ObjectiveTo evaluate the effectiveness of stone needle thermocompression and massage compared to flurbiprofen gel patch in relieving chronic musculoskeletal pain in the shoulder and back， and to explore the potential mediating mechanism through muscle elasticity. MethodsA total of 120 patients with chronic musculoskeletal pain in the shoulder and back were randomly assigned to either stone needle group or flurbiprofen group， with 60 patients in each. The stone needle group received stone needle thermocompression and massage for 30 minutes， three times per week； the flurbiprofen group received flurbiprofen gel patch twice daily. Both groups were treated for 2 weeks. Pain improvement， as the primary outcome， was assessed using the Global Pain Scale （GPS） at baseline， after 2 weeks of treatment， and again 2 weeks post-treatment. To explore potential mechanisms， a mediator analysis was conducted by measuring changes in superficial and deep muscle elasticity using musculoskeletal ultrasound at baseline and after the 2-week treatment period. ResultsThe stone needle group showed significantly greater pain relief than the flurbiprofen group 2 weeks post-treatment. After adjusting for confounders related to pain duration， the between-group mean difference was -8.8 ［95% CI （-18.2， -0.7）， P＜0.05］. Part of the therapeutic effect was mediated by changes in deep muscle elasticity， with a mediation effect size of -1.5 ［95% CI （-2.0， -0.9）， P = 0.024］， accounting for 17.9% of the total effect. ConclusionStone needle thermocompression and massage can effectively relieve chronic musculoskeletal pain in the shoulder and back， partly through a mediating effect of improved deep muscle elasticity.

Objective　To understand the serotypes and sources of dengue virus (DENV) in Yunnan Province in 2023, providing a scientific basis for dengue fever prevention and control. Methods DENV nucleic acid testing and virus isolation were performed on the serum samples of dengue fever cases diagnosed at three national monitoring sites in Yunnan Province (Longchuan County, Menghai County, Hekou County) in 2023. Dengue virus envelope (E) gene sequencing was performed on positive serum samples and dengue virus isolates, and phylogenetic analysis was conducted using molecular biology software. Results A total of 1 006 dengue fever cases were reported at three monitoring sites in 2023, including 838 imported cases, 161 cases imported from other counties and cities in Yunnan, and 7 autochthonous cases. Among 371 serum samples, 351 were found DENV-positive, including 305 DENV-1 positive samples (174 imported from Myanmar, 1 imported from Laos, 1 imported from Vietnam, 99 imported from Jinghong, 26 imported from Ruili, and 4 local cases), 43 DENV-2 positive samples (8 imported from Myanmar, 6 imported from Jinghong, 26 imported from Ruili, and 3 local cases), 1 DENV-3 positive sample (imported from Myanmar), 1 DENV-4 positive sample (introduced from Ruili), and 1 untyped case. A total of 23 DENV strains were isolated, including 9 strains of DENV-1, 12 strains of DENV-2, 1 strain of DENV-3, and 1 strain of DENV-4. All DENV-1 strains from three monitoring sites belong to genotype I but were located on different evolutionary branches. The DENV-2 strains from Menghai County and Longchuan County belonged to the Cosmopolitan genotype and Asian I genotype, respectively. The DENV-3 strain from Longchuan County belonged to genotype I, and the DENV-4 strain from Longchuan County belonged to genotype I. Conclusions During the dengue fever epidemic season, the border regions of Yunnan Province face dual pressures from both international and domestic imported dengue cases. Imported or introduced cases carried DENVs of serotypes 1-4 (with five genotypes in total), leading to local outbreaks caused by these cases. Imported and local DENVs originated from Southeast Asian countries and exhibited distinct geographic distribution characteristics.

