Objective To analyze the disease burden and trends of bladder cancer in China and globally from 1992 to 2021.  Methods Using the GBD 2021 database, the incidence, prevalence, mortality, and disability-adjusted life years (DALYs) rates of bladder cancer in China and globally from 1992–2021 were analyzed. Average annual percentage change (AAPC) was calculated using Joinpoint regression. Subgroup analyses by sex and age were conducted, and a Bayesian age-period-cohort (BAPC) model was used to predict trends in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) for the next 15 years.  Results In 2021, China reported 106 000 new cases (ASIR: 5.14/100 000), 571 000 prevalent cases (age-standardized prevalence rate, ASPR: 26.61/100 000), 43 000 deaths (ASMR: 2.34/100 000), and a DALY rate of 45.31/100 000. From 1992–2021, China showed upward trends in ASIR and ASPR but declines in ASMR and DALYs, while global ASIR, ASMR, and DALYs decreased overall with slow ASPR growth. The peak cases in China and globally were both concentrated in the 65-79 age group, with a significantly higher burden on males than females. In China, smoking-related ASMR and ASDR exceeded global averages and rose, whereas high glucose-related indexes were lower and declined. Projections for 2021–2036 indicated that the global incidence and mortality rates would be rising, but ASIR/ASPR would be declining, while in China, the incidence rate would continue to rise, and the mortality rate will stabilize, with a significant increase in ASIR and a gradual decrease in ASPR.  Conclusion From 1992 to 2021, the incidence of bladder cancer in China has shown a continuous upward trend and is projected to persist in the future, with significant gender and age differences. Particular attention should be given to elderly males aged 85-89. The disease burden of bladder cancer attributable to smoking continues to rise, highlighting the urgent need to strengthen tobacco control policies.

Objective:To analyze the prevalence trends and epidemiological characteristics of cardiometabolic multimorbidity(CMM) in Beijing from 2005 to 2022.Methods:A series of representative cross-sectional surveys were conducted in Beijing between 2005 and 2022 using a stratified multistage cluster random sampling method. A total of 110 496 permanent residents aged 18-79 years participated in face-to-face interviews, physical examinations, and laboratory testing. Complex sampling logistic regression models were employed to identify factors associated with CMM, and Joinpoint regression was used to assess temporal trends in prevalence. Results:The prevalence of CMM was 22.3% in 2005 and 24.3% in 2022, with an average annual percent change of 0.1%(95% CI -1.3%-1.3%, P>0.05). In rural areas, the prevalence increased by 1.3% per year(95% CI 0.2%-2.6%, P<0.05), while among obese individuals, it decreased by 1.0% annually( P<0.05). The most common CMM patterns were hypertension combined with dyslipidemia(13.2%), hypertension combined with diabetes(7.0%), and diabetes combined with dyslipidemia(5.8%). The prevalence of hypertension and dyslipidemia comorbidity showed a long-term decline among females, those aged 60-79 and obese individuals( P<0.05). In contrast, the prevalence of hypertension and diabetes comorbidity increased over time in rural residents and individuals with normal body weight( P<0.05). Furthermore, diabetes and dyslipidemia comorbidity rates increased significantly among males, adults aged 18-59 years, those with a college education or above, rural residents and individuals with normal body weight( P<0.05). Multivariable logistic regression indicated that male, older age, overweight, obese, and lower education level were independently associated with a higher risk of CMM( P<0.05). Conclusion:From 2005 to 2022, the prevalence of CMM remained high among adults in Beijing. While prevalence decreased among obese individuals, it increased significantly in rural areas. Hypertension combined with dyslipidemia was the most common multimorbidity pattern throughout the study period.

Objective:To develop an intelligent recognition and precise segmentation technique using ultrasonic images，and to enhance diagnostic efficiency and accuracy.Methods:A total of 1，430 patients diagnosed with uterine fibroids through transvaginal ultrasonography at the Maternal and Child Health Hospital of Guangming from November 2020 to October 2024 were retrospectively included. Ultrasonic images were manually annotated by two experienced physicians and reviewed by a senior expert. The Mask DINO deep learning model was used for lesion segmentation，and the segmentation results were optimized using ellipse fitting technology. Model performance was evaluated using the Dice coefficient，intraclass correlation coefficient（ICC），mean absolute error（MAE），and measurement accuracy.Results:In the test set of 286 cases，the average Dice coefficient of model prediction was 0.992，indicating extremely high segmentation accuracy. The average accuracy of lesion identification by the model was 0.909，with 241 correctly identified samples，19 basically correct samples，and 26 incorrect samples. In terms of long and short axis measurements，the ICC of the model's direct predictions were 0.871（short axis）and 0.784（long axis），with MAE of 0.436 cm（short axis）and 0.508 cm（long axis）. After optimization with ellipse fitting，the ICC increased to 0.893（short axis）and 0.866（long axis），and the MAE decreased to 0.191 cm（short axis）and 0.274 cm（long axis），the measurement accuracy improved significantly.Conclusions:The intelligent recognition and precise segmentation technique for uterine fibroids based on ultrasonic images constructed in this study performed excellently in lesion segmentation and measurement，it can significantly improve the efficiency and accuracy of diagnosis.

