A Urine Metabonomics Study of Rat Bladder Cancer by Combining Gas Chromatography-Mass Spectrometry with Random Forest Algorithm
المؤلفون المشاركون
Liu, Fan
Fang, Mengchan
Wu, Liqing
Guo, Lan
Wan, Yiqun
Huang, Lingling
المصدر
International Journal of Analytical Chemistry
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-21
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
A urine metabolomics study based on gas chromatography-mass spectrometry (GC-MS) and multivariate statistical analysis was applied to distinguish rat bladder cancer.
Urine samples with different stages were collected from animal models, i.e., the early stage, medium stage, and advanced stage of the bladder cancer model group and healthy group.
After resolving urea with urease, the urine samples were extracted with methanol and, then, derived with N, O-Bis(trimethylsilyl) trifluoroacetamide and trimethylchlorosilane (BSTFA + TMCS, 99 : 1, v/v), before analyzed by GC-MS.
Three classification models, i.e., healthy control vs.
early- and middle-stage groups, healthy control vs.
advanced-stage group, and early- and middle-stage groups vs.
advanced-stage group, were established to analyze these experimental data by using Random Forests (RF) algorithm, respectively.
The classification results showed that combining random forest algorithm with metabolites characters, the differences caused by the progress of disease could be effectively exhibited.
Our results showed that glyceric acid, 2, 3-dihydroxybutanoic acid, N-(oxohexyl)-glycine, and D-turanose had higher contributions in classification of different groups.
The pathway analysis results showed that these metabolites had relationships with starch and sucrose, glycine, serine, threonine, and galactose metabolism.
Our study results suggested that urine metabolomics was an effective approach for disease diagnosis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fang, Mengchan& Liu, Fan& Huang, Lingling& Wu, Liqing& Guo, Lan& Wan, Yiqun. 2020. A Urine Metabonomics Study of Rat Bladder Cancer by Combining Gas Chromatography-Mass Spectrometry with Random Forest Algorithm. International Journal of Analytical Chemistry،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1167757
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fang, Mengchan…[et al.]. A Urine Metabonomics Study of Rat Bladder Cancer by Combining Gas Chromatography-Mass Spectrometry with Random Forest Algorithm. International Journal of Analytical Chemistry No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1167757
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fang, Mengchan& Liu, Fan& Huang, Lingling& Wu, Liqing& Guo, Lan& Wan, Yiqun. A Urine Metabonomics Study of Rat Bladder Cancer by Combining Gas Chromatography-Mass Spectrometry with Random Forest Algorithm. International Journal of Analytical Chemistry. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1167757
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1167757
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر