Dendritic cells (DCs) serve as the primary antigen-presenting cells in autoimmune diseases, like rheumatoid arthritis (RA), and exhibit distinct signaling profiles due to antigenic diversity. Type II collagen (CII) has been recognized as an RA-specific antigen; however, little is known about CII-stimulated DCs, limiting the development of RA-specific therapeutic interventions. In this study, we show that CII-stimulated DCs display a preferential gene expression profile associated with migration, offering a new perspective for targeting DC migration in RA treatment. Then, saikosaponin D (SSD) was identified as a compound capable of blocking CII-induced DC migration and effectively ameliorating arthritis. Optineurin (OPTN) is further revealed as a potential SSD target, with Optn deletion impairing CII-pulsed DC migration without affecting maturation. Function analyses uncover that OPTN prevents the proteasomal transport and ubiquitin-dependent degradation of C-C chemokine receptor 7 (CCR7), a pivotal chemokine receptor in DC migration. Optn-deficient DCs exhibit reduced CCR7 expression, leading to slower migration in CII-surrounded environment, thus alleviating arthritis progression. Our findings underscore the significance of antigen-specific DC activation in RA and suggest OPTN is a crucial regulator of CII-specific DC migration. OPTN emerges as a promising drug target for RA, potentially offering significant value for the therapeutic management of RA.

Objective:To investigate the epidemiological characteristics of herpangina (HA) and its correlation with the incidence of hand, foot and mouth disease (HFMD) in children aged ≤6 years in Yinzhou District of Ningbo from 2017 to 2022.Methods:Epidemiological characteristics of HA in children aged ≤6 years were analyzed based on the electronic medical record data and public health management data from 2017 to 2022 collected from the Health Information Platform of Yinzhou. The incidence of HFMD was calculated using the infectious disease reporting data from the public health management data. Autoregressive integrated moving average model and cross-correlation function were used to evaluate the correlation between the incidence of HA and HFMD.Results:From 2017 to 2022, a total of 25 385 cases of HA were detected in children aged ≤6 years in Yinzhou, the male-to-female ratio of the cases was 1.12∶1. The average annual incidence of HA was 4 986.67/100 000, with the highest incidence in 2018 (10 477.09/100 000) and the lowest incidence in 2020 (870.88/100 000). The incidence peak of HA was during June to July. The incidence of HA was higher in age group 1 year (7 950.45/100 000) than in other age groups. The incidences of HA in Yunlong, Jiangshan and Xiaying were higher, with the incidence of 8 764.31/100 000, 8 377.58/100 000 and 7 965.31/100 000, respectively. The correlation coefficients between the incidence of HA and HFMD at lag day 0, 7, 12 and 18 were 0.199, 0.139, 0.090 and 0.086, respectively (all P<0.05). Conclusions:From 2017 to 2022, the incidence of HA was high in children aged ≤6 years in Yinzhou with obvious seasonality and area difference. The incidence of HA was correlated with the incidence of HFMD and the incidence of HFMD had certain lags. The comprehensive prevention and control of HA and HFMD should be further strengthened by prioritizing HA surveillance and implementing integrated surveillance and management of HA and HFMD.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To understand the current status of gastroscopy in diagnosing gastric lesions in general population, and to recommend the optimal age for the first gastroscopy and intervals for repeated gastroscopy.Methods:The gastroscopy records of residents aged 18-80 years in Yinzhou District of Ningbo, Zhejiang Province, between April 2010 and December 2021 were analyzed retrospectively. The detections of gastric lesions across different years, age and genders were described. Goodness of fit tests were applied to compare the differences in detection rates of different lesions in first-time endoscopy in different age groups and different populations. Generalized additive models were used to fit the trend of age specific gastric lesion detection rate explore the optimal age for gastroscopy. The appropriate gastroscopy intervals were determined according to the progress of the gastric lesions detected in repeated gastroscopy.Results:A total of 237 751 participants with 344 398 gastroscopy records were included in analyses. A total of 5 597 cases of chronic atrophic gastritis (CAG), 9 796 cases of intestinal metaplasia (IM), 165 cases of low-grade intraepithelial neoplasia (LGIN), 52 cases of high-grade intraepithelial neoplasia (HGIN) and 435 cases of gastric cancer were detected by the first gastroscopy. The overall detection rate of gastric lesions increased significantly in age group 45-70 years, and remained stable after 70 years old, with LGIN and HGIN showing notable increases at 50 and 55 years old, respectively. Repeated gastroscopy detected CAG, IM, LGIN, and HGIN at a higher rate compared with the first gastroscopy. Normal/superficial gastritis progressed in 3-5 years, whereas CAG or more severe lesions progressed in 1-6 years.Conclusion:Gastroscopy is recommended for general population aged 45 years and above. Furthermore, gastroscopy can be performed every 3-5 years for individuals with normal endoscopy results and once a year for patients with CAG or more severe gastric lesions.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Background and purpose:Limbs soft tissue sarcoma(STS)is a common malignant tumor,and surgical resection is the main treatment method for it.The concept of barrier made us realize the blocking effect of natural barrier on STS,and we aimed to search for tissues that can act as barrier,and to perform complete resection of surgical margins around the tissue barrier.This study aimed to investigate the feasibility,safety and prognosis of barrier resection in the treatment of limbs STS.Methods:From December 2013 to September 2016,data of 72 patients who underwent barrier resection of STS of extremities in department of oncosurgery,Minhang Branch,Fudan University Shanghai Cancer Center were retrospectively analyzed,and the resection margin was sampled.All 72 patients underwent preoperative magnetic resonance imaging(MRI)or computed tomography(CT)design,and the physiological barrier or at least 3 cm distance was found outward from the anatomical location of the tumor.And en bloc excision was performed outside this barrier or at a distance of 3 cm.The influence of postoperative pathological margin,musculoskeletal tumor society(MSTS)score and postoperative complications on the patients were analyzed.The 1-and 3-year locoregional recurrence-free survival(LRFS)rates and sarcoma-specific survival(SSS)rates were evaluated,and the influencing factors were analyzed.This study was approved by the Ethics Committee of Fudan University Shanghai Cancer Center(number:1212117-12&1212117-12-1301).Results:All patients had negative margins.The 1-and 3-year LRFS rates were 98.2%and 93.3%,respectively.The 1-and 3-year SSS rates were 98.4%and 94.2%,respectively.The mean MSTS scores were 28.3 preoperatively and 25.5 postoperatively.Surgical complications were grade 1 to 2 in 20 cases and grade 3 in 1 case,and there were no grade 4 to 5 complications.Conclusion:Based on the combination of clinical,imaging and pathology data,barrier resection,including tumor resection and functional reconstruction,can be applied to the surgical treatment of STS,with good feasibility and safety,reliable margin and satisfactory local control.

