The polysaccharide extracted from Huidouba(PEH) exihibited a significant anti-diabetic activity. The polysaccharide contained glucose, mannose and galactose in a content ratio of 1.00:0.34:0.32. After administration w...The polysaccharide extracted from Huidouba(PEH) exihibited a significant anti-diabetic activity. The polysaccharide contained glucose, mannose and galactose in a content ratio of 1.00:0.34:0.32. After administration with 50―200 mg/kg body weight of PEH to type Ⅱ diabetic mice induced by alloxan for four weeks, the blood glucose level of mice was decreased significantly. Moreover, the SOD activity increased at the same time(p<0.01). PEH showed a significant anti-diabetic and anti-oxidation activity. In addition, PEH affected the BUN and ALT levels(p<0.05), which are important characteristics of diabetes mellitus. Through this work, PEH should be a potential anti-diabetic drug in the future.展开更多
Partial least squares(PLS),back-propagation neural network(BPNN)and radial basis function neural network(RBFNN)were respectively used for estalishing quantative analysis models with near infrared(NIR)diffuse reflectan...Partial least squares(PLS),back-propagation neural network(BPNN)and radial basis function neural network(RBFNN)were respectively used for estalishing quantative analysis models with near infrared(NIR)diffuse reflectance spectra for determining the contents of rifampincin(RMP),isoniazid(INH)and pyrazinamide(PZA)in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform(FFT)and standard normal variate(SNV)transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis(PCA)method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models' parameters were chosen by comparing the root mean square error of cross-validation(RMSECV)values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.展开更多
基金Supported by the China Medical Foundation(No.20061108)
文摘The polysaccharide extracted from Huidouba(PEH) exihibited a significant anti-diabetic activity. The polysaccharide contained glucose, mannose and galactose in a content ratio of 1.00:0.34:0.32. After administration with 50―200 mg/kg body weight of PEH to type Ⅱ diabetic mice induced by alloxan for four weeks, the blood glucose level of mice was decreased significantly. Moreover, the SOD activity increased at the same time(p<0.01). PEH showed a significant anti-diabetic and anti-oxidation activity. In addition, PEH affected the BUN and ALT levels(p<0.05), which are important characteristics of diabetes mellitus. Through this work, PEH should be a potential anti-diabetic drug in the future.
基金Supported by the Science Technology Development Project of Jilin Province,China(No.20020503-2).
文摘Partial least squares(PLS),back-propagation neural network(BPNN)and radial basis function neural network(RBFNN)were respectively used for estalishing quantative analysis models with near infrared(NIR)diffuse reflectance spectra for determining the contents of rifampincin(RMP),isoniazid(INH)and pyrazinamide(PZA)in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform(FFT)and standard normal variate(SNV)transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis(PCA)method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models' parameters were chosen by comparing the root mean square error of cross-validation(RMSECV)values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.
