode feature in Model-II. The (1)H-NMR spectra of the SAA low groups exhibit highly regular patterns with more variability than that of the SAA high groups for both models. Moreover, the discriminatory analysis conducted using the support vector machine and the principal components analysis shows that the (1)H-NMR spectra of SAA high and low groups can be easily discriminatory for both models, while the spectra of depletion and repletion within these groups are discriminatory for Model-I and Model-II. Therefore, the study outcomes imply that the amount of SAA is important and that SAA intake affects mostly the hourly variation of the metabolic process and the difference between depletion and repletion each day. In conclusion, the proposed multifractal analysis of (1)H-NMR spectra provides a novel tool to investigate metabolic processes.
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spelling pubmed-102497962023-06-09 Analysis and classification of 1H-NMR spectra by multifractal analysis Kim, Jongphil Woo, Hin Kyeol Vimalajeewa, Dixon Vidakovic, Brani PLoS One Research Article The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing procedures, have been criticized as not being fully informative, as well as inappropriate for translation of methodology. Rather than focusing on particular biomarkers, our proposed methodology involves the multifractal analysis that measures the inhomogeneity of regularity of the proton nuclear magnetic resonance ((1)H-NMR) spectrum by wavelet-based multifractal spectrum. With two different statistical models (Model-I and Model-II), three different geometric features of the multifractal spectrum of each (1)H-NMR spectrum (spectral mode, left slope, and broadness) are employed to evaluate the effect of SAA and discriminate (1)H-NMR spectra associated with different treatments. The investigated effects of SAA include group effect (high and low doses of SAA), depletion/repletion effect, and time over data effect. The (1)H-NMR spectra analysis outcomes show that group effect is significant for both models. The hourly variation in time and depletion/repletion effects does not show noticeable differences for the three features in Model-I. However, these two effects are significant for the spectral mode feature in Model-II. The (1)H-NMR spectra of the SAA low groups exhibit highly regular patterns with more variability than that of the SAA high groups for both models. Moreover, the discriminatory analysis conducted using the support vector machine and the principal components analysis shows that the (1)H-NMR spectra of SAA high and low groups can be easily discriminatory for both models, while the spectra of depletion and repletion within these groups are discriminatory for Model-I and Model-II. Therefore, the study outcomes imply that the amount of SAA is important and that SAA intake affects mostly the hourly variation of the metabolic process and the difference between depletion and repletion each day. In conclusion, the proposed multifractal analysis of (1)H-NMR spectra provides a novel tool to investigate metabolic processes. Public Library of Science 2023-06-08 /pmc/articles/PMC10249796/ /pubmed/37289702 http://dx.doi.org/10.1371/journal.pone.0286205 Text en © 2023 Kim et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kim, Jongphil
Woo, Hin Kyeol
Vimalajeewa, Dixon
Vidakovic, Brani
Analysis and classification of 1H-NMR spectra by multifractal analysis
title Analysis and classification of 1H-NMR spectra by multifractal analysis
title_full Analysis and classification of 1H-NMR spectra by multifractal analysis
title_fullStr Analysis and classification of 1H-NMR spectra by multifractal analysis
title_full_unstemmed Analysis and classification of 1H-NMR spectra by multifractal analysis
title_short Analysis and classification of 1H-NMR spectra by multifractal analysis
title_sort analysis and classification of 1h-nmr spectra by multifractal analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249796/
https://www.ncbi.nlm.nih.gov/pubmed/37289702
http://dx.doi.org/10.1371/journal.pone.0286205
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