Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

Chronic, unresolved inflammation correlates with persistent hepatic injury and fibrosis, ultimately progressing to hepatocellular carcinoma (HCC). Bisdemethoxycurcumin (BDMC) demonstrates therapeutic potential against HCC, yet its mechanism in preventing hepatic "inflammation-carcinoma transformation" remains incompletely understood. In the current research, clinical HCC specimens underwent analysis using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC) to evaluate the expression of fibrosis markers, M2 macrophage markers, and CXCL12. In vitro, transforming growth factor-β1 (TGF-β1)-induced LX-2 cells and a co-culture system of LX-2, THP-1, and HCC cells were established. Cell functions underwent assessment through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, and Transwell assays. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blotting and immunofluorescence evaluated the differential expression of molecules. The interaction between β-catenin/TCF4 and CXCL12 was examined using co-immunoprecipitation (Co-IP), dual luciferase, and chromatin immunoprecipitation (ChIP) assays. A DEN-induced rat model was developed to investigate BDMC's role in liver fibrosis-associated HCC (LFAHCC) development in vivo. Our results showed that clinical HCC tissues exhibited elevated fibrosis and enriched M2 macrophages. BDMC delayed liver fibrosis progression to HCC in vivo. BDMC inhibited the inflammatory microenvironment induced by activated hepatic stellate cells (HSCs). Furthermore, BDMC suppressed M2 macrophage-induced fibrosis and HCC cell proliferation and metastasis. Mechanistically, BDMC repressed TCF4/β-catenin complex formation, thereby reducing CXCL12 transcription in LX-2 cells. Moreover, CXCL12 overexpression reversed BDMC's inhibitory effect on macrophage M2 polarization and its mediation of fibrosis, as well as HCC proliferation and metastasis. BDMC significantly suppressed LFAHCC development through CXCL12 in rats. In conclusion, BDMC inhibited LFAHCC progression by reducing M2 macrophage polarization through suppressing β-catenin/TCF4-mediated CXCL12 transcription.
Animals ; Liver Neoplasms/etiology* ; Humans ; Carcinoma, Hepatocellular/immunology* ; Liver Cirrhosis/complications* ; Macrophages/drug effects* ; Male ; Rats ; Chemokine CXCL12/genetics* ; Diarylheptanoids/pharmacology* ; Rats, Sprague-Dawley ; beta Catenin/genetics*

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Chronic hepatitis B(CHB)is the main cause of hepatocellular carcinoma(HCC).Early prediction and diagnosis of HCC in CHB patients can further reduce the onset risk of HCC and improve patient prognosis.Scholars at home and abroad have proposed a number of HCC risk prediction models for CHB patients,and these models have achieved new development and opti-mization in the era of antiviral therapy.Due to differences in research backgrounds,these models vary in the use of antiviral drugs,included variables(such as host factors,viral activity,cirrhosis status,etc.)and application scenarios.At the same time,the application of artificial intelligence and liquid biopsy technology in risk prediction models has become a new research highlight.This paper aims to compare the HCC risk prediction models reported so far for CHB patients,clarify the characteristics of each model,explore appropriate HCC risk prediction methods,and provide reference for the risk prediction of hepatitis B virus related HCC.

