Azerbaijani
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Journal of Ethnopharmacology 2019-Sep

Plasma metabolomics of depressed patients and treatment with Xiaoyaosan based on mass spectrometry technique.

Yalnız qeydiyyatdan keçmiş istifadəçilər məqalələri tərcümə edə bilərlər
Giriş / Qeydiyyatdan keçin
Bağlantı panoya saxlanılır
Xiaojie Liu
Caichun Liu
Junsheng Tian
Xiaoxia Gao
Ke Li
Guanhua Du
Xuemei Qin

Açar sözlər

Mücərrəd

Xiaoyaosan (XYS), a famous and classic traditional Chinese prescription, has been used for long time in treating depressive disorders. XYS consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.).A GC-MS based metabolomics approach was applied to discover the potential biomarkers that were related to metabolic differences between healthy volunteers and depression cohort diagnosed by HAMD and CGI, and to demonstrate the potential utility of these biomarkers in the diagnosis of depression and pharmaceutical efficacy of XYS.A total of 17 depressed patients and the 17 age- and gender-matched healthy subjects were served as the primary cohort. The depressed patients were screened according to the Chinese Classification of Mental Disorder (CCMD-3) and the Hamilton Depression Scale (HAMD). In addition, five other depressed patients were also enrolled as the primary cohort when the final step of sample collection was conducted. Plasma samples were analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). Clinical and metabolomics data were analyzed by multivariate statistics analysis, Receiver Operating Characteristic (ROC) curve and MetaboAnalyst.We observed significant differences between depression cohort and healthy volunteers, and between patients before and after the treatment of XYS. The method was then clinically validated in an independent validation cohort. Levels of oxalic and stearic acids significantly increased in depressed patients' plasma while valine and urea significantly decreased, as compared with healthy controls. Of note, XYS reversed these metabolite changes in terms of regulating dysfunctions in glyoxylate and dicarboxylate metabolism, fatty acid biosynthesis, valine, leucine and isoleucine biosynthesis, and arginine and proline metabolism. Importantly, the combination of oxalic and stearic acids is in prospect as diagnose biomarkers.This study highlights the clinical application of metabolomics in disease diagnose and therapy evaluation, which will help in improving our understanding of depression and will lay solid foundation for the clinic application of TCMs. In addition, it suggests that the combination of the two potential biomarkers had also achieved a high diagnostic value, which consequently could be used a diagnose biomarkers.

Facebook səhifəmizə qoşulun

Elm tərəfindən dəstəklənən ən tam dərman bitkiləri bazası

  • 55 dildə işləyir
  • Elm tərəfindən dəstəklənən bitki mənşəli müalicələr
  • Təsvirə görə otların tanınması
  • İnteraktiv GPS xəritəsi - yerdəki otları etiketləyin (tezliklə)
  • Axtarışınızla əlaqəli elmi nəşrləri oxuyun
  • Təsirlərinə görə dərman bitkilərini axtarın
  • Maraqlarınızı təşkil edin və xəbər araşdırmaları, klinik sınaqlar və patentlər barədə məlumatlı olun

Bir simptom və ya bir xəstəlik yazın və kömək edə biləcək otlar haqqında oxuyun, bir ot yazın və istifadə olunan xəstəliklərə və simptomlara baxın.
* Bütün məlumatlar dərc olunmuş elmi araşdırmalara əsaslanır

Google Play badgeApp Store badge