Objective To construct and verify an early prediction model for visual benefit of diabetic macular edema(DME)after anti-vascular endothelial growth factor(VEGF)treatment based on clinical data,optical coherence tomo-graphy angiography(OCTA),serum brain tissue aquaporin-4(AQP4)mRNA and total bilirubin(TBIL)levels.Methods A total of 480 patients(480 eyes)with DME treated in the First People's Hospital of Zigong City from October 2021 to March 2024 were selected and divided into a modeling set(320 cases)and a validation set(160 cases)at a ratio of 2∶1.According to the visual benefit after anti-VEGF treatment,patients in the modeling set were further divided into a benefit group(80 cases)and a non-benefit group(240 cases).The baseline data of the two groups of patients were collected,and the factors influencing visual benefits in DME patients after anti-VEGF treatment were analyzed.An early prediction model was constructed and validated both internally and externally.Results The inter-group comparison results showed that the diabetes duration in the non-benefit group was longer than that in the benefit group(P＜0.05).The proportion of smokers,the best corrected visual acuity(BCVA),the minimum resolution angle(logMAR)vision,hemoglobin A1c(HbAlc)and AQP4 mRNA levels were higher in the non-benefit group than those in the benefit group(all P＜0.05).The foveal retinal deep capillary plexus blood flow density(DCP-VD),central macular thickness(CMT),and TBIL levels were lower in the non-benefit group than those in the benefit group(all P＜0.05).The least absolute shrinkage and selection operator(LAS-SO)-Logistic regression analysis showed that the factors influencing visual benefit in DME patients after anti-VEGF treat-ment were CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels.The predictive risk con-sistency index of the nomogram model constructed based on the above-mentioned influencing factors for visual benefit pre-diction after anti-VEGF treatment was 0.844.The receiver operating characteristic(ROC)curve showed that the area un-der the ROC curve(AUC)of the model was 0.844(95％ CI:0.797-0.891)in the modeling set and 0.898(95％ CI:0.847-0.949)in the validation set.The decision analysis curve showed that when the high-risk threshold of the modeling set ranged between 0 and 82％ and that of the validation set ranged between 0 and 100％,the model could bring net clinical benefits.Conclusion CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels are the fac-tors influencing visual benefit in DME patients after anti-VEGF treatment.The visual benefit prediction model constructed based on these factors has high accuracy and stability,and can be used as an effective tool for clinical prediction of visual benefit after treatment.

Objective To construct and verify an early prediction model for visual benefit of diabetic macular edema(DME)after anti-vascular endothelial growth factor(VEGF)treatment based on clinical data,optical coherence tomo-graphy angiography(OCTA),serum brain tissue aquaporin-4(AQP4)mRNA and total bilirubin(TBIL)levels.Methods A total of 480 patients(480 eyes)with DME treated in the First People's Hospital of Zigong City from October 2021 to March 2024 were selected and divided into a modeling set(320 cases)and a validation set(160 cases)at a ratio of 2∶1.According to the visual benefit after anti-VEGF treatment,patients in the modeling set were further divided into a benefit group(80 cases)and a non-benefit group(240 cases).The baseline data of the two groups of patients were collected,and the factors influencing visual benefits in DME patients after anti-VEGF treatment were analyzed.An early prediction model was constructed and validated both internally and externally.Results The inter-group comparison results showed that the diabetes duration in the non-benefit group was longer than that in the benefit group(P＜0.05).The proportion of smokers,the best corrected visual acuity(BCVA),the minimum resolution angle(logMAR)vision,hemoglobin A1c(HbAlc)and AQP4 mRNA levels were higher in the non-benefit group than those in the benefit group(all P＜0.05).The foveal retinal deep capillary plexus blood flow density(DCP-VD),central macular thickness(CMT),and TBIL levels were lower in the non-benefit group than those in the benefit group(all P＜0.05).The least absolute shrinkage and selection operator(LAS-SO)-Logistic regression analysis showed that the factors influencing visual benefit in DME patients after anti-VEGF treat-ment were CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels.The predictive risk con-sistency index of the nomogram model constructed based on the above-mentioned influencing factors for visual benefit pre-diction after anti-VEGF treatment was 0.844.The receiver operating characteristic(ROC)curve showed that the area un-der the ROC curve(AUC)of the model was 0.844(95％ CI:0.797-0.891)in the modeling set and 0.898(95％ CI:0.847-0.949)in the validation set.The decision analysis curve showed that when the high-risk threshold of the modeling set ranged between 0 and 82％ and that of the validation set ranged between 0 and 100％,the model could bring net clinical benefits.Conclusion CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels are the fac-tors influencing visual benefit in DME patients after anti-VEGF treatment.The visual benefit prediction model constructed based on these factors has high accuracy and stability,and can be used as an effective tool for clinical prediction of visual benefit after treatment.

