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Journal of Chinese Integrative Medicine ›› 2011, Vol. 9 ›› Issue (1): 15-21.doi: 10.3736/jcim20110104

• Methodology • Previous Articles     Next Articles

Mathematical analysis of characteristics of glucocorticoid-induced yang deficiency or yin deficiency syndrome in animal models based on information entropy theory

Rui Jin1, Bing Zhang1(), Sen-mao Liu2, Li Ni1, Min  Li1, Lian-zhen Li1   

  1. 1. School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100102, China
    2. School of Mathematical Sciences, Peking University, Beijing 101871, China
  • Received:2010-05-18 Accepted:2010-06-16 Online:2011-01-20 Published:2011-01-15
  • Contact: Zhang Bing

Objective: Based on information entropy theory, this study analyzes the experimental indicators of glucocorticoid-induced traditional Chinese medicine yang deficiency or yin deficiency syndrome in animal models, thus laying the foundation of defining and interpreting the model state.
Methods: Data of biochemical indicators from 24 groups of animal models with different modeling conditions (type of modeling agent, dosage of modeling agent and modeling time) were collected. Information gain values for three study objects (type of modeling agent, dosage of modeling agent and modeling time) were calculated respectively after standardization, and then characteristics of yang deficiency or yin deficiency syndrome models were interpreted with these values and ranking map.
Results: Greatest information gain values of most indicators were got when the study object was the type of modeling agent, which is the most important factor in the differentiation of model state. With this study object, triglyceride (TG), total cholesterol (TC), total protein (TP), albumin (ALB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and corticosteroid (CS) got larger information gain values than testosterone (T), lactic dehydrogenase (LDH), and cyclic adenosine monophosphate (cAMP). This indicated that the former seven indicators may be significantly different between the two animal models induced by hydrocortisone and dexamethasone, respectively. In the study of the modeling time, AST may be affected more than others. In the study of the dosage of modeling agent, TC and ALB may be affected more in the model of hydrocortisone and no indicators were significantly affected by the dosage of modeling agent in the dexamethasone model.
Conclusion: Mathematical method based on information entropy theory allows researchers to analyze experimental data in several experiments at the same time and to interpret the trend and stability of indicators. Based on this study and by analyzing the impacts of different modeling conditions on the indicators, elucidations of the characteristics of glucocorticoid-induced yang deficiency or yin deficiency syndrome in animal models and some biochemical indicators for model comparison are in need.

Key words: information entropy, glucocorticoids, yang deficiency, yin deficiency, models, animal, mathematical computing

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