BACKGROUND:Angiogenesis is the main treatment target of cardiovascular diseases.Bone morphogenetic protein 2 can modulate angiogenesis,but the regulatory effect of endothelial cell-specific bone morphogenetic protein 2 on angiogenesis is unclear. OBJECTIVE:To investigate the effect of endothelial-specific bone morphogenetic protein 2 on angiogenesis. METHODS:(1)Bioinformatics analysis:Cellular expression specificity and abundance of bone morphogenetic protein 2 were meta-analyzed by the PanglaoDB single-cell transcriptome database.The endothelial cell transcriptome sequencing dataset of the mouse hindlimb model and endocardial transcriptome dataset of mice overexpressing bone morphogenetic protein 2 were reanalyzed to evaluate the effect of endothelial cell bone morphogenetic protein 2 on the angiogenesis pathway.(2)Validation in vivo:After establishing the mouse hindlimb model,we compared the blood perfusion between the affected and sham limb at 7,14,and 21 days.The expression of the colocation of bone morphogenetic protein 2 and CD31 was explored by immunofluorescence and immunohistochemical staining.(3)Validation in vitro:The cultured human umbilical vein endothelial cells in vitro were divided into a control group,a hypoxia group,and a bone morphogenetic protein 2 inhibitor Noggin intervention group.After being cultured for 24 hours,the angiogenesis of endothelial cells in each group was observed. RESULTS AND CONCLUSION:(1)Endothelial cells are an important cell subgroup expressing bone morphogenetic protein 2.Both in the mouse hindlimb ischemia model and endocardial cells overexpressing bone morphogenetic protein 2,bone morphogenetic protein 2 was significantly up-regulated,and the angiogenesis pathway was significantly activated.(2)In the mouse hindlimb model,bone morphogenetic protein 2-positive blood vessels around neoangiogenesis increased significantly at 7 days of ischemia(P<0.05),and decreased significantly after 2 weeks of ischemia(P<0.001).(3)In umbilical vein endothelial cells cultured in vitro,after hypoxic intervention,the migration and sprouting of endothelial cells increased significantly,and the expression of angiogenesis factors vascular endothelial growth factor and platelet-derived growth factor was significantly increased.Noggin significantly reduced hypoxia-induced endothelial cell angiogenesis(P<0.001)and down-regulated the expression of vascular endothelial growth factor and platelet-derived growth factor(P<0.01).(4)These findings verify that endothelial cell-specific bone morphogenetic protein 2 can regulate angiogenesis,and targeting endothelial cell bone morphogenetic protein 2 is a promising way to improve angiogenesis.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.

Aim To analyze the risk factor of the cardiac rupture(CR)in patients with acute ST-segment eleva-tion myocardial infarction(STEMI).Based on this,the nomogram model of acute STEMI patients with CR was estab-lished.Methods Through Ningxia Medical University General Hospital's big data research platform and hospital in-formation system retrieval,5 412 patients with acute STEMI from January 2015 to December 2019 were continuously includ-ed in the study,of which 91 patients with CR were included as CR group;5 321 patients non-combined with CR were in-cluded as non-CR group.LASSO regression,univariate and multivariate Logistic regression were used to analyze the risk factors of CR in patients with acute STEMI,and the CR nomogram predictive model was established.The nomogram mod-el was validated and evaluated by using receiver operating characteristic(ROC)curve,Hosmer-Lemeshow test and clinical decision curve analysis(DCA).Results LASSO regression results showed that age,female,hypertension history,first medical contact time,shock index,Killip grade,white blood cell count,d-dimer,lactic acid,anterior myocardial in-farction,β-blocker administration within 24 hours,angiotensin converting enzyme inhibitor/angiotensin receptor antagonist(ACEI/ARB)administration within 24 hours,emergency percutaneous coronary intervention(PCI)were 13 risk factors of CR(P＜0.05).The screened 13 risk factors were analyzed by univariate and multivariate Logistic regression,the results suggested that age,Killip grade,first medical contact time,white blood cell count,not undergoing emergency PCI and not taking ACEI/ARB drugs within 24 hours were the risk factors of CR in patients with acute STEMI.The acute STEMI with CR nomogram model was established according to the above 6 risk variables.The area under the ROC curve before and after the internal verification of the nomogram model was 0.946(95％CI:0.927～0.961),0.947(95％CI:0.927～0.959),and the sensitivity was 0.957 and 0.904,respectively,the specificity was 0.858 and 0.876,respectively,which indicated that the model had good discrimination degree.The Hosmer-Lemeshow test showed that the deviation between the predicted value and the observed value was not statistically significant(x2=12.70,P=0.122),indicating that the no-mogram model had a good calibration.The DCA curve indicated that the predictive probability threshold of the model was from 0.00 to 0.40,and the clinical net benefit was the highest,indicating that the model had good clinical efficacy.Conclusion The nomogram model established in this study has better distinction,calibration and clinical effectiveness.It can effectively predict the probability of acute STEMI with CR,and provide some help for clinical diagnosis and treat-ment,so as to reduce the incidence of CR.

