Objective: To investigate the distribution characteristics and related factors of weight loss behavior among middle school students in Shanghai, so as to provide a reference for guiding scientific weight loss among middle school students. Methods: From May to June 2021, a stratified cluster random sampling method was used to select 16 758 junior and high school students in 16 districts of Shanghai. Youth Risk Behavior Surveillance System was administered to assess the basic condition and weight loss behaviors of the students. An unordered multinomial Logistic regression model was employed to analyze the factors associated with weight loss behaviors. Results: A total of 5 881 (35.09%) reported engaging in exercise for weight loss, 6 344 (37.86%) reported dieting for weight loss, and 461 (2.75%) engaged in unhealthy weight loss behaviors. The unordered multinomial Logistic regression analysis indicated that compared with the no weight loss behavior group, students from urban areas( OR =1.35,95% CI =1.10-1.66), those with Internet addiction ( OR =1.71,95% CI =1.23-2.38), those with victims of bullying ( OR =2.09, 95% CI =1.68-2.61), those experiencing insomnia ( OR =2.33,95% CI = 1.74-3.11), those feelings of sadness or despair ( OR =3.10, 95% CI =2.42- 3.97 ), and those who perceived their body weight as slightly heavy ( OR =2.77, 95% CI = 2.17-3.55) or very heavy ( OR =3.41, 95% CI =2.44-4.75) were more likely to engage in unhealthy weight loss behaviors ( P <0.05). Conclusions There are significant differences in weight loss behaviors among middle school students with varying characteristics in Shanghai. Negative emotions such as insomnia and feelings of sadness or despair, Internet addiction, cognitive bias in weight and experiences of bullying are identified as related factors for unhealthy weight loss behaviors. Targeted intervention measures should be implemented to guide students towards scientific approaches to weight management.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective:To investigate the protocol and clinical efficacy of hair follicle-bearing microskin (HF-MS) transplantation in the treatment of hypertrophic scars.Methods:Prospective randomized controlled trial. From January to November 2024, patients with hypertrophic scars were recruited from the Medical Cosmetic Center of Affiliated Hangzhou First People’s Hospital with Westlake University School of Medicine and the Department of Plastic and Reconstructive Surgery of Ningbo Sixth Hospital. Patients were randomly divided into the observation group and the control group using a random number table. In the observation group, 1.0 mm punch decompression was performed on the hypertrophic scar area, followed by implantation of HF-MS extracted from the scalp donor site using follicular unit excision (FUE) into the decompression pores. The control group underwent only 1.0 mm punch decompression. Vancouver scar scale (VSS) scores (total score 0-15, higher scores indicating more severe scarring) were assessed preoperatively and at 1, 3, and 6 months postoperatively. Efficacy at 6 months, improvement in hypertrophic scar area, hair survival rate (observation group), adverse reactions, and patients’ satisfaction rates were evaluated. Categorical data were expressed as frequency (%) and analyzed using chi-square tests; normally distributed measurement data were expressed as Mean ± SD and analyzed using independent samples t-tests. Results:A total of 50 patients were included (25 per group), with 22 males and 28 females, aged 18-60 years (mean age: 33 years). The effective rate was 92% (23/25) in the observation group and 68% (17/25) in the control group, showing a statistically significant difference ( P<0.05). Preoperative VSS scores did not differ significantly between the observation and control groups [(6.67±3.19) vs. (7.12±2.89), P>0.05]. At 1, 3, and 6 months postoperatively, the observation group had VSS scores of (5.48±2.60), (4.64±2.39), and (3.80±2.10), respectively, compared to (6.36±2.53), (5.84±2.28), and (5.32±2.09) in the control group. The 6-month postoperative VSS scores differed significantly between groups ( P<0.05). Preoperative hypertrophic scar areas showed no significant difference [(5.75±2.83) cm 2 vs. (6.91±3.31) cm 2,P>0.05]. At 6 months postoperatively, the observation group had significantly smaller scar areas than the control group [(3.15±1.55) cm 2 vs. (5.37±2.93) cm 2,P<0.01]. The average hair survival rate in the observation group was 41% at 6 months. Adverse reactions occurred in 3 cases in the observation group (2 skin indurations, 1 hyperpigmentation) and 7 cases in the control group (4 hyperpigmentation, 2 skin atrophy, 1 skin induration). The observation group had a significantly lower adverse reaction rate [12% (3/25) vs. 28% (7/25), P<0.05]. Patient satisfaction rates were 88% (22/25) in the observation group and 64% (16/25) in the control group ( P<0.05). Conclusion:HF-MS transplantation demonstrates definitive clinical efficacy in treating hypertrophic scars, effectively improving scar morphology, clinical symptoms, and patient quality of life.

