OBJECTIVE: To study the protective efffects of Chailing Guiqi Decoction (CLGQD) combined with lumbrukinase on renal function in rats with adriamycin nephropathy. METHODS: Thirty-six SD rats were randomly divided into four groups: normal control group, untreated group, simvastatin-treated group and CLGQD -treated group. Adriamycin nephropathy was induced by intravenous injection with 5 mg/kg adriamycin. After seven-day treatment, quantitative measurement of 24-h urine protein was determined with trichloroacetic acid, and serum total protein (TP), albumin (Alb), total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), creatinine (Cr) and blood urea nitrogen (BUN) were assessed using automatic biochemistry analyzer. The pathomorphological changes of renal tissues were observed with light and electron microscopes. RESULTS: In the untreated group, the 24-h urine protein excretion, serum TC, TG, LDL, Cr and BUN were significantly higher than those in the normal control group (P<0.05 or P<0.01), while the serum TP, Alb, HDL were significantly lower than those in the normal control group (P<0.01). In the CLGQD-treated group, the 24-h urine protein excretion, serum TC, TG, LDL, Cr and BUN were significantly lower as compared with those in the untreated group (P<0.05 or P<0.01), while the serum TP, Alb and HDL were significantly higher as compared with those in the untreated group (P<0.05 or P<0.01). The pathomorphological findings of the renal tissues under the light microscope in the untreated group showed focal segmental glomerulosclerosis in a few of glomerulus, degenerated and swelled proximal tubular epithelial cells, proteins in cast formation in some renal tubules and scattered fibrosis in interstitial tissues of the kidney, while the electron microscope images showed the fusion of foot processes in glomerular epithelial cells. The pathomorphological changes in the CLGQD-treated group were slighter than those in the untreated group. CONCLUSION: CLGQD combined with lumbrukinase can reduce proteinuria, regulate lipid metabolism, protect renal function, and delay progressive renal damage in rats.

Objective To explore the application status and development trend of machine learning in the field of pharmacovigilance worldwide,and to provide reference for the research on the application of machine learning in the field of pharmacovigilance.Methods Relevant literature was searched in the Web of Science with the key words of"machine learning"and"pharmacovigilance"from the inception to March 1,2023.R language and other software were used to quantitatively analyze the literature data in this field.The clustering,co-occurrence and emergence visual analysis were carried out on the characteristics of annual published papers,institutions,countries,keywords and other aspects.Results A total of 904 literature were included.The number of literature published showed a fluctuating upward trend since 1994.There was cross-regional,cross-regional and cross-agency cooperation among the cooperative network institutions.The top 5 countries in the number of publications were the United States,China,Japan,South Korea and India,China and the United States had relatively close cooperation in this field.Signal detection,social media and electronic health records were high-frequency keywords in this field.Clustering and association rule analysis showed that this field focused on three aspects signal recognition,unstructured text mining and analysis,and processing and analysis of electronic medical information.At present,machine learning has made significant progress in signal recognition,social media information mining,and unstructured text processing of electronic medical information,which broaden the data sources of pharmacovigilance,improve the real-time monitoring ability of adverse drug reactions,bringing innovation impetus to the field of pharmacovigilance.Conclusion The rapid development of big data and artificial intelligence technologies has led to an increasing integration of machine learning into the field of pharmacovigilance,which promotes technical exchanges and cooperation and cross-disciplinary integration.It is necessary to optimize each machine learning algorithm to improve its accuracy and stability in pharmacovigilance,strengthen the protection measures of data privacy and security to ensure the safety of patient information.Integrating expertise in the fields of science,medicine,and data statistics with a view to promoting technological progress in the field of pharmacovigilance.

OBJECTIVE To mine the risk sig nals o f iodine contrast media from spontaneous reporting system. METHODS Reporting odds ratio ，proportional reporting ratio ，Medicines and Healthcare Products Regulatory Agency and Bayesian confidence propagation neural network were used to mine risk signals of 5 iodine contrast media （iopamidol，iohexol，iopromide，ioversol， iodixanol）. RESULTS 1 164（2 446 case times ）adverse drug reaction of iodine contrast media were included ，a total of 14 risk signals involving systems/organs such as respiratory system （3，2，4，3，2 for the above 5 iodine contrast media ）and immune system and 32 specific adverse drug reaction signals including anaphylactic shock ，rash and flushing （11，7，7，3，4 for the above 5 iodine contrast media ）were found in 5 iodine contrast media. CONCLUSIONS The risk signals of 5 iodine contrast media verify that there is a certain correlation between these drugs and above adverse drug reactions. It is suggested that before using iodine contrast media in clinic ，it is necessary to pay attention to whether the patient has a history of tumor and combined medication ，evaluate the patient’s renal function ，and give preventive measures such as hydration in advance. When using iodine contrast media ，it is necessary to pay attention to the temperature ，dose and injection rate. And medical staff need to follow up the patient ’s situation in time after using iodine contrast media to avoiding the impact of delayed adverse reactions.