Objective To compare and analyze the differences between customized models and commercial universal models in the segmentation of organs-at-risk in cervical cancer,and to investigate the feasibility of customized models.Methods A retrospective analysis was conducted on 270 cervical cancer patients.Senior clinicians manually delineated organs-at-risk,including the bladder,rectum,small intestine,pelvic bone marrow,femoral heads,and kidneys.The cases were randomly selected to develop customized models,with 202 cases allocated to the training set,38 cases to the test set,and 30 cases to the validation set.The universal and customized models were used for segmentation on the test set,and the automatic segmentation results obtained by the two models were compared with manual segmentation results to assess the performance of the customized model.Results Both customized model and universal model had comparable DSC values to manual segmentation,demonstrating satisfactory delineation outcomes(DSC values ranging from 0.7 to 0.9).However,in terms of deviation of centroid and 95％Hausdorff distance,the customized model surpassed the universal model.Conclusion Compared with the universal model,the customized model offers superior accuracy in delineating the structures of organs-at-risk in cervical cancer.As the customized model is optimized based on specific datasets,it provides precise support for clinical decision-making and holds promising applications in the treatment of cervical cancer.

Objective To explore basement membrane markers and potential drugs for treatment in idiopathic pulmona-ry fibrosis(IPF).Methods IPF-related datasets were downloaded from the Gene Expression Omnibus(GEO)database,processed to construct basement membrane gene expression matrices associated with IPF,and screened for differential basement membrane genes(DEBMs);DEBMs were enriched for function and pathways,and machine learning algorithms were used to ob-tain candidate signature genes,receiver operating characteristic(ROC)curves were used to identify signature genes and con-struct a nomogram.We performed ssGSEA analysis to explore the correlation between signature genes and immune cells and their functions and predicted the corresponding miRNAs and therapeutic drugs by signature genes.Results A total of 56 DEBMs were extracted;enrichment analysis showed that DEBMs were mainly enriched in"extracellular matrix tissue","extracellular structural tissue",etc.,and were closely related to"ECM-receptor interaction"and"local adhesion spot"pathways.The ma-chine learning has identified six candidate signature genes(TIMP3,P3H2,ITGA7,ITGA4,ADAMTS2,COL8A2),all of which meet the requirements of the signature genes by the ROC curve test,and the nomogram diagnostic value was outstanding(AUC=0.991 523);B cells and Macrophages in IPF were significantly different from the normal group.Finally,miRNAs were predicted to be dominated by miR-4305,miR-3684,progesterone,and tert-butyl hydroperoxide as therapeutic agents with strong relevance to IPF.Conclusion Signature genes and predictive miRNAs may serve as novel markers for IPF diagnosis,and pre-dictive drugs may be a potential source of drugs for treating IPF.