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Overcoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.(Report)

The article investigates the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. From the analysis of 80 plasma and serum samples in experimental triplicate, a total of... Full description

Journal Title: Analytical Chemistry Sept 5, 2017, Vol.89(17), p.9424(8)
Main Author: Deying Chen, Wei Han, Xiaoling Su, Liang Li, Lanjuan Li
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 0003-2700
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title: Overcoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.(Report)
format: Article
creator:
  • Deying Chen, Wei Han, Xiaoling Su, Liang Li, Lanjuan Li
subjects:
  • Liquid Chromatography – Usage
  • Metabolomics – Research
  • Blood – Research
  • Isotopes – Research
ispartof: Analytical Chemistry, Sept 5, 2017, Vol.89(17), p.9424(8)
description: The article investigates the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. From the analysis of 80 plasma and serum samples in experimental triplicate, a total of 3651 metabolites with an average of 1818 metabolites per run, is detected. The results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics.
language: eng
source:
identifier: ISSN: 0003-2700
fulltext: fulltext
issn:
  • 0003-2700
  • 00032700
url: Link


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titleOvercoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.(Report)
creatorDeying Chen, Wei Han, Xiaoling Su, Liang Li, Lanjuan Li
ispartofAnalytical Chemistry, Sept 5, 2017, Vol.89(17), p.9424(8)
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subjectLiquid Chromatography – Usage ; Metabolomics – Research ; Blood – Research ; Isotopes – Research
descriptionThe article investigates the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. From the analysis of 80 plasma and serum samples in experimental triplicate, a total of 3651 metabolites with an average of 1818 metabolites per run, is detected. The results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics.
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titleOvercoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.(Report)
descriptionThe article investigates the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. From the analysis of 80 plasma and serum samples in experimental triplicate, a total of 3651 metabolites with an average of 1818 metabolites per run, is detected. The results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics.
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abstractThe article investigates the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. From the analysis of 80 plasma and serum samples in experimental triplicate, a total of 3651 metabolites with an average of 1818 metabolites per run, is detected. The results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics.
pubAmerican Chemical Society
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doi10.1021/acs.analchem.7b02240
pages9424-9431
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date2017-09-05