Journal article
Selectivity for glucose, glucose-6-phosphate, and pyruvate in ternary mixtures from the multivariate analysis of near-infrared spectra
Analytical and bioanalytical chemistry, Vol.393(2), pp.669-677
01/2009
DOI: 10.1007/s00216-008-2475-0
PMID: 19009286
Abstract
Near-infrared spectroscopy offers the potential for direct in situ analysis in complex biological systems. Chemical selectivity is a critical issue for such measurements given the extent of spectral overlap of overtone and combination spectra. In this work, the chemical basis of selectivity is investigated for a set of multivariate calibration models designed to quantify glucose, glucose-6-phosphate, and pyruvate independently in ternary mixtures. Near-infrared spectra are collected over the combination region (4,000-5,000 cm(-1)) for a set of 60 standard solutions maintained at 37 degrees C. These standard solutions are composed of randomized concentrations (0.5-30 mM) of glucose, glucose-6-phosphate, and pyruvate. Individual calibration models are constructed for each solute by using the partial least-squares (PLS) algorithm with optimized spectral range and number of latent variables. The resulting standard errors are 0.90, 0.72, and 0.32 mM for glucose, glucose-6-phosphate, and pyruvate, respectively. A pure component selectivity analysis (PCSA) demonstrates selectivity for each solute in these ternary samples. The concentration of each solute is also predicted for each sample by using a set of net analyte signal (NAS) calibration models. A comparison of the PLS and NAS calibration vectors demonstrates the chemical basis of selectivity for these multivariate methods. Selectivity of each PLS and NAS calibration model originates from the unique spectral features associated with the targeted analyte. Overall, selectivity is demonstrated for each solute with an order of sensitivity of pyruvate > glucose-6-phosphate > glucose.
Details
- Title: Subtitle
- Selectivity for glucose, glucose-6-phosphate, and pyruvate in ternary mixtures from the multivariate analysis of near-infrared spectra
- Creators
- Lingzhi Liu - Department of Chemistry and Optical Science Technology Center, University of Iowa, Iowa City, IA 52242, USA. lliu@coldstreamlabs.comMark A Arnold
- Resource Type
- Journal article
- Publication Details
- Analytical and bioanalytical chemistry, Vol.393(2), pp.669-677
- DOI
- 10.1007/s00216-008-2475-0
- PMID
- 19009286
- ISSN
- 1618-2642
- eISSN
- 1618-2650
- Grant note
- DK-60657 / NIDDK NIH HHS
- Language
- English
- Date published
- 01/2009
- Academic Unit
- Center for Biocatalysis and Bioprocessing; Fraternal Order of Eagles Diabetes Research Center; Chemistry
- Record Identifier
- 9984216613302771
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