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Enhanced multivariate analysis by correlation scaling and fusion of LC/MS and 1H-NMR data
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
2007 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 85, no 2, 179-185 p.Article in journal (Refereed) Published
Abstract [en]

A method to enhance the multivariate data interpretation of, for instance, metabolic profiles is presented. This was done by correlation scaling of 1H NMR data by the time pattern of drug metabolite peaks identified by LC/MS, followed by parallel factor analysis (PARAFAC). The variables responsible for the discrimination between the dosed and control rats in this model were then eliminated in both data sets. Next, an additional PARAFAC analysis was performed with both LC/MS and 1H NMR data, fused by outer product analysis (OPA), to obtain sufficient class separation. The loadings from this second PARAFAC analysis showed new peaks discriminating between the classes. The time trajectories of these peaks did not agree with the drug metabolites and were detected as possible candidates for markers. These data analyses were also compared with the PARAFAC analysis of raw data, which showed very much the same loading peaks as for the correlation-scaled data, although the intensities differed. Elimination of the variables correlated with the drug metabolites was therefore necessary to be able to select the peaks which were not drug metabolites and which discriminated between the classes.1

Place, publisher, year, edition, pages
Elsevier B.V , 2007. Vol. 85, no 2, 179-185 p.
Keyword [en]
Data correlation; Correlation scaling; Data fusion; Outer product analysis; PARAFAC analysis; PLS
National Category
Analytical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-24515DOI: doi:10.1016/j.chemolab.2006.06.012ISI: 000245073200004OAI: oai:DiVA.org:su-24515DiVA: diva2:197687
Note
Part of urn:nbn:se:su:diva-712Available from: 2005-10-28 Created: 2005-10-28 Last updated: 2017-12-13Bibliographically approved
In thesis
1. Processing and analysis of NMR data: Impurity determination and metabolic profiling
Open this publication in new window or tab >>Processing and analysis of NMR data: Impurity determination and metabolic profiling
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis describes the use of nuclear magnetic resonance (NMR) spectrometry as an analytical tool. The theory of NMR spectroscopy in general and quantitative NMR spectrometry (qNMR) in particular is described and the instrumental properties and parameter setups for qNMR measurements are discussed. Examples of qNMR are presented by impurity determination of pharmaceutical compounds and analysis of urine samples from rats fed with either water or a drug (metabolic profiling). The instrumental parameter setup of qNMR and traditional data pre-treatments are examined. Spectral smoothing by convolution with a triangular function, which is an unusual application in this context, was shown to be successful regarding the sensitivity and robustness of the method in paper II. In addition, papers III and IV comprise the field of peak alignment, especially designed for 1H-NMR spectra of urine samples. This is an important preprocessing tool when multivariate analysis is to be applied. A novel peak alignment method was developed and compared to the traditional bucketing approach and a conceptually different alignment method.

Univariate, multivariate, linear and nonlinear data analyses were applied to qNMR data. In papers I–II, calibration models were created to examine the potential of qNMR for these applications. The data analysis in papers III–VI was mainly explorative. The potential of data fusion and data correlation was examined in order to increase the possibilities of analysing the highly complex samples from metabolic profiling (papers V–VI). Data from LC/MS analysis of the same samples were used with the 1H-NMR data in different ways. Correlation analyses between the 1H-NMR data and the drug metabolites identified from the LC/MS data were also performed. In this process, data fusion proved to be a valuable tool.

Place, publisher, year, edition, pages
Stockholm: Institutionen för analytisk kemi, 2005. 95 p.
Keyword
quantitative nuclear magnetic resonance spectrometry, qNMR, multivariate analysis, peak alignment, data fusion
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:su:diva-712 (URN)91-7155-139-5 (ISBN)
Public defence
2005-12-01, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 12 A, Stockholm, 13:00
Opponent
Supervisors
Available from: 2005-10-28 Created: 2005-10-28Bibliographically approved

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