Exploring metabolic syndrome serum free fatty acid profiles based on GC–SIM–MS combined with random forests and canonical correlation analysis

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成果类型：

期刊论文

作者：

Dai, Ling;Goncalves, Carlos M. Vicente;Lin, Zhang;Huang, Jianhua;Lu, Hongmei*;...

通讯作者：

Lu, Hongmei

作者机构：

[Lu, Hongmei; Goncalves, Carlos M. Vicente; Lin, Zhang; Huang, Jianhua; An, Dong; Liang, Yizeng; Dai, Ling; Yi, Lunzhao] Cent South Univ, Coll Chem & Chem Engn, Res Ctr Modernizat Chinese Med, Changsha 410083, Peoples R China.

[Goncalves, Carlos M. Vicente] Univ Bergen, Fac Math & Nat Sci, Dept Chem, N-5020 Bergen, Norway.

[Huang, Jianhua] Hunan Univ Chinese Med, Dept Pharm, Changsha 410208, Hunan, Peoples R China.

[Yi, Lunzhao] Kunming Univ Sci & Technol, Yunnan Food Safety Res Inst, Kunming 650500, Peoples R China.

[Wang, Dongsheng] Cent South Univ, Xiangya Hosp, Changsha 410008, Hunan, Peoples R China.

通讯机构：

[Lu, Hongmei] C

Cent South Univ, Coll Chem & Chem Engn, Res Ctr Modernizat Chinese Med, Changsha 410083, Peoples R China.

语种：

英文

关键词：

Canonical correlation analysis;Free fatty acid;GC-SIM-MS;Metabolic profiling;Metabolic syndrome;Random forests

期刊：

Talanta

ISSN：

0039-9140

年：

2015

卷：

135

页码：

108-114

DOI：

10.1016/j.talanta.2014.12.039

基金类别：

National Nature Foundation Committee of PR China [21175157, 21375151, 21105129]; China Hunan Provincial Science and Technology Department [2012FJ4139]; Central South University, China [2010QZZD007]

机构署名：

本校为其他机构

院系归属：

药学院

摘要：

Metabolic syndrome (MetS) is a cluster of metabolic abnormalities associated with an increased risk of developing cardiovascular diseases or type II diabetes. Till now, the etiology of MetS is complex and still unknown. Metabolic profiling is a powerful tool for exploring metabolic perturbations and potential biomarkers, thus may shed light on the pathophysiological mechanism of diseases. In this study, fatty acid profiling was employed to exploit the metabolic disturbances and discover potential biomarkers of MetS. Fatty acid profiles of serum samples from metabolic syndrome patients and heal...

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Exploring metabolic syndrome serum free fatty acid profiles based on GC–SIM–MS combined with random forests and canonical correlation analysis

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