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Clinical Metabolomics

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Cover of 'Clinical Metabolomics'

Table of Contents

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    Book Overview
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    Chapter 1 Metabolomics as a Tool to Understand Pathophysiological Processes
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    Chapter 2 Metabolomics in Immunology Research
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    Chapter 3 LC-MS-Based Metabolomics of Biofluids Using All-Ion Fragmentation (AIF) Acquisition
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    Chapter 4 Lipid Mediator Metabolomics Via LC-MS/MS Profiling and Analysis
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    Chapter 5 UHPSFC/ESI-MS Analysis of Lipids
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    Chapter 6 LC-MS/MS Analysis of Lipid Oxidation Products in Blood and Tissue Samples
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    Chapter 7 Serum Testosterone by Liquid Chromatography Tandem Mass Spectrometry for Routine Clinical Diagnostics
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    Chapter 8 LC-MS/MS Analysis of Bile Acids
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    Chapter 9 LC-MS/MS Analysis of Triglycerides in Blood-Derived Samples
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    Chapter 10 LC-MS/MS Analysis of the Epoxides and Diols Derived from the Endocannabinoid Arachidonoyl Ethanolamide
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    Chapter 11 Sphingolipid Analysis in Clinical Research
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    Chapter 12 Shotgun Lipidomics Approach for Clinical Samples
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    Chapter 13 Establishing and Performing Targeted Multi-residue Analysis for Lipid Mediators and Fatty Acids in Small Clinical Plasma Samples
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    Chapter 14 Chemical Isotope Labeling LC-MS for Human Blood Metabolome Analysis
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    Chapter 15 Direct Infusion-Tandem Mass Spectrometry (DI-MS/MS) Analysis of Complex Lipids in Human Plasma and Serum Using the Lipidyzer™ Platform
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    Chapter 16 Exploratory GC/MS-Based Metabolomics of Body Fluids
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    Chapter 17 GC-MS Analysis of Short-Chain Fatty Acids in Feces, Cecum Content, and Blood Samples
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    Chapter 18 GC-MS Analysis of Medium- and Long-Chain Fatty Acids in Blood Samples
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    Chapter 19 Analysis of Oxysterols
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    Chapter 20 Analysis of Metabolites from the Tricarboxylic Acid Cycle for Yeast and Bacteria Samples Using Gas Chromatography Mass Spectrometry
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    Chapter 21 GC-MS Analysis of Lipid Oxidation Products in Blood, Urine, and Tissue Samples
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    Chapter 22 Metabolic Profiling of Urine by Capillary Electrophoresis-Mass Spectrometry Using Non-covalently Coated Capillaries
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    Chapter 23 CE-MS for the Analysis of Amino Acids
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    Chapter 24 NMR Analysis of Fecal Samples
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    Chapter 25 Quantitative Analysis of Central Energy Metabolism in Cell Culture Samples
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    Chapter 26 Mass Spectrometry Imaging of Metabolites
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    Chapter 27 Quality-Assured Biobanking: The Leiden University Medical Center Model
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    Chapter 28 Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies
Attention for Chapter 18: GC-MS Analysis of Medium- and Long-Chain Fatty Acids in Blood Samples
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Chapter title
GC-MS Analysis of Medium- and Long-Chain Fatty Acids in Blood Samples
Chapter number 18
Book title
Clinical Metabolomics
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7592-1_18
Pubmed ID
Book ISBNs
978-1-4939-7591-4, 978-1-4939-7592-1
Authors

Lisa R. Hoving, Marieke Heijink, Vanessa van Harmelen, Ko Willems van Dijk, Martin Giera

Abstract

Our body contains a wide variety of fatty acids that differ in chain length, the degree of unsaturation, and location of the double bonds. As the various fatty acids play distinct roles in health and disease, methods that can specifically determine the fatty acid profile are needed for fundamental and clinical studies. Here we describe a method for the separation and quantification of fatty acids ranging from 8 to 24 carbon chain lengths in blood samples using gas chromatography-mass spectrometry following derivatization using pentafluorobenzyl bromide. This method quantitatively monitors fatty acid composition in a manner that satisfies the requirements for comprehensiveness, sensitivity, and accuracy.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Student > Master 3 14%
Student > Postgraduate 2 10%
Student > Bachelor 2 10%
Researcher 2 10%
Other 2 10%
Unknown 5 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 19%
Chemistry 4 19%
Immunology and Microbiology 3 14%
Agricultural and Biological Sciences 2 10%
Neuroscience 2 10%
Other 2 10%
Unknown 4 19%