Traditional scientific research management suffers from problems such as scattered archives,lack of effective dynamic process supervision for projects,weak data analysis capabilities,and low sharing,making it difficult to meet the unified management of multiple hospital areas in medical groups and the independent management of each branch.The group has devel-oped an intelligent scientific research management system based on artificial big data by constructing the framework and designing the content of various demand modules for scientific research management.This system achieves full coverage management of sci-entific research activities,designing interrelated information data networks for scientific research project process management,a-chievement management,academic(specialized)construction management,postdoctoral management,etc.,realizing informa-tionization and refined management of multiple campuses within the group.Analyze the technological values of each hospital,de-partment,and personnel to provide powerful reference for decision-makers.The information-based scientific research manage-ment system is an important guarantee for hospital groups to intelligently manage and efficiently carry out scientific research work.

Traditional scientific research management suffers from problems such as scattered archives,lack of effective dynamic process supervision for projects,weak data analysis capabilities,and low sharing,making it difficult to meet the unified management of multiple hospital areas in medical groups and the independent management of each branch.The group has devel-oped an intelligent scientific research management system based on artificial big data by constructing the framework and designing the content of various demand modules for scientific research management.This system achieves full coverage management of sci-entific research activities,designing interrelated information data networks for scientific research project process management,a-chievement management,academic(specialized)construction management,postdoctoral management,etc.,realizing informa-tionization and refined management of multiple campuses within the group.Analyze the technological values of each hospital,de-partment,and personnel to provide powerful reference for decision-makers.The information-based scientific research manage-ment system is an important guarantee for hospital groups to intelligently manage and efficiently carry out scientific research work.

Objective To analyze the influencing factors of sleep disorders in the patients with breast cancer.Methods A total of 96 patients with breast cancer treated in this hospital from February 2021 to De-cember 2021 were selected and divided into the non-sleep disorder group and sleep disorder group according to whether or not having sleep disorders.The clinical characteristic data were compared between the two groups.The multivariate Logistic regression was used to analyze the influencing factors of sleep disorders in the pa-tients with breast cancer.Results Among 96 patients with breast cancer,60 cases had no sleep disorders,while 36 cases had sleep disorders.The age,disease stage,marital status,education level,economic income,self-rating anxiety scale(SAS)score and self-rating depression scale(SDS)score had statistical differences between the two groups(P＜0.05).The results of multivariate logistic regression analysis revealed that the age,disease stage,marital status,education level,economic income status,SAS score and SDS score were the influential factors of sleep disorders occurrence in the patients with breast cancer(P＜0.05).Conclusion The sleep situation in the patients with breast cancer cannot be ignored and is related to many factors.Targeted and effective interventions are needed to improve the quality of life of the patients.

To investigate the effects of sanguinarine (Sang) combined with cisplatin (Cis) in accelerating the apoptosis of bladder cancer EJ cells, CCK-8 method was used to detect the proliferation of bladder cancer EJ cells treated with different concentrations of Sang with the IC50 values calculated. Annexin V FITC/PI method was used to detect cell apoptosis in the control group, Sang group, Cis group and the combination group. Flow cytometer was used to detect cell cycle arrested. Western blot was used to detect the influence of Bcl-2 expression in the control group, Sang group, Cis group and the combination group. Nude mouse subcutaneous tumor model was constructed to verify that the combination group could accelerate the apoptosis of bladder cancer EJ cells and reduce the side-effects on mice. The safety of the Sang was evaluated by HE staining of vital organs in mice. In vitro, Sang could significantly inhibit the proliferation of EJ cells. Compared with the control group, the number of apoptosis EJ cells in the combination group was significantly increased (P < 0.05), and more cells were arrested in G2/M phase. The expression of Bcl-2 was significantly down-regulated in the combination group (P <0.001). In vivo, compared with the control group, the tumor growth was significantly slower, and a large number of apoptotic cells were inspected (P < 0.05) of the combination group. The side effects of cisplatin were reduced in the combination group. Sang has high biosafety and little side effect. Combined Sang and Cis can increase cell cycle G2/M block, down-regulate Bcl-2 expression, promote cell apoptosis and inhibit tumor growth.

In order to find the cardiotonic constituents of lateral roots of Aconitum carmichaelii Debx., the investigation was carried out. Silica gel column chromatography, Sephadex LH-20, medium-pressure MCI and reverse phase ODS column chromatography were used to separate the 90% EtOH extract of the lateral roots of Aconitum carmichaelii Debx. The structures of the isolated compounds have been identified by chemical properties and spectroscopic analyses. Ten compounds were isolated and their structures were elucidated as benzoic acid-5-hydroxy-2-benzoyl-amino methyl ester (1), honokiol (2), pinoresinol (3), salicylic acid (4), p-hydroxy-cinnamic acid (5), songorine (6), karakoline (7), mesaconitine (8), hypaconitine (9) and 14-benzoylhypaconitine (10), separetely. Compound 1 is a new compound and its structure has been established by NMR, HR-ESI-MS, UV, IR and X-Ray. Compound 2-5 are isolated from the lateral roots of Aconitum carmichaelii Debx. for the first time.