Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

Objective:To establish a prognostic prediction model for hepatocellular carcinoma (HCC) using bioinformatics approaches to guide personalized therapy.Methods:Based on bioinformatics, the differential analysis was carried out on the GSE19665 data set of The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and Gene Expression Omnibus (GEO), and the same differentially expressed genes were obtained by means of Wayne diagram. Functional enrichment analyses using Gene Ontology, Kyoto Encyclopedia of Genes and Genome, and Gene Set Enrichment Analysis were conducted on co-expressed genes. Based on clinicopathological and transcriptomic profiles, TCGA-LIHC patients were stratified into training ( n=246) and internal validation ( n=116) cohorts, with external validation using Japanese liver cancer data ( n=231) from the International Cancer Genome Consortium. A LASSO-Cox regression-derived risk scoring model was established and visualized as a nomogram. The clinical utility of the risk score was evaluated through multiple analytical approaches.A nomogram incorporating the risk score was developed, and its predictive performance was validated using the concordance index (C-index) and calibration curves. The measurement data of normal distribution were expressed as mean±standard deviation( ± s), and the t-test was used for comparison between groups. The measurement data with non-normal distribution were expressed as M( Q1, Q3), and the Wilcoxon test was used for comparison between groups. The Kruskal-Wallis test was applied to evaluate the significance of the differences among multiple groups. The prognostic value of the risk score was estimated using Kaplan-Meier analysis and ROC curve. Multivariate Cox regression clarified the independent prognostic value of the risk score. Results:Differential analysis identified 457 commonly expressed differentially expressed genes (DEGs). Enrichment analysis revealed that these common DEGs were significantly enriched in pathways related to the cell cycle of tumor cells.The LASSO-Cox regression model selected eight candidate genes ( CENPA, NDC80, ANXA10, NEIL3, G6 PD, MCM10, SOCS2, MMP1). The predictive risk score generated using these eight genes demonstrated a strong association with the overall survival of HCC patients.The nomogram combining the predictive risk score with clinicopathological features exhibited high predictive performance in both the training and validation cohorts. Furthermore, the prognostic value of this risk score was successfully validated in the external validation cohort. Conclusion:This study successfully developed a new predictive model that accurately predicts the 1-year, 3-year and 5-year survival rates of patients with liver cancer. This can serve as a potential tool to help guide patients in personalized treatment.

Objective To construct the core outcome set(COS)for clinical research on Uyghur medicine in treating psoriasis by using internationally-recognized research methods,thus to aid the researchers in choosing the standardized outcomes and to enhance the quality of evidence from research findings.Methods A systematic retrieval of Chinese and English databases was conducted to collect outcomes from clinical studies,systematic reviews,and registered protocols of Uyghur medicine for treating psoriasis.An outcome pool was constructed based on the results of literature review.The outcomes were supplemented after qualitative surveys of patients and physicians,and then an initial list of outcomes was formed.Two rounds of Delphi surveys on the initial list were conducted for obtaining Likert scale ratings from different stakeholder groups to evaluate the importance of outcomes.After that,a consensus meeting was held to finalize the COS for clinical research on Uyghur medicine in treating psoriasis.Results The COS for clinical research on Uyghur medicine in treating psoriasis comprises six domains,totaling 14 outcomes.The 14 outcomes were psoriasis symptoms(psoriasis area and area severity index),skin manifestations(erythema,scaling,infiltration,etc.),investigator global assessment,patient global assessment,treatment satisfaction,health-related quality of life,recurrence rate,adverse events,drug adverse reactions,blood routine,urine routine,liver and kidney function,Uyghur medicine symptom assessment,and fluid changes.Conclusion The COS for clinical research on Uyghur medicine in treating psoriasis has been constructed,and will provide a reference for the selection of efficacy-evaluation outcomes and for the reporting of outcomes in related studies.

Objective To develop a core outcome set(COS)for treatment of progressive vitiligo in Uyghur medicine,and to standardize the selection and reporting of outcome measures in relevant studies.Methods Based on the existing core outcome domain set of randomized controlled trials for vitiligo,additional outcome indicators reflecting the advantages and characteristics of Uyghur medical treatment were developed.Specific indicators for Uyghur medical treatment of progressive vitiligo were collected through literature review and semi-structured questionnaire surveys,and then a list of indicators were formed.The Delphi survey and consensus meetings were used to select core indicators.Results A total of 54 studies were included,and 86 questionnaires were collected.Through literature review and questionnaire surveys,a list of 28 indicators were obtained.After two rounds of Delphi survey and one consensus meeting,12 outcome indicators in 7 domains were finally determined,including vitiligo lesion area,repigmentation,disease control time,maintenance of repigmentation,recurrence rate,immune indicators,psychological health,patients' quality of life,adverse events,adverse reaction incidence,liver and kidney function monitoring,and Uyghur medicine syndrome differentiation of mucus.Additionally,some measurement tools for certain indicators were recommended.Conclusion The development of the COS for vitiligo treatment in Uyghur medicine helps to comprehensively evaluate the efficacy of Uyghur medicine,and will provide a model for establishing efficacy evaluation methods that conform to the characteristics of ethnic minority medicine.

