Document Detail


Comparison of performance of partial least squares regression, secured principal component regression, and modified secured principal component regression for determination of human serum albumin, gamma-globulin and glucose in buffer solutions and in vivo blood glucose quantification by near-infrared spectroscopy.
MedLine Citation:
PMID:  17171339     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The performances of three multivariate analysis methods--partial least squares (PLS) regression, secured principal component regression (sPCR) and modified secured principal component regression (msPCR)--are compared and tested for the determination of human serum albumin (HSA), gamma-globulin, and glucose in phosphate buffer solutions and blood glucose quantification by near-infrared (NIR) spectroscopy. Results from the application of PLS, sPCR and msPCR are presented, showing that the three methods can determine the concentrations of HSA, gamma-globulin and glucose in phosphate buffer solutions almost equally well provided that the prediction samples contain the same spectral information as the calibration samples. On the other hand, when some potential spectral features appear in new measurements, sPCR and msPCR outperform PLS significantly. The reason for this is that such spectral features are not included during calibration, which leads to a degradation in PLS prediction performance, while sPCR and msPCR can improve their predictions for the concentrations of the analytes by removing the uncalibrated features from the original spectra. This point is demonstrated by successfully applying sPCR and msPCR to in vivo blood glucose measurements. This work therefore shows that sPCR and msPCR may provide possible alternatives to PLS in cases where some uncalibrated spectral features are present in measurements used for concentration prediction.
Authors:
Bo-Yan Li; Sumaporn Kasemsumran; Yun Hu; Yi-Zeng Liang; Yukihiro Ozaki
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2006-12-15
Journal Detail:
Title:  Analytical and bioanalytical chemistry     Volume:  387     ISSN:  1618-2642     ISO Abbreviation:  Anal Bioanal Chem     Publication Date:  2007 Jan 
Date Detail:
Created Date:  2007-01-11     Completed Date:  2007-03-19     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101134327     Medline TA:  Anal Bioanal Chem     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  603-11     Citation Subset:  IM    
Affiliation:
Department of Chemistry and Research Center for Near-Infrared Spectroscopy, School of Science and Technology, Kwansei-Gakuin University, 2-1 Gakuen, Sanda, 669-1337, Japan.
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MeSH Terms
Descriptor/Qualifier:
Blood Glucose / analysis*
Buffers
Calibration
Glucose / analysis*
Humans
Least-Squares Analysis
Multivariate Analysis*
Serum Albumin / analysis*
Spectroscopy, Near-Infrared / methods*
gamma-Globulins / analysis*
Chemical
Reg. No./Substance:
0/Blood Glucose; 0/Buffers; 0/Serum Albumin; 0/gamma-Globulins; 50-99-7/Glucose

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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