Home

Citation: WEI Ying, WAN Chuan-Ling, XUE Rong, LI Xiao-Jing, ZHANG Wen-Jun, PEI Feng-Kui. ¹H NMR-Based Metabonomic Study on Urine from Haematitum-Treated Rats[J]. Chinese Journal of Analytical Chemistry, ;2016, 44(6): 857-963. doi: 10.11895/j.issn.0253-3820.150934 shu

¹H NMR-Based Metabonomic Study on Urine from Haematitum-Treated Rats

1.
Key Laboratory of Synthetic Rubber, Chinese Academy of Sciences, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China;
2.
Department of Chemistry, Hebei University of Technology, Tianjin 300130, China

Received Date: 23 November 2015
Revised Date: 26 February 2016

Fund Project: This work was supported by the National Natural Science Foundation of China (Nos. 20975097, 21305134)

Figures(5)

Wistar rats were intragastrically administered with different doses (2, 5 and 10 g/kg body weight) of haematitum. ¹H NMR-based metabonomic analysis coupled with multivariate statistical analysis (principal component analysis and partial least squares-discriminant analysis) was used to analyze the metabolic profiles of the urine samples collected from the treated rats. Univariate analysis on the ¹H NMR spectra of urine (1 d before administration, 1-5 d post administration) was used to screen out the potential features of haematitum. Significant treatment related changes were observed for the levels of citrate, tuarine, creatinine, α-ketoglutarate, succinate and dimethylglycine, which could be used as potential features of haematitum. A trend of recovery in connection with dose levels was observed overtime. Such biochemical changes indicated that haematitum treatment at the dose of 2, 5 and 10 g/kg body weight affected the Krebs cycle and glucose metabolism, energy metabolism, choline metabolism and dimethylglycine metabolism in rats. These changes may attribute to the disturbances of hepatic function in 10 g/kg body weight group.
- Nuclear magnetic resonance,
- Metabonomics,
- Principal component analysis,
- Partial least squares-discriminant analysis,
- Haematitum
1. [1]
2. [2]
3. [3]
4. [4]
5. [5]
6. [6]
7. [7]
8. [8]
9. [9]
10. [10]
11. [11]
12. [12]
13. [13]
14. [14]
15. [15]
16. [16]
17. [17]
18. [18]
19. [19]
1. [1]
  Qian Wu , Yuanxia Lv , Zixuan Guo , Zhihao Zhao , Zhimin Zhang , Hongmei Lu . A Case Study and Practice of Research-Oriented Comprehensive Instrumental Analysis Laboratory Courses. University Chemistry, 2025, 40(10): 194-202. doi: 10.12461/PKU.DXHX202411063
2. [2]
  Jinkang Jin , Yidian Sheng , Ping Lu , Zhan Lu . Introducing a Website for Learning Nuclear Magnetic Resonance (NMR) Spectrum Analysis. University Chemistry, 2024, 39(11): 388-396. doi: 10.12461/PKU.DXHX202403054
3. [3]
  Xudong Liu , Huili Fan , Junping Xiao , Min Yang , Yan Li . Teaching Approaches to the A_E + A_N Mechanism of Electrophilic Addition Reactions between Olefins and Inorganic Acids in Organic Chemistry. University Chemistry, 2025, 40(7): 367-372. doi: 10.12461/PKU.DXHX202409041
4. [4]
  Zhike Yang , Jinfan Xu , Junhao Chen , Zheng Yang , Fei Ding , Neil Qiang Su . AI NMR Assistant: A DP5-Based Intelligent System for NMR Spectral Interpretation. University Chemistry, 2026, 41(1): 20-28. doi: 10.12461/PKU.DXHX202506013
5. [5]
  Zhuoming Liang , Ming Chen , Zhiwen Zheng , Kai Chen . Multidimensional Studies on Ketone-Enol Tautomerism of 1,3-Diketones By ¹H NMR. University Chemistry, 2024, 39(7): 361-367. doi: 10.3866/PKU.DXHX202311029
6. [6]
  Yuan Zhuang , Wenhui Li , Jie Li . Curriculum Reform of “Chemical Composition Analysis of Materials” under Background of First-Class Discipline Construction. University Chemistry, 2025, 40(5): 283-290. doi: 10.12461/PKU.DXHX202407070
7. [7]
  Hao Wu , Zhen Liu , Dachang Bai . ¹H NMR Spectrum of Amide Compounds. University Chemistry, 2024, 39(3): 231-238. doi: 10.3866/PKU.DXHX202309020
