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BACKGROUND:Mesenchymal stem cells are susceptible to senescence during in vitro expansion,which greatly hinders their application in vivo and in vitro.How to improve the replicative senescence of mesenchymal stem cells is an urgent problem to be solved in tissue engineering. OBJECTIVE:To determine whether vascular endothelial growth factor combined with basic fibroblast growth factor can improve the aging of bone marrow mesenchymal stem cells caused by replicative passage. METHODS:Rat bone marrow mesenchymal stem cells were extracted by whole bone marrow adhesion method.Passage 2 cells were selected as normal control group.Passage 7 and later algebraic cells were selected as aging model group.Vascular endothelial growth factor(50 μg/L),basic fibroblast growth factor(10 μg/L),and their combination were administered.Cell proliferation was detected by CCK-8 assay.Cell senescence was observed by β-galactosidase activity staining.Cytoskeleton size and colony formation ability were observed by phalloidine staining and Giemsa staining,respectively,and the levels of senescence-related genes P16,P21,and P53 were detected by qRT-PCR.Gene expression levels of P16,P21,and P53 were tested by qRT-PCR. RESULTS AND CONCLUSION:(1)Vascular endothelial growth factor combined with basic fibroblast growth factor could promote the proliferation of aged bone marrow mesenchymal stem cells,which began to enter the plateau stage on day 9,and the absorbance value of the combined intervention group was significantly higher than that of the model group on day 9(P<0.05).(2)The phenotypic markers of the cells in the combined intervention group did not change,and the cell morphology changed from broad to slender.(3)Compared with the model group,the positive rate of β-galactosidase was significantly decreased(P<0.01);the number of nuclei increased(P<0.001);the total area of cytoskeleton increased(P<0.01);colony formation ability was enhanced(P<0.05);expression level of P16 was decreased(P<0.01)in the combined intervention group.These results indicate that vascular endothelial growth factor combined with basic fibroblast growth factor can improve the senescence of bone marrow mesenchymal stem cells caused by replicative passage without changing the cell phenotype.
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Objective To study computer toxicity prediction technology and predict the acute toxicity of Chinese materia medica; To provide a new way and method for safety evaluation of traditional Chinese medicine. Methods First, Mold2 software (version 2.0.0) was used to calculate molecular descriptors of 7409 chemical components. After preliminary screening of molecular descriptors, quantitative structure-activity relationship (QSAR) models were built up with Random Forest (RF) for screening the optimum prediction model. From the 83 kinds of toxic Chinese materia medica in Chinese Pharmacopoeia (2010 edition), acute toxicity of 60 kinds of Chinese materia medica reported from monomer structure (1692 chemical components) were under prediction.Results Totally 7409 pieces of data were obtained. When the descriptors were 52, RF modeling accuracy and Kappa were the highest, 0.712 and 0.436 respectively. Compound clusters were divided into 3 types according to optimum molecule descriptors (52). The accuracy and Kappa of the optimum model for the first type of compounds were 0.666 and 0.476 respectively; the accuracy and Kappa of the optimum model for the second type of compounds were 0.804 and 0.381 respectively; the accuracy and Kappa of the optimum model for the third type of compounds were 0.709 and 0.373 respectively. It was predicted that 60 kinds of Chinese materia medica containing 0 violent toxic compound, 2 high toxic compounds, 172 medium toxic compounds and 1518 low toxic compound.Conclusion QSAR model for prediction study on acute toxicity of chemical components of Chinese mareria medica can provide references combination medication and experimental studies.
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In order to provide a new way and method for safety evaluation of Chinese materia medica (CMM) and also to provide a reference for conventional animal experiments, computer toxicity prediction technique and method were established to predict the cardiotoxicity of CMM. Mold2 software (version 2.0.0) was used to calculate molecular descriptors of 1034 chemical components. Then, the random forest (RF) method and the support vector machine (SVM) method were used to screen the descriptors. After that, boosting trees method, SVM, regularized discriminant analysis method and RF method were used to build up prediction model, respectively. Finally, the cardiotoxicity of chemical components was predicted by the quantitative structure-activity relationship (QSAR) model with the best accuracy and Kappa value. The results showed that by comparing the accuracy and Kappa value of prediction model, it was found that the RF model was the optimal algorithm model with 86.3%accuracy and the Kappa value of 0. 725. Through the prediction research on chemical components of Chinese herbs with toxicity recorded in the Pharmacopoeia of People’s Republic of China (version2010),suchasEvodia rutaecarpa,North bean root,Murraya incense,some meaningful results had been received. It was concluded that QSAR model on prediction research of chemical components of Chinese herbs provided important references for further experimental studies and clinical researches.