Objective To investigate the current status of treatment for patients with convulsive epilepsy in rural areas of Heilongjiang Province， China and the efficacy of phenobarbital in the treatment of epilepsy， and to evaluate the effect of the epilepsy prevention and management project in rural areas. Methods EpiData， EXCEL， and SPSS 19.0 were used for data entry， processing， and statistical description to analyze the current status of epilepsy treatment in rural areas， the dose of phenobarbital， and the frequency of seizures. In the epilepsy prevention and management project of Heilongjiang Province in 2015—2020， a total of 908 patients with convulsive epilepsy were enrolled in the phenobarbital treatment group， and after standardized treatment and follow-up management， 698 patients were followed up for at least 12 months. Results The gap rate of rural epilepsy treatment in Heilongjiang Province was 56.39%. After one year of standardized treatment， the frequency of seizures decreased from 23.86 times/year before enrollment to 3.11 times/year， showing a significant reduction. The response rate of epilepsy treatment was 68.19%， and the patients without previous standard treatment tended to have a better outcome than those who received standard treatment. Conclusion The current status of epilepsy treatment is not optimistic in rural areas of Heilongjiang Province， and there remains a large gap in epilepsy treatment. It is necessary to strengthen the training on the diagnosis and treatment of epilepsy among primary care physicians and implement the public education on the prevention and treatment of epilepsy， and since phenobarbital has a marked clinical effect in the treatment of epilepsy， it holds promise for further application in rural areas.
Phenobarbital

Head and neck squamous cell carcinoma (HNSCC) is the most common type of heterogeneous malignant tumor. Over 60% of HNSCC patients are at locally advanced stage at the time of diagnosis. Despite the emergence of advanced diagnosis and treatment measures, the prognosis of patients with recurrent or metastatic HNSCC remains poor. The Period (PER) gene family is an important member of the circadian clock genes, with family members PER1, PER2, and PER3 showing differential expression in HNSCC, participating in biological processes such as proliferation, apoptosis, invasion, or metastasis of tumor cells. In most studies, they exhibit anti-cancer effects and are closely related to the tumor microenvironment, immunotherapy, chronotherapy, etc., making them potential biomarkers. A comprehensive analysis of the expression of PER gene family in HNSCC, its biological role in the occurrence and development of tumor and the corresponding molecular biological mechanism is helpful to explore its potential application value in the diagnosis and treatment of HNSCC.

Objective:To analyze the association between moderate-to-vigorous-physical activity (MVPA) and obesity, poor sleep quality, as well as multimorbidity in 7- to 8-year-old children in Shanghai City.Methods:From September to November 2023, a cluster sampling method was used to select second-grade students from four primary schools in Jinshan District, Shanghai. Three-axis acceleration motion sensors (GT3X+, Acti-graph) were used to monitor daily physical activity for seven consecutive days. A multivariate logistic regression model was used to analyze the association between MVPA duration characteristics and obesity, poor sleep quality and multimorbidity in school-age children.Results:Of the 937 study participants, 512 (54.64%) were boys and 425 (45.36%) were girls. Among them, 89 (9.50%) were obese and 782 (83.46%) had poor sleep quality. A total of 77 cases (8.22%) were affected by obesity and poor sleep quality. The average daily MVPA time was (45.97±15.87) minutes, and the MVPA attainment rate was 17.18%. The multivariate logistic regression model analysis showed that, after adjusting for covariates, the daily average MVPA time was negatively associated with the risk of obesity ( OR=0.982, 95% CI: 0.968-0.997), as well as multimorbidity ( OR=0.981, 95% CI: 0.965-0.997). The risk of obesity, poor sleep quality and multimorbidity in <1 d was 2.228 ( OR=2.228, 95% CI: 1.398-3.549), 1.702 ( OR=1.702, 95% CI: 1.141-2.540) and 2.150 ( OR=2.150, 95% CI: 1.310-3.528) times higher than that in ≥1 d. Conclusion:Obesity, poor sleep quality and multimorbidity of school-age children are closely related to the level of moderate-to-vigorous physical activity.