Objective:To analyze the distribution characteristics of sports facilities in China using geographic information system (ArcGIS) and to investigate their association with mortality risk among residents.Methods:This prospective cohort study included 97 912 community residents from the Chinese Family Database (CFD) between 2013 and 2017. After excluding participants lost to follow-up and those with incomplete data, 53 937 individuals were retained for the analysis. The distribution characteristics of sports facilities in China was mapped using ArcGIS, and the death events were recorded via structured interviews and questionnaires. The Poisson regression was used to assess the association between the distribution characteristics of sports facilities near participants′ residences and their mortality risk.Results:In 2013, a total of 79 714 sports facilities were identified across 262 districts (counties) in China, with large-scale sports facilities accounting for the highest proportion (87.09%). The median number of sports facilities within the residential buffer zone was 17 (4, 30), and the median distance from the residence to the nearest sports facility was 453.2 (341.5, 1 863.5) m. Among the 53 937 community residents analyzed in this study, there were 27 761 males and 26 176 females, 1 326 deaths (2.5%) occurred during the follow-up. Poisson regression revealed that a higher number of sports facilities in the buffer zone (≥21 vs 0-2) was associated with lower mortality risk ( RR=0.74, 95% CI: 0.64-0.85; P0.05). Subgroup analyses showed that being≥60 years old ( RR=0.82, 95% CI: 0.70-0.95), males ( RR=0.78, 95% CI: 0.64-0.95), females ( RR=0.79, 95% CI: 0.64-0.97), having a junior high school education or less ( RR=0.84, 95% CI: 0.71-0.99), and having a urban residence ( RR=0.77, 95% CI: 0.66-0.90) were all negatively associated with residents′ mortality risk (all P0.05). After adjusting for age, greater distance to the nearest sports facility ( RR=1.41, 95% CI: 1.08-1.83) and failing to meet the"10-minute fitness circle"criterion ( RR=1.25, 95% CI: 1.02-1.53) were associated with higher mortality risk among males (both P0.05). After adjusting for age and gender, urban residents with a greater distance to the nearest sports facility ( RR=1.29, 95% CI: 1.04-1.60) or not meeting the 10-minute fitness circle ( RR=1.18, 95% CI: 1.00-1.38) showed a significantly higher mortality risk (both P0.05). Conclusions:The ArcGIS analysis revealed that the distribution of sports facilities in China is characterized by a high proportion of large-scale facilities. Lower facility density within residential buffer zone and greater distance to the nearest facility increase mortality risk among adults.

[Objective] To investigate the implementation of emergency transfusion strategy of uncrossmatched type O suspended RBCs based on the single-center clinical practice, which is "emergency transfusion is initiated by the authorized doctor of the emergency department, and no more than 4 U of type O uncrossmatched suspended RBCs are issued within 15 minutes in the transfusion department"(referred as the Practice), so as to provide reference for blood management. [Methods] A retrospective analysis of the information of patients who received uncrossmatched type O suspended RBCs in West China Hospital of Sichuan University from August 2019 to April 2024 was conducted. The analysis included reasons for emergency blood transfusion, time of receiving transfusion application and blood distribution, total bilirubin, indirect bilirubin, lactate dehydrogenase before and after transfusion, blood group of patients, and disease outcome. [Results] From August 2019 to April 2024, 39 cases applied for emergency transfusion of type O suspended RBCs, and a total of 90 U uncrossmatched suspended RBCs were transfused. All patients were Rh(D) positive, including 14 cases of blood group A, 6 cases of blood group B, 16 cases of blood group O, 2 cases of blood group AB, one case of undetermined blood group, and 2 cases with positive antibody screening. The main cause of emergency transfusion of type O suspended RBCs was traffic accident, accounting for 46% (18/39), with a mortality rate at 51.28% (20/39). The cause of death was primary injury, and no adverse reactions were reported. There was no significant difference in total bilirubin (TBIL), indirect bilirubin (IBIL) and lactate dehydrogenase (LDH) before and after blood transfusion (P>0.05). The median duration from admission to receiving transfusion application was 30.20 minutes, and 5.30 minutes from receipt of the application to blood distribution. [Conclusion] The single-center based Practice is safe, but there is room for optimization before the link of blood transfusion application sent to the transfusion department when applying for emergency transfusion of type O suspended RBCs.