Objective To investigate the association between clonal hematopoiesis of indeterminate potential(CHIP)and the severity of coronary artery lesions in coronary heart disease(CHD)patients with renal insufficiency.Methods A case-control trial was conducted on 70 CHD patients with renal insufficiency admitted in Chongqing Emergency Medical Center(Affiliated Central Hospital of Chongqing University)and Department of Cardiovascular Diseases of the First Affiliated Hospital of Chongqing Medical University from December 2023 to July 2024.According to the median Gensini score,they were classified into the Gensini score＜44 group(n=34)and ≥44 group(n=36),and based on carrying CHIP mutation or not,they were divided into CHIP group(n=23)and non-CHIP group(n=47).The differences in clinical data were compared between the above 2 pair groups respectively.Binary logistic regression analysis was used to assess the relationship between CHIP status and the severity of coronary artery lesions.Results Compared with the Gensini score＜44 group,the Gensini score ≥44 group had a higher CHIP carriage rate(17.2％vs 47.6％,P=0.008)as well as NT-proBNP level(767 vs 3 480 ng/L,P=0.039).Binary logistic regression analysis showed that CHIP status was still associated with higher Gensini scores after adjustment of NT-proBNP(OR=3.935,95％CI=1.153～13.435,P=0.029).Further CHIP grouping results suggested that the patients in the CHIP group had higher Gensini score(48 vs 38,P=0.004),larger proportion of 3-vessle disease(52.2％vs 25.5％,P=0.040),and lower left ventricular ejection fraction(55.0％vs 58.0％,P=0.042)than those in the non-CHIP group.Conclusion CHIP is an independent risk factor for severe coronary artery disease in CHD patients with renal insufficiency.

Construction and application of immunization information system is an important part of health information, which is very useful to improve the quality, efficiency and safety of vaccination. The background, system architecture, functions and applications, working conditions and characteristics of Shandong province Immunization Information System (IIS) are introduced in this article. It is expected to provide experiences for the development of immunization information system of other provinces.

Construction and application of immunization information system is an important part of health information, which is very useful to improve the quality, efficiency and safety of vaccination. The background, system architecture, functions and applications, working conditions and characteristics of Shandong province Immunization Information System (IIS) are introduced in this article. It is expected to provide experiences for the development of immunization information system of other provinces.

Construction and application of immunization information system is an important part of health information, which is very useful to improve the quality, efficiency and safety of vaccination. The background, system architecture, functions and applications, working conditions and characteristics of Shandong province Immunization Information System (IIS) are introduced in this article. It is expected to provide experiences for the development of immunization information system of other provinces.

Wnt signaling has emerged as a major regulator of tissue development by governing the self-renewal and maintenance of stem cells in most tissue types. As a key upstream regulator of the Wnt pathway, the transmembrane E3 ligase ZNRF3 has recently been established to play a role in negative regulation of Wnt signaling by targeting Frizzled (FZD) receptor for ubiquitination and degradation. However, the upstream regulation of ZNRF3, in particular the turnover of ZNRF3, is still unclear. Here we report that ZNRF3 is accumulated in the presence of proteasome inhibitor treatment independent of its E3-ubiquitin ligase activity. Furthermore, the Cullin 1-specific SCF complex containing β-TRCP has been identified to directly interact with and ubiquitinate ZNRF3 thereby regulating its protein stability. Similar with the degradation of β-catenin by β-TRCP, ZNRF3 is ubiquitinated by β-TRCP in both CKI-phosphorylation- and degron-dependent manners. Thus, our findings not only identify a novel substrate for β-TRCP oncogenic regulation, but also highlight the dual regulation of Wnt signaling by β-TRCP in a context-dependent manner where β-TRCP negatively regulates Wnt signaling by targeting β-catenin, and positively regulates Wnt signaling by targeting ZNRF3.
Cells, Cultured ; Humans ; Proteolysis ; Ubiquitin-Protein Ligases ; metabolism ; Ubiquitination ; beta-Transducin Repeat-Containing Proteins ; metabolism