Cognitive impairment, the leading cause of traumatic brain injury (TBI)-related disability, adversely affects the quality of life of TBI patients, and exacts a personal and economic cost that is difficult to quantify. The underlying pathophysiological mechanism is currently unknown, and an effective treatment of the disease has not yet been identified. This study aimed to advance our understanding of the mechanism of disease pathogenesis; thus, metabolomics based on gas chromatography/mass spectrometry (GC-MS), coupled with multivariate and univariate statistical methods were used to identify potential biomarkers and the associated metabolic pathways of post-TBI cognitive impairment. A biomarker panel consisting of nine serum metabolites (serine, pyroglutamic acid, phenylalanine, galactose, palmitic acid, arachidonic acid, linoleic acid, citric acid, and 2,3,4-trihydroxybutyrate) was identified to be able to discriminate between TBI patients with cognitive impairment, TBI patients without cognitive impairment and healthy controls. Furthermore, associations between these metabolite markers and the metabolism of amino acids, lipids and carbohydrates were identified. In conclusion, our study is the first to identify several serum metabolite markers and investigate the altered metabolic pathway that is associated with post-TBI cognitive impairment. These markers appear to be suitable for further investigation of the disease mechanisms of post-TBI cognitive impairment.
This study was conducted to investigate the chemical differences between Acori Tatarinowii Rhizoma and Acori Calami Rhizoma using gas chromatography with mass spectrometry and chemometric methods. Quantitative fingerprints were established. A total of 90 volatile compounds were identified and quantified using heuristic evolving latent projection and retention index. An efficient model based on partial least squares-discriminant analysis coupled with variable iterative space shrinkage approach was developed to distinguish Acori Tatarinowii Rhizoma from Acori Calami Rhizoma. The correct rate was 95.83%, and the area under the receiver operating characteristic curve was 100%. Finally, three volatiles, namely, camphor, longicyclene, and δ-cadinene, were selected as key discrimination factors between Acori Tatarinowii Rhizoma and Acori Calami Rhizoma. The proposed protocol can serve as a valid strategy for quality control and screening of potential bioactive components of herbal medicines.
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