Objective To analyze the willingness and influencing factors of doctors in Beijing public hospitals to set up clinics in the community,and to provide scientific basis for promoting quality health technicians to go down to the grassroots and realize hierarchical diagnosis and treatment.Methods Doctors from 6 specialized hospita ls and 3 general hospitals in Beijing were selected as subjects for questionnaire survey.By stratified sampling,a questionnaire survey was conducted on 518 doctors from 9 public hospitals in Beijing through stratified sampling method.Descriptive analysis,rank sum test and ordered logistic regression were used to explore doctors'willingness to open clinics and its influencing factors.Results In all survey respondents,212(40.93%)physicians were very or somewhat willing to open a clinic in the community,physicians with higher benefit perception,and greater willingness to publicize relevant policies were more willing to set up clinics.Conclusion Opening of clinics by doctors in public hospitals is affected by perceived benefits and willingness to advocate policies.It is suggested to further improve relevant systems and policies,reduce the risk of doctors opening clinics,and promote doctors in public hospitals to open clinics in communities,so as to realize the sinking of high-quality health human resources to the grassroots.

Objective:To investigate the views of doctors on the incidence and treatment tactics of mild progression after epithelial growth factor receptor tyrosine kinase inhibitor(EGFR-TKI)treatment in lung adenocarcinoma and provide suggestions to optimize the counter-measure strategies.Methods:Convenience sampling was used to conduct an online questionnaire survey for doctors specializing in onco-logy and respiratory diseases.Results:584 valid questionnaires were collected,and all the doctors expressed concerns regarding mild tumor progression after EGFR-TKI treatment.The coping strategies included maintaining the original TKI treatment,adding other treatments to the original TKI,changing the regimen,and performing secondary tissue biopsy,among which,most doctors chose to add other treatments to the original TKI.Conclusions:Doctors have noticed the enlargement of target lesions in still stable disease(SD)and most frequently chose to add other treatments to the original TKI as a coping strategy.This finding can provide a reference for framing future guidelines for large sample prospective clinical studies that are needed to find the most effective synergistic treatment options.

Objective To analyze the influencing factors of hepatic encephalopathy(HE)after transjugular intrahepatic portosystemic shunt(TIPS)and construct a nomogram prediction model based on these factors.Methods A total of 290 patients with cirrhotic portal hypertensive variceal gastrointestinal bleeding in the Yuncheng Central Hospital Affiliated to Shanxi Medical University from January 2019 to December 2023 were selected and randomly divided into training set of 145 cases and validation set of 145 cases.All patients underwent TIPS treatment,and the incidence of HE within 3 months after TIPS was recorded.In the training set,patients were divided into HE group(n=42)and non-HE group(n=103)based on the occurrence of HE.Clinical materials were compared between the two groups,and Lasso-Logistic regression analysis was applied to explore the influencing factors of HE after TIPS.A nomogram prediction model was constructed based on the influencing factors and validated in both the training set and the validation set for its clinical value in predicting HE after TIPS.Results The overall incidence of HE was 29.31％,with incidence rates of 28.97％and 29.66％respectively in the training set and the validation set.In the training set,the HE group had significantly higher age,C grading of preoperative Child-Pugh ratio,diabetes mellitus ratio,total bilirubin(TBIL),prothrombin time(PT),serum sodium,serum creatinine,interleukin-6(IL-6),interleukin-18(IL-18),blood ammonia,monocyte chemotactic protein-1(MCP-1),postoperative portal venous pressure,and intestinal flora disturbance ratio when compared to the non-HE group,while the preoperative glial fibrillary acidic protein(GFAP)level was significantly lower in the HE group(P＜0.05).Lasso-Logistic regression analysis showed that preoperative C grading of Child-Pugh grading,diabetes mellitus,TBIL,PT,IL-6,IL-18,blood ammonia,GFAP,MCP-1 level,and postoperative intestinal flora disturbance were influencing factors for HE after TIPS(P＜0.05).A nomogram prediction model was constructed based on ten influencing factors selected by Lasso-Logistic regression analysis.The area under the curve(AUC)of this model for predicting HE after TIPS was 0.933(95％CI,0.889 to 0.976)in the training set and 0.944(95％CI,0.893 to 0.995)in the valida-tion set,with good consistency between the model's prediction and actual observation.Conclusion The nomogram prediction model for HE after TIPS,constructed based on the influencing factors selected by Lasso-Logistic regression analysis,has high predictive efficacy and accuracy.

Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.

Objective To evaluate the association between self-reported neighborhood walkability environments and mortality in China.Methods The Prospective Urban Rural Epidemiology study in China(PURE-China)recruited 47 931 participants aged 35-70 from 12 provinces in China between 2005 and 2009.Neighborhood environmental indicators were collected using the Neighborhood Environment Walkability Scale(NEWS)questionnaire,with higher scores indicating better walkable environments.The primary outcomes were all-cause mortality and cardiovascular mortality,using Cox fragile model to evaluate the association between community walkability and outcomes,as well as exploring mediating pathways.Results Of 35 490 participants included in this study,60%were female,with a mean(SD)age of 51.5(9.6)years.The median follow-up was 11.7 years.This study found an association between higher community walkability score and reduced risk of all-cause mortality,with the total score(HR=0.85;95%CI,0.80-0.89),land-use mix(HR=0.84;95%CI,0.79-0.88),and crime safety(HR=0.84;95%CI,0.80-0.89)showing the most significant associations.NEWS can affect long-term adverse outcomes through lifestyle.Conclusions In the Chinese population,favorable community walkability is associated with lower all-cause mortality risk,which may support policymakers to take actions to mitigate the adverse effects of poor community en-vironments on health.

Objective To analyze the effect of Hsa-circ-0101216 on gemcitabine(GEM)chemotherapy resistance in pancreatic cancer and its mechanism.Methods Differentially expressed circRNAs between GEM-resistant pancreatic cancer cells and parent cells were screened using the GEO database.Pancreatic cancer GEM resistant cell lines(BxPC-3-GEM and Capan-1-GEM)were constructed by intermittent concentration gradient method.qRT-PCR was used to detect the expression of Hsa-circ-0101216 in cells.GEM resistant pancreatic cancer cell lines were taken and divided into sh-circ-0101216 group(knockdown of circ-0101216),sh-NC group(transfected with sh-NC),and blank control group(untreated).CCK-8 assay and EdU proliferation assay were used to detect the half inhibitory concentration(IC50)of GEM and proliferation ability of cells in each group.Western blotting was performed to detect the expression of multidrug resistance-related protein 1(MRP1),breast cancer resistance protein(BCRP),and human equilibrative nucleoside transporter-1(hENT-1).A subcutaneous xenograft tumor model of human pancreatic cancer in nude mice was constructed,and sh-NC+GEM group and sh-circ-0101216+GEM group(n=6)were set up.The volume and weight of xenograft tumor in nude mice were compared between the two groups.Western blotting and immunohistochemistry were used to detect the expression of MRP1,BCRP,and hENT-1 proteins in xenograft tumor tissues,and EDU proliferation assay was used to detect the proliferation ability of tumor cells.Results The GEO database screening showed that Hsa-circ-0101216 was up-regulated in GEM-resistant pancreatic cancer cell lines.Pancreatic cancer GEM-resistant cell lines were successfully constructed,and the expression levels of Hsa-circ-0101216 and the IC50 value in GEM-resistant pancreatic cancer cells BxPC-3-GEM and Capan-1-GEM were significantly higher than those in parental cells(P<0.05).In sh-circ-0101216 group,the IC50 values of GEM,cell viability,EdU positivity rate,and the expression levels of MRP1 and BCRP proteins in GEM-resistant pancreatic cancer cells BxPC-3-GEM and Capan-1-GEM were significantly lower than those in blank control group and sh-NC group,while the expression level of hENT-1 protein was significantly higher(P<0.05 or P<0.001).In sh-circ-0101216+GEM group,the weight and volume of subcutaneous xenograft tumors in nude mice,the expression levels and positive expression rates of MRP1 and BCRP proteins in tumor tissues,and the EdU positive rate were significantly lower than those in sh-NC+GEM group,while the expression level and positive expression rate of hENT-1 protein were significantly higher(P<0.05).Conclusions Hsa-circ-0101216 is highly expressed in GEM-resistant pancreatic cancer cell lines.Its knockdown can inhibit the proliferation of pancreatic cancer cells and enhance the chemosensitivity of pancreatic cancer cells to GEM.The mechanism may be related to the regulation of transmembrane transporter protein expression.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.