OBJECTIVE To optimize the preparation of Xiakucao Kaiyin Granules(XKG)and control the quality of its intermedi-ates.METHODS The physical characteristics of spray dry powder of XKG were determined by powder evaluation method,and the physical fingerprint composed of 9 secondary physical quality indexes,such as bulk density,tap density,angle of repose and Hausner ratio,was established to determine the stability of the previous process and the quality consistency of spray dry powder.Taking the parti-cle forming rate,dissolution rate,moisture absorption rate and angle of repose as evaluation indexes,dry granulation was carried out,and the auxiliary materials of XKG were screened.The mixture design experiment combined with G1-entropy weight method and neural network method were used to optimize the proportion of the selected excipients,and the best preparation technology of XKG was deter-mined by comparing the two methods.The physical fingerprint of particles was established to evaluate the consistency of particle quality among different batches.RESULTS The similarity of physical fingerprints of 9 batches of spray dry powder was greater than 0.970,and the physical properties were stable.The comprehensive score of the best proportion of auxiliary materials obtained through the anal-ysis of mixture design was higher than that obtained by neural network modeling and optimization,so it was finally determined that the proportion of medicine and auxiliary materials of XKG was 7:3 and 29%maltodextrin and 71%lactose were added for dry granulation.The similarity of physical fingerprints of five batches of granule was greater than 0.994.CONCLUSION The estab-lished physical fingerprint of intermediates can be used to control the quality process of XKG,and the optimized prescription of XKG can improve the physical properties of granules and improve the consistency of granule quality.

OBJECTIVE To predict the amount of colorants used in the preparation of placebo of Chinese medicine by construc-ting particle swarm optimization-back propagation neural network PSO-BPNN compound granules,and to provide a new idea for the simulation of placebo color of Chinese medicine compound granules.METHODS The BP neural network was used to establish the model of sample color parameters L,a?,b?and pigment mass fraction.The global search ability of particle swarm optimization algo-rithm was used to optimize the weight and bias of BP neural network to prevent the local minimum value of the model.The linear reduc-tion weight coefficient method and the introduction of mutation operator were used to improve the global optimization ability of particle swarm optimization algorithm.The color comprehensive evaluation index(ΔE)was used as the objective evaluation standard to verify the test results.RESULTS The training results show that the fitting accuracy of the improved PSO-BP neural network was up to 98.31%.The prediction results show that the prediction error of the improved PSO-BP neural network was the smallest,and the mean absolute percentage error(MAPE),root mean square error(RMSE)and mean color difference(ΔE)were 0.411 5,2.164 6 and 2.56,respectively.The verification samples of three kinds of particles were prepared for verification.The ΔE of the verification sample and the model drug were 1.73,2.63 and 4.11,respectively.The color difference between the two groups and the model drug was small by visual evaluation.CONCLUSION The BP neural network based on the improved particle swarm optimization algorithm can simulate the prediction of the amount of colorants used in the preparation of Chinese medicine compound granules,and can be used as a recommended optimization model for placebo color matching research.

OBJECTIVE To optimize the preparation of Xiakucao Kaiyin Granules(XKG)and control the quality of its intermedi-ates.METHODS The physical characteristics of spray dry powder of XKG were determined by powder evaluation method,and the physical fingerprint composed of 9 secondary physical quality indexes,such as bulk density,tap density,angle of repose and Hausner ratio,was established to determine the stability of the previous process and the quality consistency of spray dry powder.Taking the parti-cle forming rate,dissolution rate,moisture absorption rate and angle of repose as evaluation indexes,dry granulation was carried out,and the auxiliary materials of XKG were screened.The mixture design experiment combined with G1-entropy weight method and neural network method were used to optimize the proportion of the selected excipients,and the best preparation technology of XKG was deter-mined by comparing the two methods.The physical fingerprint of particles was established to evaluate the consistency of particle quality among different batches.RESULTS The similarity of physical fingerprints of 9 batches of spray dry powder was greater than 0.970,and the physical properties were stable.The comprehensive score of the best proportion of auxiliary materials obtained through the anal-ysis of mixture design was higher than that obtained by neural network modeling and optimization,so it was finally determined that the proportion of medicine and auxiliary materials of XKG was 7:3 and 29%maltodextrin and 71%lactose were added for dry granulation.The similarity of physical fingerprints of five batches of granule was greater than 0.994.CONCLUSION The estab-lished physical fingerprint of intermediates can be used to control the quality process of XKG,and the optimized prescription of XKG can improve the physical properties of granules and improve the consistency of granule quality.

Based on the research results of aspiration in patients with dysphagia after ischemic stroke at home and abroad, this paper reviews the definition, detection methods, and risk factors of aspiration and emphasizes the incidence rate and severity of this disease. The authors conclude that preventing aspiration can decrease the incidence rate of aspiration pneumonia, change the clinical outcome of patients, and thereby save medical resources.

This study was aimed to optimize the ethanol extraction technology ofXiao-Xu-Ming (XXM) decoction. The extraction rates of paeoniflorin, ferulic acid, tetrandrine and yield extract were used as comprehensive evaluation indexes. The amount of ethanol, extraction times, extraction time and concentration of ethanol were selected as factors. The orthogonal design was used to optimize ethanol reflux extraction technology of XXM decoction. The results showed that the optimum extraction conditions were as follows: refluxing extracted 3 times with 10 folds, 70% ethanol, 1.5 h for each time. It was concluded that the optimized extraction process was objective, practical, reasonable and stable, which provided experimental basis for industrial production of XXM decoction.

[ ABSTRACT] AIM:To investigate the effect of triptolide on the inhibition of microglial activation in 1-methyl-4-phenyl pyridinium ( MPP+)-induced hemiparkinson disease rats.METHODS:The rat model of Parkinson disease was es-tablished by intranigral injection of MPP +.The rats were randomly divided into sham group, MPP+group, triptolide group and vehicle group.The survival of dopaminergic neurons was detected by the immunofluorescence of tyrosine hydroxylase ( TH) in the substantia nigra ( SN) .The activation of microglia was determined by immunofluorescence of OX-42 ( micro-glia marker) in the SN.The expression of chemokine receptor CX3CR1 in SN was measured by Western blotting.RE-SULTS:Intranigral injection of MPP+increased the fluorescence intensity of the microglial marker, and promoted DA neu-ron degenerative death.Immunohistological analysis showed that the OX-42 density was decreased (P<0.01) and tyrosine hydroxylase (TH) positive neurons were increased in the triptolide group (P<0.01).The expression of CX3CR1 was lower in triptolide group than that in model group (P<0.05).CONCLUSION:Triptolide may improve PA neurons func-tion in MPP+-induced rats through inhibiting CX3CR1 expression and microglial activation.