Prediction of plasma protein binding rate based on machine learning / 中国药科大学学报

@#Predicting the protein binding rate of drugs in plasma is helpful to us in understanding the pharmacokinetic characteristics of drugs, with much value of reference for early research on drug discovery. In this study, plasma protein binding rate information of 2 452 clinical drugs were collected.Two pieces of software, Molecular Operating Environment (MOE) and Mordred, were used to calculate molecular descriptors, which were used as input features of the model.Extreme gradient boosting (XGBoost) algorithm and random forest (RF) algorithm were then used to build a machine learning model.The results showed that, compared with MOE, the prediction performance of the constructed model was better using the molecular descriptor calculated by Mordred as the input of the model.The prediction performance results of the model constructed using the XGBoost algorithm and the RF algorithm were similar, and the R2 of the optimal model were both 0.715.According to the research results, it can be concluded that the drug plasma protein binding rate is closely related to some physical and chemical properties of the drug molecule, such as water solubility, octanol/water partition coefficient and conjugated double bonds.Using these parameters to predict the plasma protein binding rate of drugs has the advantages of convenience and efficiency, which can provide reference for related pharmacokinetic studies.

Influence of nursing intervention on the compliance of patients with dysfunctional uterine bleeding in climacteric period / 中国实用护理杂志

Objective The aim of this research is to evaluate the influence of nursing intervention on the compliance of patients with dysfunctional uterine bleeding in climacteric period. Methods We divided 96 patients with dysfunctional uterine bleeding in climacteric period from February to December in 2006 into the intervention group and the control group with 48 cases in each group.The control group was given medication instruction simply by the doctors and no nursing intervention.The intervention group was given health education and follow-up supervision.The general information and medical history of patients were registered at the first visit. The medication, adverse effect and effect of drugs were also registered at every visit. All patients were given follow-up visit 3 months later.The medication and visiting compliance and the treatment effect were observed. Results One patients missed follow-up visit in the intervention group and 11 patients missed in the control group.The medication compliance was 87.2% and the visit compliance was 93.6% in the intervention group,which was superior to those of the control group (67.6%,56.8%).The effect of hormone treatment was also better than that of the control group,P ＜ 0.05. Conclusions Nursing intervention couhl improve the compliance and medication effect of patients with dysfunctional uterine bleeding in climacteric period.