Literature DB >> 31887681

Study on glycoprotein terahertz time-domain spectroscopy based on composite multiscale entropy feature extraction method.

Pingjie Huang1, Zhangwei Huang2, Xiaodong Lu2, Yuqi Cao2, Jie Yu2, Dibo Hou2, Guangxin Zhang3.   

Abstract

Tumor genesis is accompanied by glycosylation of related proteins. Glycoprotein is usually regarded as a tumor marker since glycoproteins are consumed remarkably more by the cancer cells than the normal ones. In this paper, the terahertz time-domain attenuated total reflection (ATR) technique is applied to inspect the glycoprotein solution from a concentration gradient of 0.2 mg/ml to 50 mg/ml. A significant nonlinear relationship between the absorption coefficient and the concentrations has been discovered. The influence of the dynamical hydration shell around glycoprotein molecules on the absorption coefficient is discussed and the phenomenon is explained by the concepts of THz excess and THz defect. In order to identify glycoproteins, features are obtained by composite multiscale entropy (CMSE) method and clustered by the K-means algorithm. The results indicate that features extracted by the CMSE method are better than the Principal Component Analysis (PCA) method in both specificity and sensitivity of recognition. Meanwhile, the absorption coefficient and dielectric loss angle tangent are more suitable for qualitative identification. Research shows that the CMSE method has important directive significance for analyzing glycoprotein terahertz spectroscopy. And it has the potential for glycoprotein related tumor markers identification using terahertz technology in medical applications.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Absorption coefficient; Composite multiscale entropy (CMSE); Dielectric loss tangent; Glycoprotein; Terahertz time-domain attenuated total reflection spectroscopy; Tumor marker identification

Mesh:

Substances:

Year:  2019        PMID: 31887681     DOI: 10.1016/j.saa.2019.117948

Source DB:  PubMed          Journal:  Spectrochim Acta A Mol Biomol Spectrosc        ISSN: 1386-1425            Impact factor:   4.098


  2 in total

1.  Children's Neurological Status Epilepticus and Poor Prognostic Factors through Electroencephalogram Image under Composite Domain Analysis Algorithm.

Authors:  Runhan Zhang; Chao Gao; Junting Liu; Manting Zhao; Yongli Wu
Journal:  J Healthc Eng       Date:  2021-11-25       Impact factor: 2.682

2.  Electroencephalogram Image under Complex Domain Analysis Algorithm to Analyze Neurological Status Epilepticus and Poor Prognostic Factors of Children.

Authors:  Jiyong Gao; Na Dai; Zhigang Liu; Dehong Chen; Junqing Zhen; Jin Wang
Journal:  J Healthc Eng       Date:  2021-12-15       Impact factor: 2.682

  2 in total

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