Gastric cancer is a high-incidence malignancy that poses a serious threat to public health in China, ranking among the top three cancers in both incidence and mortality. The majority of patients are diagnosed at an advanced stage, resulting in limited treatment options and poor prognosis. To address key challenges in gastric cancer diagnosis and treatment, a research team led by Professor Jiafu Ji at Peking University Cancer Hospital has focused on the project "Development and Dissemination of Precision Medicine Approaches in Gastric Cancer Management". Through a series of high-quality multicenter clinical studies, the team established a set of new international standards in perioperative treatment, individua-lized drug selection, intelligent noninvasive diagnostics, and novel immunotherapy strategies. These advances have significantly improved treatment efficacy and reduced surgical trauma, achieving key technological breakthroughs in diagnosis, therapy, and mechanistic understanding, and systematically enhancing outcomes for gastric cancer patients. The project ' s findings had a broad international impact, including hosting China ' s first International Gastric Cancer Congress. Through nationwide dissemination, they have promoted the development of precision diagnosis and treatment of gastric cancer as a discipline, and led the formulation of the National Health Commission's guidelines for gastric cancer diagnosis and treatment. In recognition of its achievements, the project was awarded the First Prize of the 2024 Chinese Medical Science and Technology Award.
Stomach Neoplasms/genetics* ; Humans ; Precision Medicine/methods* ; China ; Immunotherapy/methods*

Most cancers are currently incurable, partly due to abnormal post-translational modifications (PTMs). In this study, we initially used multiple myeloma (MM) as a working model and found that SUMOylation activating enzyme subunit 1 (SAE1) promotes the malignancy of MM. Through proteome microarray analysis, SAE1 was identified as a potential target for bioactive colcemid or its derivative colchicine. Elevated levels of SAE1 were associated with poor clinical survival and increased MM proliferation in vitro and in vivo. Additionally, SAE1 directly SUMOylated and upregulated the total protein expression of p27, leading to LLPS-mediated nuclear export of p27. Our study also demonstrated the involvement of SAE1 in other types of cancer cells, and provided the first monomer crystal structure of SAE1 and its key binding model with colchicine. Colchicine also showed promising results in the Patient-Derived Tumor Xenograft (PDX) model. Furthermore, a controlled clinical trial with 56 MM patients demonstrated the clinical efficacy of colchicine. Our findings reveal a novel mechanism by which tumor cells evade p27-induced cellular growth arrest through p27 SUMOylation-mediated nuclear export. SAE1 may serve as a promising therapeutic target, and colchicine may be a potential treatment option for multiple types of cancer in clinical settings.

OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers. METHODS: Based on the endoscopic appearance of peptic ulcers, color features were extracted to distinguish active bleeding (Forrest I) from non-bleeding ulcers (Forrest II and III). The edge and texture features were used to describe the morphology and appearance of the ulcers in different grades. By integrating deep features extracted from a deep learning network with manually extracted visual features, a multi-feature representation of endoscopic images was created to predict the risk of rebleeding of peptic ulcers. RESULTS: In a dataset consisting of 3573 images from 708 patients with Forrest classification, the proposed multi-feature fusion model achieved an accuracy of 74.94% in the 6-level rebleeding risk classification task, outperforming the experienced physicians who had a classification accuracy of 59.9% (P<0.05). The F1 scores of the model for identifying Forrest Ib, IIa, and III ulcers were 90.16%, 75.44%, and 77.13%, respectively, demonstrating particularly good performance of the model for Forrest Ib ulcers. Compared with the first model for peptic ulcer rebleeding classification, the proposed model had improved F1 scores by 5.8%. In the simplified 3-level risk (high-risk, low-risk, and non-endoscopic treatment) classification task, the model achieved F1 scores of 93.74%, 81.30%, and 73.59%, respectively. CONCLUSIONS The proposed multi-feature fusion model integrating deep features from CNNs with manually extracted visual features effectively improves the accuracy of rebleeding risk classification for peptic ulcers, thus providing an efficient diagnostic tool for clinical assessment of rebleeding risks of peptic ulcers.
Humans ; Deep Learning ; Peptic Ulcer ; Risk Assessment ; Peptic Ulcer Hemorrhage ; Recurrence

