Document Detail


Spectroscopic correlation analysis of NMR-based metabonomics in exercise science.
MedLine Citation:
PMID:  19786178     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a (1)H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.
Authors:
Gemma M Kirwan; Vernon G Coffey; Julie O Niere; John A Hawley; Michael J Adams
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-07-08
Journal Detail:
Title:  Analytica chimica acta     Volume:  652     ISSN:  1873-4324     ISO Abbreviation:  Anal. Chim. Acta     Publication Date:  2009 Oct 
Date Detail:
Created Date:  2009-09-29     Completed Date:  2009-12-15     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0370534     Medline TA:  Anal Chim Acta     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  173-9     Citation Subset:  IM    
Affiliation:
Applied Chemistry, School of Applied Sciences, RMIT University, Melbourne, Vic., Australia.
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MeSH Terms
Descriptor/Qualifier:
Automatic Data Processing
Blood Chemical Analysis
Exercise*
Humans
Metabolomics / methods*
Nuclear Magnetic Resonance, Biomolecular / methods*

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