ArticleRSC advances2018
Identification of potential diagnostic biomarkers of cerebral infarction using gas chromatography-mass spectrometry and chemometrics.
Article in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.Frontiers in neurology · 2025Pooled it
- An ultrasensitive aptamer-based fluorescent biosensor for luteinizing hormone with mutually orthogonal DNAzyme and self-replication CHA amplification.Analytical and bioanalytical chemistry · 2026Article
- Article
- LC-MS-based serum metabolomics reveals distinct metabolic signatures in patients with cerebral infarction.Frontiers in neurologyArticle
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cerebral infarction (CI) is one of the most common cerebrovascular diseases and remains a major health problem worldwide. In this study, we evaluated the potential diagnostic biomarkers and important relevant metabolic pathways associated with CI. Metabolomics based on gas chromatography-mass spectrometry coupled with the multivariate pattern recognition technique were used to characterize the potential serum metabolic profiles of CI. Forty healthy controls and thirty-three cerebral infarction patients were recruited for the nontargeted global metabolites' study and subsequent targeted fatty acid analysis. Overall, thirty-four endogenous metabolites were found in serum from the untargeted global study, four of which were detected to be significantly different between the CI group and healthy controls, including l-lysine, octadecanoic acid (fatty acid), l-tyrosine and lactic acid. Additionally, fourteen free fatty acids were identified by the subsequent targeted fatty acid analysis, and seven of them were detected to be significantly different between the CI group and healthy controls, which were mainly associated with arachidonic acid metabolism and fatty acid metabolism. Our results suggest several potential diagnostic biomarkers, and serum metabolism research is demonstrated as a powerful tool to explore the pathogenesis of CI.
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Registered trials
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