Objective:To explore the manifestations of magnetic resonance imaging(MRI)on acute traumatic lateral patellar dislocation of children and adolescents.Methods:MRI images of the affected side and healthy side of 110 children and adolescents with acute traumatic lateral patellar dislocation who were treated in the Second Hospital of Tangshan from July 2016 to April 2022 were retrospectively analyzed.The correlation of the medial patellofemoral ligament(MPFL)on the affected side between the tear location and tear degree was compared and analyzed.According to the cartilage injury grading system of international cartilage repair society(ICRS),the articular cartilage injury of affected side was divided into 4 grades,and the correlation between the articular cartilage injury grading and the articular cartilage injury location was compared and analyzed.Three methods of measuring patellar height,which included Insall-Salvati index(ISI),patellotrocheal index(PTI)and Caton-Deschamps index(CDI),were used to compare and analyze the differences of MRI data of patellar height between the affected side of knee joint and the healthy knee joint of pediatric children.Results:In 110 patients with MPFL injury,73 cases were partial tears and 37 cases were complete tears.There was significant difference in the injury at MPFL patellar attachment location between complete tears(22 cases)and partial tears(19 cases)(x2=11.740,P<0.05),and there was significant difference in MPFL multiple injury between partial tear(40 cases)and complete tear(8 cases)(x2=10.990,P<0.05).There were no significant differences in the injuries of MPFL middle segment and the origin of femur between partial tears and complete tears.There were 162 lesions in 110 cases with osteochondral injury,which included 55 lesions on the patellar side,33 lesions on the femur side and 74 multiple lesions according to the part of injury.There was significant difference between the location of osteochondral injury and injury grading(x2=38.153,P<0.05).The ISI,PTI and CDI on the affected side were significantly lower than those on the healthy side in pediatric patients with acute traumatic lateral patellar dislocation of children and adolescents(x2=30.853,12.586,19.656,P<0.05),respectively.Conclusion:The complete tears are more likely to occur in the injury of MPFL patellar attachment location of pediatric patients with acute traumatic lateral patellar dislocation of children and adolescents,while multiple injuries are more likely to be in partial tears.There is correlation between the articular cartilage injury grading and the articular cartilage injury location in pediatric patients.MRI is an important method to diagnose MPFL injury,which can provide more evidence for clinical treatment.

Objective To investigate the feasibility of using contrast-enhanced T1WI radiomics in predicting the pathological grade in rectal adenocarcinoma.Methods The MRI and pathological data of 127 patients with rectal adenocarcinoma were analyzed retrospectively.ITK-SNAP software was used to manually draw region of interest(ROI)in rectal cancer on axial T,WI enhanced images.The radiomics features were extracted by the Pyradiomics software from ROI.The task was divided into two parts:task 1("high & non-high"group)predicted the high-differentiation and moderate/low-differentiation of the tumor;task 2("moderate & low"group)predicted the tumor's moderate-differentiation and low-differentiation in"non-high"group.Maximum relevance and minimum redundancy(mRMR)method was used to screen features.The five methods including least absolute shrinkage and selection operator(LASSO),logistic regression(LR),naive Bayes(NB),random forest(RF),and support vector machine(SVM)were used to build the models,and the efficiency of each model was evaluated and compared.Results In task 1,the area under the curve(AUC)of five methods were 0.86,0.90,0.59,1.00,0.99 in the training cohort and 0.71,0.62,0.53,0.67,0.64 in the testing cohort.In task 2,the AUC of five methods in the training cohort were 0.93,0.85,0.67,0.92,0.89,and in the testing cohort were 0.86,0.80,0.50,0.78,0.71.The models constructed by LASSO in both tasks were the dominant models,the AUC of the fusion model in the testing cohort which combined with age,gender and the dominant Radiomics score(Radscore)was 0.80[95％confidence interval(CI)0.63-0.96]in task 1,and the accuracy,sensitivity and specificity were 78.94％,77.78％,and 79.31％respectively.They were 0.89(95％CI 0.74-1.00),90.00％,95.65％,and 71.43％,respectively in task 2.The calibration curves showed that the fusion models had a good goodness of fit.Conclusion Based on the establishment of two dichotomous models,the radiomics based on the contrast-enhanced T1 WI is feasible in predicting the high,moderate and low differentiation degree of rectal adenocarcinoma.

