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- W2591676680 endingPage "1178623X1769434" @default.
- W2591676680 startingPage "1178623X1769434" @default.
- W2591676680 abstract "Metabolomics is a rapidly growing field with potential applications in various disciplines. In particular, metabolomics has received special attention in the discovery of biomarkers and diagnostics. This is largely due to the fact that metabolomics provides critical information related to the downstream products of many cellular and metabolic processes which could provide a snapshot of the health/disease status of a particular tissue or organ. Many of these cellular products eventually find their way to urine; hence, analysis of urine via metabolomics has the potential to yield useful diagnostic and prognostic information. Although there are a number of analytical platforms that can be used for this purpose, this review article will focus on nuclear magnetic resonance–based metabolomics. Furthermore, although there have been many studies addressing different diseases and metabolic disorders, the focus of this review article will be in the following specific applications: urinary tract infection, kidney transplant rejection, diabetes, some types of cancer, and inborn errors of metabolism. A number of methodological considerations that need to be taken into account for the development of a clinically useful optimal test are discussed briefly." @default.
- W2591676680 created "2017-03-16" @default.
- W2591676680 creator A5034603359 @default.
- W2591676680 creator A5037817807 @default.
- W2591676680 creator A5079970098 @default.
- W2591676680 date "2017-01-01" @default.
- W2591676680 modified "2023-10-10" @default.
- W2591676680 title "Diagnostic Applications of Nuclear Magnetic Resonance–Based Urinary Metabolomics" @default.
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- W2591676680 doi "https://doi.org/10.1177/1178623x17694346" @default.
- W2591676680 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5428226" @default.
- W2591676680 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28579794" @default.
- W2591676680 hasPublicationYear "2017" @default.