The treatment of glioblastoma, the most prevalent malignant tumor in the central nervous system, poses considerable challenges. Glioblastoma multiforme, classified as a grade Ⅳ highly malignant brain glioma by the World Health Organization, is typically managed through a combination of surgery, postoperative chemotherapy, and radiotherapy. The treatment of glioblastoma is complicated by its infiltrative nature, genetic heterogeneity, and presence of the blood-brain barrier. Almost all cases of glioblastoma experience recurrence despite aggressive therapy, exploring the development of updated molecular treatment strategies that can improve overall efficacy. A crucial aspect in modern neurosurgery is the precise delineation of brain regions in terms of their anatomy and function. It serves as the fundamental basis for investigating variations in the distribution of brain gliomas. Hence, this review will elucidate the origin of glioblastomas and analyze the potential factors contributing to the spatially specific distribution of gliomas on the basis of a theoretical framework of brain connectomics research. Molecular characteristics, information pathways, tumor microenvironment landscape, and immunology will inform the analysis. We aim to identify novel biomolecular targets and therapeutic pathways to gain scientific insights for effective glioblastoma treatment.

Objective To investigate the differences and the immunocompatibility of wild-type (WT), four-gene modified (TKO/hCD55) and six-gene modified (TKO/hCD55/hCD46/hTBM) pig erythrocytes with human serum. Methods The blood samples were collected from 20 volunteers with different blood groups. WT, TKO/hCD55, TKO/hCD55/hCD46/hTBM pig erythrocytes, ABO-compatible (ABO-C) and ABO-incompatible (ABO-I) human erythrocytes were exposed to human serum of different blood groups, respectively. The blood agglutination and antigen-antibody binding levels (IgG, IgM) and complement-dependent cytotoxicity were detected. The immunocompatibility of two types of genetically modified pig erythrocytes with human serum was evaluated. Results No significant blood agglutination was observed in the ABO-C group. The blood agglutination levels in the WT and ABO-I groups were higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (all P<0.001). The level of erythrocyte lysis in the WT group was higher than those in the ABO-C, TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups. The level of erythrocyte lysis in the ABO-I group was higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (both P<0.01). The pig erythrocyte binding level with IgM and IgG in the TKO/hCD55 group was lower than those in the WT and ABO-I groups. The pig erythrocyte binding level with IgG and IgM in the TKO/hCD55/hCD46/hTBM group was lower than that in the WT group and pig erythrocyte binding level with IgG was lower than that in the ABO-I group (all P<0.05). Conclusions The immunocompatibility of genetically modified pig erythrocytes is better than that of wild-type pigs and close to that of ABO-C pigs. Humanized pig erythrocytes may be considered as a blood source when blood sources are extremely scarce.

Head and neck malignant tumor is one of the most heterogeneous diseases.The multi-disciplinary team(MDT)is an essen-tial component for personal precise diagnosis,treatment and integrated care management of oncologic diseases including head and neck malignant tumor.MDT clinical practice is also an important teaching mode for head and neck malignant tumors,but it is limited by time and space in actual teaching.An internet visualization platform was constructed based on the Internet,hospital HIS/PACS/LIS/EMR system,medical visualization screen,oral endoscope,remote consultation platform and other accessible audio and video terminals,and has been applied in MDT clinical teaching of head and neck malignant tumors,allowing medical students to participate in MDT through a networked visualization platform.Medical students will achieve deep learning for the most heterogeneous malignant tumor.MDT sup-ported by the internet visualization platform provides a new pathway for clinical medical education.