Identification of metabolic kinetic patterns in different brain regions using metabolomics methods coupled with various discriminant approaches

Zheng, D, Li, Z, Li, S, Li, X, Kamal, GM, Liu, C, Manyande, Anne ORCID: https://orcid.org/0000-0002-8257-0722, Xu, F, Bao, Q and Wang, J (2021) Identification of metabolic kinetic patterns in different brain regions using metabolomics methods coupled with various discriminant approaches. Journal of Pharmaceutical and Biomedical Analysis, 198. p. 114027. ISSN 0731-7085

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Abstract

Metabolomics is widely used as a powerful technique for identifying metabolic patterns and functions of organs and biological systems. Normally, there are multiple groups/targets involved in data processed by discriminant analysis. This is more common in cerebral studies, as there are always several brain regions involved in neuronal studies or brain metabolic dysfunctions. Furthermore, neuronal activity is highly correlated with cerebral energy metabolism, such as oxidation of glucose, especially for glutamatergic(excitatory) and GABAergic (inhibitory) neuronal activities. Thus, regional cerebral energy metabolism recognition is essential for understanding brain functions. In the current study, ten different brain regions were considered for discrimination analysis. The metabolic kinetics were investigated with13C enrichments in metabolic products of glucose and measured using the nuclear magnetic spectroscopic method. Multiple discriminative methods were used to construct classification models in order to screen out the best method. After comparing all the applied discriminatory analysis methods, the boost-decision tree method was found to be the best method for classification and every cerebral region exhibited its own metabolic pattern. Finally, the differences in metabolic kinetics among these brain regions were analyzed. We, therefore, concluded that the current technology could also be utilized in other multi-class metabolomics studies and special metabolic kinetic patterns could provide useful information for brain function studies.

Item Type: Article
Uncontrolled Keywords: Metabolomics, Metabolic kinetics, POCE, Brain, Decision tree
Subjects: Medicine and health > Clinical medicine > Therapeutics
Medicine and health > Clinical medicine
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Depositing User: Anne Manyande
Date Deposited: 20 Mar 2021 14:20
Last Modified: 23 Mar 2021 13:33
URI: http://repository.uwl.ac.uk/id/eprint/7762

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