Objective:To explore the anxiety level, influencing factors among surrogate decision-makers of patients with acute ischemic stroke during thrombolysis decision-making, and their correlation with decision-making duration.Methods:Acute ischemic stroke patients and their surrogate decision-makers who visited the Emergency Department of the First Affiliated Hospital of Zhengzhou University from September 2019 to December 2021 were selected as the research subjects.Sociodemographic data and disease related data of patients and surrogate decision-makers were collected.Surrogate decision-makers were evaluated with the state-trait anxiety inventory, decision participation expectation scale, Wake Forest physician trust scale, and perceived social support scale.SPSS 26.0 software was used for data processing.Pearson correlation analysis, Spearman correlation analysis and ridge regression analysis were used for statistical analysis.Results:The score of state anxiety of decision-makers was (49.47±9.04), and 18.2% (70/383) of decision-makers had a decision duration exceeding 15 minutes.The score of state anxiety of decision-makers was positively correlated with decision duration ( r=0.189, P<0.001). The influencing factors of state anxiety level of decision-makers included sociodemographic factors (age of decision-makers and patients, relationship between payers and patients, whether decision-makers bear the current medical expenses, type of medical insurance for patients), psychological factors (trust level in physicians, perceived social support), factors related to patient disease (numbers of stroke relapses, National Institutes of Health stroke scale scores for patients), characteristics of the decision-making process (whether patients participate in the decision-making process, and the role of decision-makers in the decision-making process) (all P<0.05). Conclusion:Most surrogate decision-makers experience anxiety.Medical staff should pay attention to the emotions of decision-makers and adopt appropriate communication skills when communicating with informed consent for thrombolysis, alleviate the anxiety of surrogate decision-makers, so as so reduce the decision-making duration.

Objective:To investigate the therapeutic effect difference between first-line treatment with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI) and chemotherapy in non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) rare mutation.Methods:A retrospective case-control study was performed. Data of NSCLC patients with rare EGFR mutation who were treated in Shanxi Province Cancer Hospital from January 2013 to October 2019 were retrospectively analyzed. EGFR mutations in living tissues or blood were detected by using amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) before first-line treatment. According to first-line treatment methods,they were divided into EGFR-TKI treatment group and chemotherapy group. Objective remission rate (ORR) and disease control rate (DCR) of both groups were compared. Kaplan-Meier method was used to draw progression-free survival (PFS) and the overall survival (OS) curves. Log-rank test was used for comparison among groups. Single-factor and multi-factor Cox proportional risk models were used to analyze the influencing factors of PFS and OS.Results:A total of 169 patients with EGFR rare mutations were included, and the age [ M (IQR)] was 63 years (12 years); there were 96 cases (56.8%) < 65 years and 73 cases (43.2%) ≥65 years; 70 (41.4%)males and 99 (58.6%) females; 55 cases (32.5%) had EGFR G719X mutation,45 cases (26.6%) had L861Q mutation, 17 cases (10.1%) had S768I mutation, and 52 cases (30.8%) had complex mutation; 55 cases (32.5%) received the first-line chemotherapy and 114 cases (67.5%) received the first-line EGFR-TKI treatment. In the chemotherapy group, ORR was 36.4% (20/55) and DCR was 85.5% (47/55); in EGFR-TKI treatment group, ORR was 72.8% (83/114) and DCR was 90.4% (103/114). The ORR of EGFR-TKI treatment group was higher than that of chemotherapy group ( χ2 = 20.70, P = 0.001), and there was no statistically significant difference in DCR between two groups ( χ2 = 1.76, P = 0.184). Subgroup analysis showed that ORR in EGFR-TKI treatment group with G719X, L861Q and complex mutations was higher than that of the corresponding mutations in chemotherapy group, and the differences were statistically significant (all P < 0.05), while there were no significant differences in DCR among subgroups (all P > 0.05). The median PFS time was 9.7 months (95% CI: 6.0-13.4 months) and 3.8 months (95% CI: 3.1-7.1 months), respectively in EGFR-TKI treatment group and chemotherapy group, and there was a statistically significant difference in PFS between the two groups ( P < 0.001). The median OS time was 25.6 months (95% CI: 18.0-37.9 months) and 31.7 months (95% CI: 18.0-42.8 months), respectively in EGFR-TKI treatment group and chemotherapy group, and there was no statistically significant difference in OS between the two groups ( P = 0.231). Multivariate Cox regression analysis showed that brain metastasis [with vs. without: HR = 2.306, 95% CI: 1.452-3.661, P < 0.001] and the first-line treatment methods (EGFR-TKI vs. chemotherapy: HR = 0.457, 95% CI:0.317-0.658, P < 0.001) were independent influencing factors for PFS of NSCLC patients with EGFR rare mutation; brain metastasis (with vs. without: HR = 2.087, 95% CI: 1.102-3.953, P = 0.024; unknown vs. without: HR = 2.118,95% CI: 1.274-3.520, P = 0.004) were independent influencing factors for OS of NSCLC patients with EGFR rare mutation. Conclusions:Compared with the first-line chemotherapy, EGFR-TKI first-line treatment could improve objective remission and PFS of NSCLC patients with EGFR rare mutation, while no OS benefit is observed.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.