Document Detail

A metabonomic approach applied to predict patients with cerebral infarction.
MedLine Citation:
PMID:  21376948     Owner:  NLM     Status:  In-Data-Review    
Cerebral infarction is always of sudden onset, and usually leading to serious consequence. It is of therapeutic significance to develop fast and accurate diagnosis methods for cerebral infarction so that patients can be treated timely and properly. A metabonomic approach was then proposed to investigate the potential biomarkers and metabolic pathways associated with cerebral infarction and also establish a prediction model of cerebral infarction for the fast diagnosis. Serum metabolic profiling of sixty-seven cerebral infarction patients and sixty-two controls was obtained using UPLC-TOF MS. The resulting data were then processed by multivariate statistical analysis to graphically demonstrate metabolic variations. The PLS-DA model was validated with cross validation and permutation tests to assure the model's reliability, and significant difference was obtained between the original and hypothetical models (p<0.0001). A series of endogenous metabolites in the one-carbon cycle, such as folic acid, cysteine, S-adenosyl homocysteine and oxidized glutathione, were determined as potential biomarkers of cerebral infarction. A prediction model developed using PLS-KNN algorithm was established to differentiate cerebral infarction patients from controls, and an average accuracy of 100% was obtained. In conclusion, metabonomic approach is a powerful tool to investigate the pathogenesis of stroke and is expected to be developed as a useful method for the fast diagnosis.
Zhiting Jiang; Jingbo Sun; Qionglin Liang; Yefeng Cai; Shasha Li; Yan Huang; Yiming Wang; Guoan Luo
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Publication Detail:
Type:  Journal Article     Date:  2011-01-15
Journal Detail:
Title:  Talanta     Volume:  84     ISSN:  1873-3573     ISO Abbreviation:  Talanta     Publication Date:  2011 Apr 
Date Detail:
Created Date:  2011-03-07     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2984816R     Medline TA:  Talanta     Country:  England    
Other Details:
Languages:  eng     Pagination:  298-304     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Elsevier B.V. All rights reserved.
School of Pharmacy, East-China University of Science & Technology, Shanghai, PR China; Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Department of Chemistry, Tsinghua University, Beijing, PR China.
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