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Clinical Metabolomics

Overview of attention for book
Cover of 'Clinical Metabolomics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    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 11: Sphingolipid Analysis in Clinical Research
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Chapter title
Sphingolipid Analysis in Clinical Research
Chapter number 11
Book title
Clinical Metabolomics
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7592-1_11
Pubmed ID
Book ISBNs
978-1-4939-7591-4, 978-1-4939-7592-1
Authors

Bo Burla, Sneha Muralidharan, Markus R. Wenk, Federico Torta

Abstract

Sphingolipids are the most diverse class of lipids due to the numerous variations in their structural components. This diversity is also reflected in their extremely different functions. Sphingolipids are not only constituents of cell membranes but have also emerged as key signaling molecules involved in a variety of cellular functions, such as cell growth and differentiation, proliferation, and apoptotic cell death. Lipidomic analyses in clinical research have identified pathways and products of sphingolipid metabolism that are altered in several human pathologies. In this article, we describe how to properly design a lipidomic experiment in clinical research, how to handle plasma and serum samples for this purpose, and how to measure sphingolipids using liquid chromatography-mass spectrometry.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 18%
Researcher 3 18%
Student > Ph. D. Student 3 18%
Student > Bachelor 2 12%
Student > Doctoral Student 1 6%
Other 1 6%
Unknown 4 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 24%
Chemistry 4 24%
Agricultural and Biological Sciences 2 12%
Medicine and Dentistry 1 6%
Unknown 6 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 February 2018.
All research outputs
#14,965,143
of 23,018,998 outputs
Outputs from Methods in molecular biology
#4,729
of 13,165 outputs
Outputs of similar age
#255,751
of 442,354 outputs
Outputs of similar age from Methods in molecular biology
#508
of 1,498 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,165 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,354 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.