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GC/MS-Based Metabolomics Reveals Biomarkers in Asthma Murine Model Modulated by Opuntia humifusa.
Seo, Seung-Ho; Kim, Eun-Ju; Park, Seong-Eun; Byun, Sung-Hoon; Lee, Soon-Young; Bok, So-Hyeon; Park, Dae-Hun; Son, Hong-Seok.
Affiliation
  • Seo SH; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Kim EJ; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Park SE; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Byun SH; Department of Oral and Maxillofacial Surgery, Gyeongsang National University Hospital, Jinju 52727, Republic of Korea.
  • Lee SY; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Bok SH; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Park DH; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
  • Son HS; School of Korean Medicine, Dongshin University, Naju 58245, Republic of Korea.
Article in En | MEDLINE | ID: mdl-30515230
ABSTRACT
GC/MS coupled with multivariate statistical analysis was performed to identify marker metabolites in serum of mice after healing ovalbumin- (OVA-) induced asthma using Opuntia humifusa. Principal component analysis (PCA) score plot showed separation among groups, with metabolite profiles of serum showing differences according to various treatments for the asthma murine model. Levels of stearic acid and arachidic acid were significantly lower in the serum from OVA-induced group than those from the control group. Dexamethasone treatment group was characterized by higher serum levels of urea, myristic acid, and palmitic acid along with lower levels of aspartic acid compared to OVA-induced group. O. humifusa treatment mice groups showed dose-proportional higher levels of urea and glycerol than OVA-induced group. These results highlight that GC/MS-based metabolomics is a powerful technique for identifying molecular markers of asthma.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Evid Based Complement Alternat Med Year: 2018 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Evid Based Complement Alternat Med Year: 2018 Document type: Article
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