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Background. This study is to determine mode of metabolism on triple collaboration bridges of traditional medicine, modern medicine and NCM.Goal. To determine membrane redoxy potentials three line involves important regulation factors on mode of metabolism which relationship connected with rlung, mkris, and badgan symbolic code.Materials and Methods. Only 81 healthy individuals were involved in the study. Proton leak was determined by quantity rate of MDA in cell membrane and membrane resistance, proton conductance was determined by serum and urine oxidase activity.Results. The table 1 shows quantity rate of membrane resistance was decreased 1.08-1.52 fold, HDL content was decreased, and however LDL was increased. This result is to manifest low proton leak which means this type is likely belonged to badgan symbolic code with qualities cold fatty, earth, water. The table 2 shows serum and urine oxidize activity 2.22-6.1 fold was increased, HDL content was increased; UCP-3 gene activity relatively was increased. This result is to manifest highproton conductance which means this type is likely belonged to mkris symbolic code with qualities hot fatty, fire.Conclusions:1. Individuals with high proton leak and slow proton conductance had serum and urine oxidize activity were weak, therefore there are visceral and subcutaneous fat were low.2. Individuals with medium proton leak and high proton conductance had serum and urine oxidize activity were high, therefore there are visceral was low and subcutaneous fat was high.3. Individuals with weak proton leak and medium proton conductance had serum and urine oxidize activity were medium, therefore there are visceral was high and subcutaneous fat was low.
RESUMO
Objective Predicting protein structural class is the basis for predicting protein spatial structure,so it is important to improve the prediction accuracy of protein structural class.Methods We proposed 3-state and 8-state Hidden Markov model (HMM),and applied these HMMs to the prediction of protein structural class,respectively.We evaluated their accuracy on two different datasets through the rigorous jackknife cross-validation test.Results Prediction ability of 8-state HMM and 3-state HMM to all α class were excellent,the prediction accuracy of 3-state HMM even reached above 95％.Compared with Chou data set,the prediction accuracy of Zhou data set for all β class and α/β class of was improved,while overall prediction accuracy increased by 2％.Conclusion HMM is an effective method to predict protein structural class.