[Study on action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis based on techniques of gene expression profile and molecular fingerprint].

Action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis were discussed based on gene expression profile and molecular fingerprint in this paper. First, gene expression profiles of atherosclerotic carotid artery tissues and histologically normal tissues in human body were collected, and were screened using significance analysis of microarray (SAM) to screen out differential gene expressions; then differential genes were analyzed by Gene Ontology (GO) analysis and KEGG pathway analysis; to avoid some genes with non-outstanding differential expression but biologically importance, Gene Set Enrichment Analysis (GSEA) were performed, and 7 chemical ingredients with higher negative enrichment score were obtained by Cmap method, implying that they could reversely regulate the gene expression profiles of pathological tissues; and last, based on the hypotheses that similar structures have similar activities, 336 ingredients of compound Danshen dripping pills were compared with 7 drug molecules in 2D molecular fingerprints method. The results showed that 147 differential genes including 60 up-regulated genes and 87 down regulated genes were screened out by SAM.

[Study on material base of Ligusticum wallichii for treating brain ischemia and its molecular mechanism based on molecular docking].

To explore the effective ingredients and mechanism of Ligusticum wallichii in treating brain ischemia. Four brain ischemia-related target proteins were selected in the joint screening for the 45 component in L. wallichii reported in literatures based on molecular docking by reference to the corresponding drugs in the market.

[Effects of Different Pretreatment Methods on the Phenylketonuria Screening Model by FTIR/ATR Spectroscopy].

To establish a phenylketonuria screening model by FTIR/ATR spectroscopy, and to compare the effects of different pretreatment methods, such as baseline correction, smoothing, derivation, Fourier deconvolution, on the model quality. A consensus partial least squares regression method (cPLS) was used to build the quantitative model of phenylalanine in dried blood spots. The effects of different pretreatment methods on the model performance were investigated, using the correlation coefficient (r), root mean square error of prediction (RMSEP), mean relative error (MRE) and predictive accuracy (Acc).

[Study on prediction of compound-target-disease network of chuanxiong rhizoma based on random forest algorithm].

To collect small molecule drugs and their drug target data such as enzymes, ion channels, G-protein-coupled receptors and nuclear receptors from KEGG database as the training sets, in order to establish drug-target interaction models based on the random forest algorithm. The accuracies of the models were evaluated by the 10-fold cross-validation test, showing that the predicted success rates of the four drug target models were 71.34%, 67.