Objective To investigate the early warning factors for the efficacy of Conbercept in treating diabetic macular edema(DME)and build a Nomograph prediction model based on the early warning factors.Methods A total of 269 DME patients(269 eyes)treated with Conbercept at Nanchang First Hospital from January 2021 to March 2023 were se-lected and divided into an effective group and an ineffective group according to the therapeutic effect at 3 months after treatment.Single factor analysis was made on the efficacy of Conbercept.The random forest method was used to screen and reduce the dimension of the characteristic variables on the efficacy of Conbercept,Logistic regression was used to ana-lyze the relevant factors affecting the efficacy of Conbercept,and R language was used to draw the Nomograph prediction model on the efficacy of Conbercept.The decision curve analysis(DCA)was made to evaluate the clinical effectiveness of the Nomograph prediction model.Results The duration of diabetes,drinking history,fasting blood glucose,2-hour postprandial blood glucose,and glycosylated hemoglobin of patients in the ineffective group were higher than those in the effective group,while the macular central retinal thickness and vessel density in the foveal retinal deep capillary plexus were lower than those in the effective group(all P＜0.05).According to the random forest algorithm,the top five predic-tive factors for the efficacy of Conbercept were glycosylated hemoglobin,macular central retinal thickness,fasting blood glucose,2-hour postprandial blood glucose,and vessel density in the foveal retinal deep capillary plexus.Logistic regres-sion analysis showed that glycosylated hemoglobin(OR=5.012),fasting blood glucose(OR=3.877),and 2-hour post-prandial blood glucose(OR=4.231)were risk factors for the efficacy of Conbercept,while the macular central retinal thickness(OR=0.409)and vessel density in the foveal retinal deep capillary plexus(OR=0.410)were protective factors for the efficacy of Conbercept(all P＜0.05).The Nomograph showed that the C-index of the prediction model was 0.900(95％CI:0.859-0.941),the sensitivity was 90.58％,and the specificity was 75.64％.The DCA curve showed that using the Nomogram prediction model to predict the efficacy of Conbercept could obtain positive net benefit,suggesting that it had certain clinical effectiveness.Conclusion The efficacy of Conbercept for DME patients is affected by a variety of factors,including glycosylated hemoglobin,fasting blood glucose,2-hour postprandial blood glucose,macular central reti-nal thickness,and vessel density in the foveal retinal deep capillary plexus.The Nomogram model constructed based on the above factors may be used to predict patients'treatment response in early stage,providing evidence for clinical decision-making.

Objective To investigate the changes of macular microcirculation and aqueous humor cytokine expression in patients with diabetic macular edema(DME)after anti-vascular endothelial growth factor(VEGF)treatment,and analyze the relationship with efficacy.Methods A total of 62 patients(91 eyes)with DME who were treated in the First Hospital of Nanchang from October 2021 to August 2023 were selected and treated with intravitreal injection of conbercept.According to the reduction of central macular thickness(CMT),they were divided into efficacy significant group(CMT reduction≥100μm,59 eyes)and non-efficacy significant group(CMT reduction＜100μm or increase,32 eyes).The changes of CMT,vessel density(VD)of superficial capillary plexus(SCP),fovea avascular area(FAZ),VEGF,interleuki(IL)-6,IL-8,and IL-10 after anti-VEGF treatment were analyzed.Receiver operating characteristic(ROC)curve was used to evaluate the predictive value of each index.Results Before treatment,the levels of VEGF and IL-10 in aqueous humor in efficacy significant group were significantly higher than those in non-efficacy significant group,and the level of IL-8 was significantly lower than that in non-efficacy significant group(P＜0.05).After treatment,levels of VEGF,IL-6,IL-8 and IL-10 in aqueous humor in both groups were significantly lower than before treatment(P＜0.05).The levels of VEGF,IL-6 and IL-8 in aqueous humor in efficacy significant group were significantly lower than those in non-efficacy significant group,and the level of IL-10 was significantly higher than that in non-efficacy significant group(P＜0.05).Before and after anti-VEGF treatment,there were no significant changes in FAZ area and SCP-VD in both groups(P＞0.05).Correlation analysis showed that VEGF(r=0.571,P＜0.001)and IL-10(r=0.382,P=0.008)in aqueous humor at baseline were positively correlated with CMT reduction,IL-8 was negatively correlated with CMT reduction(r=-0.689,P＜0.001).IL-6,FAZ area and SCP-VD were not correlated with CMT reduction(P＞0.05).Cytokine levels were not correlated with FAZ area and SCP-VD(P＞0.05).ROC curve results showed that area under the curve of IL-8,VEGF and IL-10 at baseline predicting anti-VEGF efficacy were 0.825,0.813 and 0.676,respectively.Conclusion The levels of VEGF,IL-8,and IL-10 in aqueous humor at baseline in DME patients were correlated with anti-VEGF efficacy and could predict the efficacy of anti-VEGF.

Background::Heterogeneity of tumor cells and the tumor microenvironment (TME) is significantly associated with clinical outcomes and treatment responses in patients with urothelial carcinoma (UC). Comprehensive profiling of the cellular diversity and interactions between malignant cells and TME may clarify the mechanisms underlying UC progression and guide the development of novel therapies. This study aimed to extend our understanding of intra-tumoral heterogeneity and the immunosuppressive TME in UC and provide basic support for the development of novel UC therapies.Methods::Seven patients with UC were included who underwent curative surgery at our hospital between July 2020 and October 2020. We performed single-cell RNA sequencing (scRNA-seq) analysis in seven tumors with six matched adjacent normal tissues and integrated the results with two public scRNA-seq datasets. The functional properties and intercellular interactions between single cells were characterized, and the results were validated using multiplex immunofluorescence staining, flow cytometry, and bulk transcriptomic datasets. All statistical analyses were performed using the R package with two-sided tests. Wilcoxon-rank test, log-rank test, one-way analysis of variance test, and Pearson correlation analysis were used properly.Results::Unsupervised t-distributed stochastic neighbor embedding clustering analysis identified ten main cellular subclusters in urothelial tissues. Of them, seven urothelial subtypes were noted, and malignant urothelial cells were characterized with enhanced cellular proliferation and reduced immunogenicity. CD8 + T cell subclusters exhibited enhanced cellular cytotoxicity activities along with increased exhaustion signature in UC tissues, and the recruitment of CD4 + T regulatory cells was also increased in tumor tissues. Regarding myeloid cells, coordinated reprogramming of infiltrated neutrophils, M2-type polarized macrophages, and LAMP3 + dendritic cells contribute to immunosuppressive TME in UC tissues. Tumor tissues demonstrated enhanced angiogenesis mediated by KDR + endothelial cells and RGS5 +/ACTA2 + pericytes. Through deconvolution analysis, we identified multiple cellular subtypes may influence the programmed death-ligand 1 (PD-L1) immunotherapy response in patients with UC. Conclusion::Our scRNA-seq analysis clarified intra-tumoral heterogeneity and delineated the pro-tumoral and immunosuppressive microenvironment in UC tissues, which may provide novel therapeutic targets.