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Application of ultraperformance liquid chromatography/mass spectrometry-based metabonomic techniques to analyze the joint toxic action of long-term low-level exposure to a mixture of organophosphate pesticides on rat urine profile. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Discriminant independent component analysis. Galaxy-M: A galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data. M., Liu, H., Sharma-Oates, A., & Viant, M. Analytical and Bioanalytical Chemistry, 390(1), 419–427. Fruit juice authentication by 1H NMR spectroscopy in combination with different chemometrics tools. Evolving window zone selection method followed by independent component analysis as useful chemometric tools to discriminate between grapefruit juice, orange juice and blends.
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Proceedings of the National Academy of Sciences of the United States of America, 108(34), 14015–14020. Detection and formation scenario of citric acid, pyruvic acid, and other possible metabolism precursors in carbonaceous meteorites. High-order contrasts for independent component analysis. Metabolomics tools for describing complex pesticide exposure in pregnant women in Brittany (France).
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In Proceedings of NOLTA, 95, 49–53.īonvallot, N., Tremblay-Franco, M., Chevrier, C., Canlet, C., Warembourg, C., Cravedi, J. Maximum likelihood source separation by the expectation-maximization technique: Deterministic and stochastic implementation. As well the improvement of high throughput metabolomic studies was provided by combining DI–HRMS with this new chemometric tool.īallabio, D., & Consonni, V. This study demonstrated the efficiency of IC–DA to discriminate the different exposure groups. Targeted correlation analysis was used for the detection of ions associated with the most discriminant variables, consolidating their identity assignment. Putative annotation of these variables was performed using metabolomic databases. IC–DA results enabled a good detection of discriminant variables and a clear discrimination of control samples and exposure classes whereas a less striking discrimination was obtained with PLS–DA. For both the IC–DA and PLS–DA methods, a validation was performed based on a permutation test. Results obtained from this method were compared to those obtained by the conventional Partial least squares–discriminant analysis (PLS–DA). Spectral data were processed using the developed IC–DA procedure. Metabolomic fingerprints were obtained by direct introduction high resolution mass spectrometry (DI-HRMS) analysis of urine samples of subjects that had been professionally exposed to pesticides. Independent component–discriminant analysis (IC–DA), for processing DIMS data. The objective of this study is to develop a computational procedure, based on an innovative chemometric method, i.e. However, processing DIMS data is still very challenging due to the large number of samples and the intrinsic complexity of the mass spectra. The direct introduction mass spectrometry (DIMS) approach appears to be very attractive to achieve this goal. To perform large scale metabolomic analyses, high throughput approaches are required.