8. [8]
  Haiyang Jin , Yonghai Hui , Yongfei Zhang , Lijun Gao , Yun Wang . Application and Exploration of Nuclear Magnetic Resonance Spectrometer in Undergraduate Basic Laboratory Teaching. University Chemistry, 2025, 40(3): 245-250. doi: 10.12461/PKU.DXHX202406022
9. [9]
  Haolin Zhan , Qiyuan Fang , Jiawei Liu , Xiaoqi Shi , Xinyu Chen , Yuqing Huang , Zhong Chen . Noise Reduction of Nuclear Magnetic Resonance Spectroscopy Using Lightweight Deep Neural Network. Acta Physico-Chimica Sinica, 2025, 41(2): 100017-0. doi: 10.3866/PKU.WHXB202310045
10. [10]
  Zelin Wang , Gang Liu , Mengran Wang , Peiyu Zhang , Aixin Song , Jingcheng Hao , Jiwei Cui . Application of Instrumental Analysis in the Detection of Organic Components in Liquor. University Chemistry, 2025, 40(11): 318-326. doi: 10.12461/PKU.DXHX202502077
11. [11]
  Zunxiang Zeng , Yuling Hu , Yufei Hu , Hua Xiao . Analysis of Plant Essential Oils by Supercritical CO₂Extraction with Gas Chromatography-Mass Spectrometry: An Instrumental Analysis Comprehensive Experiment Teaching Reform. University Chemistry, 2024, 39(3): 274-282. doi: 10.3866/PKU.DXHX202309069
12. [12]
  Lijun Dong , Pengcheng Du , Guangnong Lu , Wei Wang . Exploration and Practice of Independent Design Experiments in Inorganic and Analytical Chemistry: A Case Study of “Preparation and Composition Analysis of Tetraammine Copper(II) Sulfate”. University Chemistry, 2024, 39(4): 361-366. doi: 10.3866/PKU.DXHX202310041
13. [13]
  Shunü Peng , Huamin Li , Zhaobin Chen , Yiru Wang . Simultaneous Application of Multiple Quantitative Analysis Methods in Gas Chromatography for the Determination of Active Ingredients in Traditional Chinese Medicine Preparations. University Chemistry, 2025, 40(10): 243-249. doi: 10.12461/PKU.DXHX202412043
14. [14]
  Jiageng Li , Putrama . 数值积分耦合非线性最小二乘法一步确定反应动力学参数. University Chemistry, 2025, 40(6): 364-370. doi: 10.12461/PKU.DXHX202407098
15. [15]
  Linghua Chen . 基于双联动“三学”模式的食品专业分析化学教学改革. University Chemistry, 2025, 40(8): 78-91. doi: 10.12461/PKU.DXHX202409095
16. [16]
  Yuan Zheng , Quan Lan , Zhenggen Zha , Lingling Li , Jun Jiang , Pingping Zhu . Teaching Reform of Organic Synthesis Experiments by Introducing Reverse Thinking and Design Concepts: Taking the Synthesis of Cinnamic Acid Based on Retrosynthetic Analysis as an Example. University Chemistry, 2024, 39(6): 207-213. doi: 10.3866/PKU.DXHX202310065
17. [17]
  Yan Su , Xiuyun Wang , Huimin Guo , Yanjuan Zhang , Xinwen Zhang , Yunting Shang , Wenfeng Jiang . To Cultivate Scientific Literacy by Learning, Thinking, Practicing and Understanding, To Utilize the “Smart Eye” Expertise by Integrating of Knowledge and Action: Ideological and Political Construction of Analytical Chemistry Experiment Course. University Chemistry, 2024, 39(2): 196-202. doi: 10.3866/PKU.DXHX202308003
18. [18]
  Weiwei Zhang , Yongxin Ren , Hong Zhang , Ke Lu . Current Situation and Quality Improvement Measures of Undergraduate Education in Modern Analytical Testing Technology under the “Learning, Teaching, and Practicing” Trinity Concept. University Chemistry, 2025, 40(10): 78-85. doi: 10.12461/PKU.DXHX202412006
19. [19]
  Mi Wen , Baoshuo Jia , Yongqi Chai , Tong Wang , Jianbo Liu , Hailong Wu . Improvement of Fluorescence Quantitative Analysis Experiment: Simultaneous Determination of Rhodamine 6G and Rhodamine 123 in Food Using Chemometrics-Assisted Three-Dimensional Fluorescence Method. University Chemistry, 2025, 40(4): 390-398. doi: 10.12461/PKU.DXHX202405147
20. [20]
  Tingting Yu , Si Chen , Lianglong Sun , Tongtong Shi , Kai Sun , Xin Wang . Comprehensive Experimental Design for the Photochemical Synthesis, Analysis, and Characterization of Difluoropyrroles. University Chemistry, 2024, 39(11): 196-203. doi: 10.3866/PKU.DXHX202401022