Objective To investigate the clinicopathological features and key points of diagnosis and treatment of malignant perivascular epithelioid cell tumor(PEComa)to increase awareness of the disease.Methods The clinicopathological data of 2 patients with malignant PEComa treated in our hospital were retrospectively analyzed,and relevant literatures were reviewed.Results Both patients were male,aged 53 and 16 years,respectively.The sites of occurrence were in the retroperitoneum and pelvis,respectively.Both tumors were resected surgically,and the diagnosis was confirmed with postoperative pathology.Under the microscope,the tumor tissue of one patient was mainly composed of smooth muscle-like cells,and that of the other patient was composed of epithelioid cells,both showing pathological mitotic images and expressing HMB45,Melan-A,SMA and CD34,no tumor recurrence or metastasis was observed during the follow-up.The literatures collected involved 15 patients with retroperitoneal or pelvic PEComa,including 3 males and 12 females,of which 9 were malignant.The clinical manifestations were abdominal pain,bloating,or lower back pain.Some cases were detected during physical examinations.Conclusion Malignant PEComa is difficult to be diagnosed before surgery and easy to be misdiagnosed.The confirmed diagnosis depends on the postoperative pathological results.The preferred treatment is complete resection of tumor.Long-term follow-up is needed.

Objective To explore the risk factors that affect the outcome of testicular torsion in patients with testicular resection,to provide ideas for clinical management.Methods The clinical data of 117 patients with testicular torsion treated in our hospital during Jan.1,2012 and Mar.1,2023 were retrospectively analyzed,43 of whom underwent testicular detorsion and orchidopexy,and 74 underwent orchiectomy.The correlation between preoperative inflammatory and coagulation-related indicators,testicular torsion angle,TWIST score and orchiectomy was analyzed with univariate analysis.The independent risk factors for testicular torsion patients with testicular resection as the outcome were analyzed with binary logistic regression.The predictive value of each factor for orchiectomy was assessed with receiver operating characteristic(ROC)curve.Results Binary logistic regression analysis indicated that long duration of onset(OR=1.841,P=0.036),large torsion angle(OR=1.005,P=0.016),high TWIST score(OR=2.225,P=0.003)and elevated FIB level(OR=2.489,P=0.049)were independent risk factors for testicular torsion patients with testicular resection as the outcome.ROC curve analysis showed that the best cut-off value of the above 4 factors to predict orchiectomy were 1.75 days,225°,3.5 and 3.155 g/L;the area under the ROC curve(AUC)were 0.893,0.718,0.812 and 0.770,respectively.Conclusion The duration of onset,torsion angle,TWIST score,and FIB level are independent risk factors for testicular torsion patients with testicular resection as the outcome,and these indicators have certain predictive value.

Establishing a governance structure and an operational model that is compatible with modern hospital manage-ment systems,deepening the reform of hospital management institutions,and exploring the implementation of Super-department System with unified functions are inevitable requirements for promoting the high-quality development of public hospitals.Hospital of Stomatology of Sun Yat-sen University takes the Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era as a guide and fully implements the"Opinions of the General Office of the State Council on Promoting the High Quality Development of Public Hospitals,"integrates party building work and vocational work,carries out practical exploration of the reform of the Su-per-department System,and leads the hospital to achieve phased results in high-quality development.

In recent years,there have been active studies on intracranial hemorrhage associated with hematological malignancies,but the understanding of subarachnoid hemorrhage associated with hematological malignancies is still insufficient.We retrieve from PubMed and China National Knowledge Infrastructure(NCKI),and describes the understanding of hematological malignant tumor related subarachnoid hemorrhage.This article summarizes the clinical characteristics and possible pathogenesis of subarachnoid hemorrhage associated with hematological malignancies.At present,there is a lack of effective prevention and treatment measures for hematological malignant tumor-related subarachnoid hemorrhage,which mainly focuses on the active treatment of the primary disease while saving time for the treatment of complications,and the mortality is high.

Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology.By leveraging these genes,our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy. Methods Sample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases.In the initial stage,we identified 67 differentially expressed genes associated with immune response in CD8+T cells.Subsequently,we narrowed our focus to three key genes,namely CXCL13,GBP2,and GZMB,which were used to construct a prognostic model.The accuracy of the model was assessed using the validation set data and receiver operating characteristic(ROC)curves.Furthermore,we employed various methods,including Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,immune infiltration,and correlation analyses with CD274(PD-L1)to explore the model's predictive efficacy in immunotherapeutic responses.Additionally,we investigated the potential underlying biological pathways that contribute to divergent treatment responses. Results We successfully developed a model capable of predicting the prognosis of patients with TNBC.The areas under the curve(AUC)values for the 1-,3-,and 5-year survival predictions were 0.618,0.652,and 0.826,respectively.Employing this risk model,we stratified the samples into high-and low-risk groups.Through KEGG enrichment analysis,we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism,whereas the low-risk group demonstrated significant enrichment in cytokine pathways.Furthermore,immune landscape analysis revealed noteworthy variations between(PD-L1)expression and risk scores, Conclusion Our study demonstrates the potential of CXCL13,GBP2,and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC.These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.