Objective:To study the distribution characteristics of current patients with Kashin-Beck disease (KBD) in Molidawa Daur Autonomous Banner (referred to as Morin Banner), and provide suggestions for service management.Methods:Information of KBD current patients in Morin Banner was collected from January 1, 2018 to June 30, 2024 using the "KBD Current Patient Survey System" provided by the Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention. A descriptive study method was used to analyze the basic information and clinical data of current patients.Results:As of June 30, 2024, a total of 6 223 KBD current patients were reported in Morin Banner, and the patients were distributed in 15 townships (towns). There was a statistically significant difference in the prevalence rate of KBD among different townships (towns, χ 2 = 3 069.01, P < 0.001). The minimum age of the KBD current patients was 27 years old, and the maximum was 98 years old, mainly concentrated in the age range of 45 - 74 years old, accounting for 95.7% (5 954/6 223). There was a significant difference in the prevalence rate of KBD among different age groups (χ 2 = 5 912.76, P < 0.001). The male to female ratio was 1.00∶1.14 (2 910 ∶ 3 313), and there was a statistically significant difference in prevalence rate of KBD between genders(χ 2 = 44.38, P < 0.001). The KBD current patients mainly had a primary school education, married, and farmers, accounting for 59.2% (3 685/6 223), 89.8% (5 590/6 223), 93.2% (5 802/6 223), respectively; and the clinical grading of patients is mainly degree Ⅰ. There was a statistically significant difference in the rate of limb disability among patients with different clinical grades (χ 2 = 64.26, P < 0.001). The rate of limb disability in males was higher than that in females (χ 2 = 10.36, P = 0.001). Conclusions:The KBD current patients in Morin Banner are distributed in various township (town), with middle-aged and elderly famers being the main ones. It is necessary to strengthen monitoring of KBD, and pay attention to personalized treatment and management of KBD current patients.

Objective The differences in biomechanical characteristics of the lower limbs between individuals with chronic ankle instability(CAI)and healthy individuals during unanticipated and anticipated jumping were compared,in order to provide practical references and ideas for the prevention and treatment of recurrent ankle sprains.Methods Thirty subjects were recruited,including 15 patients with CAI and 15 healthy volunteers.All subjects completed unanticipated and anticipated jumping tests in a random order,with a 1-week interval between the two tests.Kinematic and kinetic data of lower limbs were collected synchronously using Vicon infrared high-speed motion capture system and Kistler three-dimensional force platform.Results At the moment of touchdown,knee flexion angle was significantly greater during unanticipated jumping than that during anticipated jumping(P=0.009),while ankle eversion angle was notably lower(P=0.043).During the early landing phase,unanticipated jumping showed significantly greater peak hip flexion and abduction angles,as well as knee flexion(P=0.038,P=0.036,P=0.04),while peak ankle dorsiflexion and eversion angles were significantly lower(P=0.001,P=0.01)compared to anticipated jumping.Additionally,peak hip abduction moment during unanticipated jumping was significantly higher in patients with CAI than that during anticipated jumping(P=0.028).Conclusions Unanticipated jumping reduced ankle dorsiflexion and eversion angles in individuals with CAI,putting the ankle in an open,sprain-prone position.Individuals with CAI compensated proximally by increasing hip flexion,abduction,knee flexion angles,and hip extension moment to stabilize the ankle.

