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 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

ObjectiveTo observe the clinical effectiveness and safety of Xuandi Ziyin Mixture （玄地滋阴合剂） for central precocious puberty （CPP） in girls with syndrome of yin deficiency and fire exuberance， and to analyse the effect of body mass index （BMI） on the effectiveness. MethodsA total of 236 girls with CPP of yin deficiency and fire exuberance syndrome were included， and all of them were given Xuandi Ziyin Mixture， 30 ml each time， twice a day， for a total treatment period of 6 months. Before and after treatment， children's weight， height and bone age were measured， BMI and BMI Z-score （BMI Z） and the difference between bone age and actual age were calculated； ultrasound was used to detect uterine and ovarian sizes， and to calculate uterine volume （V_uterus）， bilateral ovarian volume （V_{left ovary}， V_{right ovary}）， and bilateral maximal follicle diameters （r_{left follicle} and r_{right follicle}）； and serum sex hormones were measured， including follicle-stimulating hormone （FSH）， luteinising hormone （LH）， prolactin （PRL）， estradiol （E₂）， and testosterone （T）， and were scored for traditional Chinese medicine （TCM） syndrome. Multiple linear regression was used to analyse the influence factors of the difference between bone age and actual age， and changes in uterine volume. The children were divided into the normal weight group and the overweight/obesity group according to baseline BMI， and the bone age， the difference between bone age and actual age， V_uterus and BMI Z scores before and after treatment were compared between the two groups. ResultsFinally， 199 children entered the statistical analysis. Compared with pre-treatment， the bone age， BMI and BMI Z scores of the children increased after treatment， and the difference between bone age and actual age， TCM syndrome scores， V_uterus， V_{left ovary}， V_{right ovary}， r_{left follicle} and r_{right follicle} decreased； and the levels of serum FSH， LH， E₂， and T significantly decreased （P＜0.05 or P＜0.01）. The difference between bone age and actual age was negatively correlated with LH and V_uterus （P＜0.05）， and changes in uterine volume were positively correlated with LH （P＜0.01）. Comparing between the groups before and after treatment， the bone age， difference between bone age and actual age， and BMI Z scores of children in the normal weight group （100 cases） were significantly smaller than those in the overweight/obesity group （99 cases） （P＜0.01）. Compared with pre-treatment， the bone age of the children in both groups increased， but the difference between bone age and actual age and V_uterus were significantly smaller （P＜0.01）. Further comparison of Δ bone age and actual age difference and ΔV_uterus （Δ = post-treatment value - pre-treatment value） between the two groups showed no statistically significant difference （P＞0.05）. ConclusionsXuandi Ziyin Mixture can reduce bone age， sex hormone level， ovary and uterus size， and improve clinical symptoms in girls with yin deficiency and fire exuberance syndrome of CPP. It is also effective in overweight/obese children， and the inhibitory effect on bone age in girls with CPP is not affected by BMI， with good safety.

The retrieval and evaluation of evidence is the basis for the development of clinical practice guidelines for Chinese patent medicine. As traditional Chinese medicine has a different development trajectory and utilization characteristics from modern medicine， there is certain differences in terms of evidence composition， retrieval and integration.This paper discussed multi-source body of evidence on Chinese patent medicine based on modern evidence-based medicine and ancient medical literature， and summarized the retrieval strategy as well as the possible problems and solving methods. For different types of evidence on Chinese patent medicine， the corresponding evaluation tools have been recommended， and the order to integrate the evidence based on the quality of the evidence from high to low is suggested. Finally， a multi-source based evidence retrieval-evaluation-integration scheme for Chinese patent medicine has been formed， which will provide a methodological reference for practitioners in the development of clinical practice guidelines for Chinese patent medicine.

Background::Heterotaxy (HTX) is a thoracoabdominal organ anomaly syndrome and commonly accompanied by congenital heart disease (CHD). The aim of this study was to analyze rare copy number variations (CNVs) in a HTX/CHD cohort and to examine the potential mechanisms contributing to HTX/CHD.Methods::Chromosome microarray analysis was used to identify rare CNVs in a cohort of 120 unrelated HTX/CHD patients, and available samples from parents were used to confirm the inheritance pattern. Potential candidate genes in CNVs region were prioritized via the DECIPHER database, and PNPLA4 was identified as the leading candidate gene. To validate, we generated PNPLA4-overexpressing human induced pluripotent stem cell lines as well as pnpla4-overexpressing zebrafish model, followed by a series of transcriptomic, biochemical and cellular analyses. Results::Seventeen rare CNVs were identified in 15 of the 120 HTX/CHD patients (12.5%). Xp22.31 duplication was one of the inherited CNVs identified in this HTX/CHD cohort, and PNPLA4 in the Xp22.31 was a candidate gene associated with HTX/CHD. PNPLA4 is expressed in the lateral plate mesoderm, which is known to be critical for left/right embryonic patterning as well as cardiomyocyte differentiation, and in the neural crest cell lineage. Through a series of in vivo and in vitro analyses at the molecular and cellular levels, we revealed that the biological function of PNPLA4 is importantly involved in the primary cilia formation and function via its regulation of energy metabolism and mitochondria-mediated ATP production. Conclusions::Our findings demonstrated a significant association between CNVs and HTX/CHD. Our data strongly suggested that an increased genetic dose of PNPLA4 due to Xp22.31 duplication is a disease-causing risk factor for HTX/CHD.