Objective To establish a new-type virtual screening predictive model of Chinese medicinal compounds with anti-fibrosis effects, and to verify the predictive performance of the model.Methods The dimension reduction and characteristic optimization of molecular fingerprints were implemented by using random forest (RF) algorithm and gradient boosting decision tree (GBDT) algorithm.A hybrid model of characteristic optimization-machine learning was established, and optimized characteristics were input into logistic regression (LR) and machine learning algorithm of artificial neural network (ANN) for training.Precision, recall rate and F1 value were used for reviewing the performances of various model combinations.The virtual screening predictive model of Chinese medicinal compounds with anti-fibrosis effect was determined according to results of model performance reviewing.The predictive results of anti-fibrosis activity of Chinese medicinal compounds were compared between the virtual screening predictive model and molecular docking model for further verifying the predictive efficiency of the virtual screening predictive model.Results The precision of RF model was 0.76, recall rate was 0.75 and F1 value was 0.74 (AUC=0.818).The precision that of GBDT model was 0.76, recall rate was 0.74 and F1 value was 0.72 (AUC=0.829).The precision of ANN model was 0.75, racall rate was 0.75 and F1 value was 0.75 (AUC=0.802) , and that of model of RF+LR was 0.77, recall rate was 0.76 and F1 value was 0.75 (AUC=0.840).The precision of model of RF+LR was 0.74, recall rate was 0.84 and F1 value was 0.79 (AUC=0.850) , and that of model of GBDT+LR was 0.80, recall rate was 0.80 and F1 value was 0.79 (AUC=0.872).The precision of model of GBDT+ANN was 0.73, recall rate was 0.91 and F1 value was 0.81 (AUC=0.837).The results of molecular docking activities of Chinese medicinal compounds including curcumin, glycyrrhizic acid, hydro-xysafflor yellow A, emodine and gypenoside were accordance with the predictive results of the virtual screening predictive model.Conclusion The model based on RF+LR is better than the models established based on other methods.The virtual screening predictive model has good performance in prediction of Chinese medicinal compounds through comparing with molecular docking model.The method has feature of highthroughput screening and can make up the shortage of compound screening efficiency in molecular docking.It provides a new way for virtual screening prediction of Chinese medicinal compounds with anti-fibrosis effects.

目的 以体外培养的肥大细胞为实验材料,考察注射用双黄连诱发肥大细胞脱颗粒早期的生物学效应,初步探讨中药注射剂安全性评价的质控指标.方法 肥大细胞为RBL-2H3细胞株(ATCC-6562),注射用双黄连购自哈药集团中药二厂(Z20043425);细胞活力检测采用MTT法,β-氨基己糖苷酶检测采用ELISA法;采用扫描电镜观察肥大细胞形态,用激光共聚焦显微镜检测活细胞内钙离子浓度.结果 注射用双黄连细胞毒性剂量及致类过敏剂量为≥0.08 mg/mL;肥大细胞脱颗粒反应出现在药物作用早期(≤1分钟);较低浓度注射用双黄连诱发肥大细胞内钙离子浓度峰值出现在4分钟左右.结论 注射用双黄连作用肥大细胞早期,可激活Ca2+相关信号通路、启动肥大细胞脱颗粒反应、大量释放β-氨基己糖苷酶.该结果提示:基于RBL-2H3细胞的Ca2+浓度及致敏介质检测平台有望成为中药注射剂安全性评价的质控指标之一,具有重要应用前景.

This study was aimed to explore traditional Chinese medicine (TCM) professor Niu Jianzhao's medication rule in prescription with climacteric syndrome.Prescriptions treating climacteric syndrome that built by professor Niu were collected to build a database based on TCM Inheritance Assist System.The method of association rules with apriori algorithm was used to achieve frequency of single medicine,nature,taste and channel tropism of herbs,frequency of drug combination,association rules between herbs and core herb combinations.The data mining results showed 22 types of herbs used with high frequency,28 pairs of herb combination with most frequency,20 groups of herb association rules with the confidence of more than 0.95,52 herb pairs with high association,32 groups of three herbs as the core combinations,and 7 new prescriptions.It was concluded that in professor Niu Jianzhao's treatment of climacteric syndrome,the drugs were commonly used to invigorate the kidney,liver and spleen,and in combination with promoting blood circulation and calming the nerves.The medicinal properties of used herbs were even,warm or slightly cold.The tastes of used herbs were sweet,bitter and spicy.The channel tropisms of used herbs were the liver,kidney and lung meridian.This study highlighted data mining as an important tool for expedited analysis of TCM professor Niu Jianzhao's medication rules in prescriptions with climacteric syndrome.

目的 观察补肾活血方对去卵巢大鼠子宫的雌激素受体及周期蛋白(Cyclin)B表达的影响,探讨其治疗围绝经期综合征的作用机制.方法 选择SD雌性大鼠54只,随机分为假手术组、模型组、雌二醇组、补肾活血方组、联合用药组、补肾活血方+假手术组,每组9只.以双侧卵巢切除法建立大鼠围绝经期模型.各组灌胃给药40 d后取血清和子宫称重;酶联免疫吸附(ELISA)法检测血清中雌二醇(E2)、黄体生成素(LH)、卵泡刺激素(FSH)浓度;HE染色观察子宫组织病理改变并测定子宫内膜厚度;免疫组化法观察雌激素受体(ER)α、ERβ在子宫组织中分布与表达情况;蛋白质印迹法(Western blot)法检测子宫组织中周期蛋白(Cyclin B)蛋白表达.结果 补肾活血方治疗40 d后,与模型组比较,血清LH、FSH明显降低(P＜0.05或P＜0.01),血清E2水平升高(P＜0.05);同时,子宫脏器指数、子宫内膜厚度、子宫组织中ERα、ERβ和Cyclin B蛋白表达均明显升高(P＜0.05),与雌激素组呈现相似的作用,但作用强度均低于雌激素;补肾活血方+假手术组大鼠各项指标与假手术组比较无明显差异.结论 补肾活血方具有雌激素样作用,但作用强度弱于雌激素,对正常大鼠子宫组织无显著影响.