Objective:To explore the dual mediating effects of health belief and depression among health knowledge, social support, and health behaviors based on the capacity, opportunity, motivation-behavior (COM-B) model, and analyze the influencing factors of health behaviors in patients with ischemic stroke.Methods:This multi-center cluster sampling research recruited ischemic stroke patients ( n=1 696) who were hospitalized in neurology departments of five tertiary hospitals in Henan Province from October 2023 to October 2024. A cross-sectional investigation was conducted using the general information questionnaire, social support rating scale (SSRS), stroke prevention knowledge questionnaire(SPKQ), short form health belief model scale(SF-HBMS), health promoting lifestyle profile-Ⅱ (HPLP-Ⅱ), and patient health questionnaire-9(PHQ-9) to ultimately reveal the pathways and effect sizes among variables. Partial correlation analysis and multiple linear stepwise regression analysis were conducted to examine the relationships among social support, health knowledge, health belief, health behaviors, and depression in stroke patients by SPSS 26.0 software. Structural equation modeling was constructed using AMOS 28.0 software, and the mediating effect was tested using the Bootstrap method. Results:The scores of social support, health knowledge, health belief, and health behaviors among ischemic stroke patients were (37.46±9.94), (26.56±6.84), (75.62±12.62) and (130.79±26.27), respectively. The score of depression was 5.00 (2.00, 8.00). Health behaviors were positively correlated with health knowledge, social support, and health belief( r=0.333, 0.246, 0.267, all P<0.05), while negatively correlated with depression ( r=-0.146, P<0.05). Multiple linear stepwise regression analysis showed that health knowledge, social support, health belief, and depression were all influencing factors of health behaviors in ischemic stroke patients (all P<0.05). Health belief (effect value=0.068, 95% CI=0.048-0.093) and depression (effect value=0.009, 95% CI=0.003-0.018) both played partial mediating roles between health knowledge and health behaviors, accounting for 17.3%(0.077/0.446) of the total effect. Meanwhile, health belief (effect value=0.045, 95% CI=0.029-0.063) and depression (effect value=0.016, 95% CI=0.008-0.027) both played partial mediating roles between social support and health behaviors, accounting for 26.5%(0.061/0.230) of the total effect. Conclusion:Health knowledge and social support can not only directly influence health behaviors but also indirectly affect them through health belief and depression in patients with ischemic stroke.

Objective:To explore the dual mediating effects of health belief and depression among health knowledge, social support, and health behaviors based on the capacity, opportunity, motivation-behavior (COM-B) model, and analyze the influencing factors of health behaviors in patients with ischemic stroke.Methods:This multi-center cluster sampling research recruited ischemic stroke patients ( n=1 696) who were hospitalized in neurology departments of five tertiary hospitals in Henan Province from October 2023 to October 2024. A cross-sectional investigation was conducted using the general information questionnaire, social support rating scale (SSRS), stroke prevention knowledge questionnaire(SPKQ), short form health belief model scale(SF-HBMS), health promoting lifestyle profile-Ⅱ (HPLP-Ⅱ), and patient health questionnaire-9(PHQ-9) to ultimately reveal the pathways and effect sizes among variables. Partial correlation analysis and multiple linear stepwise regression analysis were conducted to examine the relationships among social support, health knowledge, health belief, health behaviors, and depression in stroke patients by SPSS 26.0 software. Structural equation modeling was constructed using AMOS 28.0 software, and the mediating effect was tested using the Bootstrap method. Results:The scores of social support, health knowledge, health belief, and health behaviors among ischemic stroke patients were (37.46±9.94), (26.56±6.84), (75.62±12.62) and (130.79±26.27), respectively. The score of depression was 5.00 (2.00, 8.00). Health behaviors were positively correlated with health knowledge, social support, and health belief( r=0.333, 0.246, 0.267, all P<0.05), while negatively correlated with depression ( r=-0.146, P<0.05). Multiple linear stepwise regression analysis showed that health knowledge, social support, health belief, and depression were all influencing factors of health behaviors in ischemic stroke patients (all P<0.05). Health belief (effect value=0.068, 95% CI=0.048-0.093) and depression (effect value=0.009, 95% CI=0.003-0.018) both played partial mediating roles between health knowledge and health behaviors, accounting for 17.3%(0.077/0.446) of the total effect. Meanwhile, health belief (effect value=0.045, 95% CI=0.029-0.063) and depression (effect value=0.016, 95% CI=0.008-0.027) both played partial mediating roles between social support and health behaviors, accounting for 26.5%(0.061/0.230) of the total effect. Conclusion:Health knowledge and social support can not only directly influence health behaviors but also indirectly affect them through health belief and depression in patients with ischemic stroke.