ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

Objective:Using bioinformatics methods to find key genes related to asthma and discussing their molecular mecha-nisms.Methods:Weighted gene co-expression network analysis(WGCNA)was performed on GSE143303 microarray dataset to screen out the modules significantly related to asthma.Module genes were subjected to protein-protein interaction(PPI)network analysis and function and pathway enrichment analysis.Key genes were obtained by intersecting WGCNA analysis results with differentially expressed genes.miRDB and miRwalk databases were used to predict upstream miRNAs of key genes,and Cytoscape was used to construct key mRNA-miRNA regulatory network.GSE147878 dataset was used to verify expressions of key genes,and evaluate diag-nostic value of key genes according to ROC curve.Results:Genes in magenta module and purple module were significantly related to asthma,mainly involved in Wnt signaling pathway,cell adhesion and so on.A total of 13 key genes were obtained,including ATP6V1G1,TXNDC17,NDUFA4,RHOA,SEC61B,RPS3A,PSMC5,GSPT1,MBP,SMARCC2,GNL3L,RPL7L1,RAD21 and their potential miRNA-mRNA regulatory networks.Conclusion:Key genes such as ATP6V1G1,GSPT1,SEC61B play an important role in bronchial asthma and have clinical diagnostic value.

Objective To explore the factors affecting the coefficient of variation(CV)of glucose in type 2 diabetes mellitus(T2DM)patients based on real-time dynamic glucose monitoring system.Methods A total of 354 patients with T2DM hospitalized in the Department of Endocrinology of Jiangsu Shengze Hospital were enrolled in this study from March 2023 to March 2024 and divided into two groups:the glycemic variability(GV,CV>36%)group(n=118)and the glucose stable(GS,CV≤36%)group(n=236).The clinical data of the two groups were compared,and the influencing factors for CV>36%were analyzed.Results The DM duration and HbA1c were higher(P<0.05),while BMI,visceral fat area,subcutaneous fat area(SFA),FC-P,serum uric acid(SUA),and TG were lower in the GV group than in the GS group(P<0.05).Spearman correlation analysis showed that CV was positively correlated with diabetes duration and HbA1c(P<0.05),and negatively correlated with FC-P,SFA and SUA(P<0.05).Logistic regression analysis showed that DM duration,HbA1c,SFA,FC-P and SUA were the influencing factors for GV.Scatter plot analysis showed that there was a linear trend between CV level and log HbA1c and log SFA in T2DM patients.CV level increased with the increase of log HbA1c,and decreased with the increase of log SFA.ROC curve analysis showed that the area under the curve(AUC)of FC-P was 0.703(95%CI:0.640～0.765,P<0.001)for predicting GV in T2DM patients,and the cut-off value was 1.095 ng/ml.The AUC of SUA was 0.622(95%CI:0.555～0.688,P<0.001)for predicting GV,and the cut-off value was 280.5 μmol/L.Conclusions The DM duration,HbA1c,SFA,FC-P and SUA are important factors for GV,and FC-P and SUA have predictive value for GV.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To explore the factors affecting the coefficient of variation(CV)of glucose in type 2 diabetes mellitus(T2DM)patients based on real-time dynamic glucose monitoring system.Methods A total of 354 patients with T2DM hospitalized in the Department of Endocrinology of Jiangsu Shengze Hospital were enrolled in this study from March 2023 to March 2024 and divided into two groups:the glycemic variability(GV,CV>36%)group(n=118)and the glucose stable(GS,CV≤36%)group(n=236).The clinical data of the two groups were compared,and the influencing factors for CV>36%were analyzed.Results The DM duration and HbA1c were higher(P<0.05),while BMI,visceral fat area,subcutaneous fat area(SFA),FC-P,serum uric acid(SUA),and TG were lower in the GV group than in the GS group(P<0.05).Spearman correlation analysis showed that CV was positively correlated with diabetes duration and HbA1c(P<0.05),and negatively correlated with FC-P,SFA and SUA(P<0.05).Logistic regression analysis showed that DM duration,HbA1c,SFA,FC-P and SUA were the influencing factors for GV.Scatter plot analysis showed that there was a linear trend between CV level and log HbA1c and log SFA in T2DM patients.CV level increased with the increase of log HbA1c,and decreased with the increase of log SFA.ROC curve analysis showed that the area under the curve(AUC)of FC-P was 0.703(95%CI:0.640～0.765,P<0.001)for predicting GV in T2DM patients,and the cut-off value was 1.095 ng/ml.The AUC of SUA was 0.622(95%CI:0.555～0.688,P<0.001)for predicting GV,and the cut-off value was 280.5 μmol/L.Conclusions The DM duration,HbA1c,SFA,FC-P and SUA are important factors for GV,and FC-P and SUA have predictive value for GV.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To investigate the application effect of strengths,weaknesses,opportunities and threats(SWOT)analysis-guided risk control management in patients with atherosclerotic obliterans(ASO).Methods:This randomized controlled study enrolled 105 ASO patients admitted in Chinese People's Liberation Army Rocket Force Characteristic Medical Center between November 2017 and November 2022.They were divided into control group(n=52,routine nursing)and intervention group(n=53,SWOT analysis-guided risk control management).Renal function,postoperative recovery,psychological status,sleep quality,pain,incidence of adverse reactions and nursing satisfaction were compared between two groups.Results:3 d after surgery,compared with patients in con-trol group,those in intervention group had significant lower cystatin C(CysC)[(1.04±0.11)mg/L vs.(1.40±0.12)mg/L],serum creatinine(Scr)[(70.70±6.48)μmol/L vs.(82.93±9.32)μmol/L]and urinary protein[(2.38±0.13)g/L vs.(3.56±0.17)g/L](P＜0.001 all);7d after surgery,compared with patients in control group,those in intervention group had significant lower incidence of adverse reactions(7.55％vs.23.08％),scores of self-rating anxiety scale(SAS)[(34.09±3.40)points vs.(39.50±3.12)points],self-rating depression scale(SDS)[(24.42±3.34)points vs.(32.04±2.77)points],Pittsburgh sleep quality index(PSQI)[(7.09±1.48)points vs.(10.19±1.65)points]and visual analogue scale(VAS)[(3.09±0.84)points vs.(4.33±1.15)points],and significant higher limp distance[(2407.89±130.09)m vs.(1521.26±102.26)m]and ankle-brachi-al index[(0.87±0.03)vs.(0.62±0.04)](P＜0.05 or＜0.01).After discharge,nursing satisfaction in inter-vention group was significantly higher than that of control group(92.45％vs.73.08％,P=0.008).Conclusion:SWOT analysis-guided risk control management could effectively reduce the damage of renal function caused by in-terventional surgery,reduce pain,improve negative emotion and sleep quality,and reduce incidence of adverse e-vents after surgery in patients with arteriosclerosis obliterans.