Objective To establish the UPLC fingerprint of 10 batches of Gongliuning capsule and the content determination methods of 10 main components;To conduct network pharmacological research;To provide scientific basis for predicting the quality marker of Gongliuning capsule.Methods UPLC-DAD technique was used to establish the fingerprint of different batches of Gongliuning capsule samples and obtain the complete chemical composition information of Gongliuning capsule.With the help of network pharmacological research techniques,the target of chemical components of Gongliuning capsule and related pathways screened from various databases were predicted and analyzed,and the protein interaction network and composition-target-pathway diagram were constructed to predict the effective components of Gongliuning capsule.Based on the obtained pharmacodynamic substances,the content determination method of Gongliuning capsule was established to evaluate the quality of Gongliuning capsule.Results The fingerprints of Gongliuning capsule identified 17 common peaks.Combined with network pharmacology method,the candidate chemical components were analyzed,10 core targets and 42 metabolic pathways were obtained.Based on the testability of components and the availability of reference substances,10 compounds with high contribution were selected for content determination.Methodological verification results showed that all the 10 compounds had good linear relationship(r2>0.999 4)in the detection range,with good precision,accuracy and stability.Conclusion The established UPLC fingerprint,network pharmacology and multiple component content determination methods are highly specific,accurate and reliable.Combined with chemical pattern recognition,they can be effectively used for quality control and quality marker prediction of Gongliuning capsules.

Objective To establish the UPLC fingerprint of 10 batches of Gongliuning capsule and the content determination methods of 10 main components;To conduct network pharmacological research;To provide scientific basis for predicting the quality marker of Gongliuning capsule.Methods UPLC-DAD technique was used to establish the fingerprint of different batches of Gongliuning capsule samples and obtain the complete chemical composition information of Gongliuning capsule.With the help of network pharmacological research techniques,the target of chemical components of Gongliuning capsule and related pathways screened from various databases were predicted and analyzed,and the protein interaction network and composition-target-pathway diagram were constructed to predict the effective components of Gongliuning capsule.Based on the obtained pharmacodynamic substances,the content determination method of Gongliuning capsule was established to evaluate the quality of Gongliuning capsule.Results The fingerprints of Gongliuning capsule identified 17 common peaks.Combined with network pharmacology method,the candidate chemical components were analyzed,10 core targets and 42 metabolic pathways were obtained.Based on the testability of components and the availability of reference substances,10 compounds with high contribution were selected for content determination.Methodological verification results showed that all the 10 compounds had good linear relationship(r2>0.999 4)in the detection range,with good precision,accuracy and stability.Conclusion The established UPLC fingerprint,network pharmacology and multiple component content determination methods are highly specific,accurate and reliable.Combined with chemical pattern recognition,they can be effectively used for quality control and quality marker prediction of Gongliuning capsules.

Objective:To explore the mediating effect of coping style between family function and psychological resilience in patients with diabetes retinopathy (DR) .Methods:From September 2021 to August 2022, 310 DR patients who visited the First Affiliated Hospital of Zhengzhou University were selected as the study subject by convenience sampling. Patients were surveyed using the General Information Questionnaire, Simplified Coping Style Questionnaire (SCSQ) , Family Assessment Device (FAD) , and Connor-Davidson Resilience Scale (CD-RISC) . Pearson correlation was used to analyze the correlation between coping style, family function, and psychological resilience in DR patients. AMOS 21.0 software was used to establish structural equation models and verify mediating effects. A total of 310 questionnaires were distributed, and 297 valid questionnaires were collected, and the effective response rate of the questionnaire was 95.81% (297/310) .Results:Among 297 DR patients, the positive coping dimension score in SCSQ was (14.79±3.58) , while the negative coping dimension score was (16.37±4.02) . the FAD score was (169.28±23.34) . The total score of CD-RISC was (65.62±11.52) . The score of the positive coping dimension was negatively correlated with the FAD score ( P<0.05) , and positively correlated with the total score and each dimension score of CD-RISC ( P<0.05) . The score of negative coping dimension was positively correlated with the score of FAD ( P<0.05) , and negatively correlated with the total score and each dimension score of CD-RISC ( P<0.05) . The FAD score was negatively correlated with the total score and each dimension score of CD-RISC ( P<0.05) . Coping styles played a partial mediating effect between family function and psychological resilience, with the mediating effect accounting for 53.65% of the total effect. Conclusions:DR patients have poor family functional and moderate psychological resilience, and their coping styles tend to be negative. Medical and nursing staff should pay attention to and improve the family function of patients, promote their positive response to diseases, and enhance their family function and psychological resilience.