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.

This paper summarizes clinical experience in treating acne based on the staged therapeutic principles of "eruption in warm diseases". It is considered that acne results from wind-heat retained in the lungs， invading the ying level and obstructing the blood collaterals， and is primarily a disorder involving both the wei and ying systems. In clinical practice， the treatment emphasizes the use of acrid-cool and sweet-cold methods. The core prescription is namely Yinqiaosan Qu Douchi Jia Xishengdi Danpi Daqingye Bei Xuanshen Fang （from Epidemic Warm Diseases ［《温病条辨》］）， and is adjusted according to the stage of disease. In the non-inflammatory stage， when the pathogen initially attacks the wei level， treatment focuses on acrid-cool herbs to release the exterior， with supplementary bitter-sweet ingredients such as Yejuhua （Chrysanthemum Indicum）. In the inflammatory stage， with pronounced heat toxin in the qi level affecting the ying and blood， and local stagnation of qi and blood， the approach is to clear heat and resolve toxin， using blood-cooling and stasis-resolving herbs early to prevent progression. Herbs such as Pugongying （Taraxacum Mongolicum）， Zihuadiding （Viola Yedoensis）， Tiankuizi （Semiaquilegia Adoxoides）， Chonglou （Paris Polyphylla）， Machixian （Portulaca Oleracea）， Zaojiaoci （Gleditsia Sinensis）， Chuanshanjia （Manis Pentadactyla） may be added. In the post-inflammatory erythema stage， when yin of the ying level is depleted and internal deficiency-heat arises， sweet-cold herbs are recommended to nourish the stomach and generate fluids， with the possible addition of Yiwei Decoction （益胃汤）.

OBJECTIVE To investigate the effects of polydatin （PD） on cell proliferation， migration， invasion and tumor growth of acute myeloid leukemia （AML）. METHODS Human AML cell KG-1 were divided into normal group， PD low-， medium- and high-concentration groups （10， 30， 60 μmol/L PD）， SQ22536 group [cyclic adenosine monophosphate （cAMP） inhibitor， 100 μmol/L]， high concentration of PD+SQ22536 group （60 μmol/L PD+100 μmol/L SQ22536）. The effects of PD on cell activity， apoptotic rate， invasion and migration ability， cAMP level， the expression of epithelial-mesenchymal transition （EMT） related proteins and protein kinase A （PKA） were investigated. Using BALB/c nude mice as subjects， a transplanted tumor model of AML nude mice was induced by subcutaneous inoculation of KG-1 cell suspension and then divided into control group， PD group， SQ22536 group and PD+SQ22536 group （with 6 mice in each group）. The effects of PD on tumor volume and mass were measured. RESULTS Compared with the normal group or control group， the cell viabilities， the number of migrating cells， the number of invasive cells， the relative expressions of vimentin and Snail as well as the tumor volume and mass were decreased significantly in PD groups， while the apoptotic rates， cAMP levels， the relative expressions of E-cadherin and PKA were significantly increased， with a dose-dependent manner （P＜0.05）. SQ22536 had opposite effects on cells and nude mice compared to PD， and could significantly reverse the anti-tumor activity of PD （P＜0.05）. CONCLUSIONS PD may inhibit the proliferation， migration， invasion and EMT process of KG-1 cells， induce apoptosis， and inhibit tumor growth， by activating the cAMP/PKA signaling pathway， thereby exerting anti-AML effects.

OBJECTIVE To provide a detailed report and interpretation of the method and results for determining the weights of the technical indicators from the “multi-dimensional and multi-criteria comprehensive evaluation index system （first edition）” stated in Guideline for Multi-dimensional and Multi-criteria Comprehensive Evaluation of Chinese Patent Medicine. METHODS Normalization calculations were performed on the comprehensive weight values calculated by the analytic hierarchy process and expert weighting method to obtain the objective weights of the indicators. RESULTS The weight results of the six primary dimensions in the current comprehensive evaluation indicator system of Chinese patent medicine showed effectiveness dimension＞ safety dimension＞standard dimension＞application dimension＞scientific dimension＞economic dimension， with weight values of 0.281 0， 0.268 5， 0.195 8， 0.107 3， 0.096 1 and 0.051 3 respectively， consistent with the results of most researches currently. CONCLUSIONS The process of weight determination in this indicator system is scientifically reasonable， with clear methods and clear interpretations， and is worthy of further optimization and widespread application.

Objective To investigate the expression and significance of microRNA(miR)-4429 and microRNA(miR)-19-3p level in patients with pelvic floor dysfunctional(PFD)disease.Methods A total of 90 PFD patients admitted to the Second People's Hospital of Hengshui from June 2021 to June 2022 were selected as the PFD group.They were grouped into the pelvic organ prolapse(POP)group(n=50),the stress urinary incontinence(SUI)group(n=25),and the POP combined with SUI group(n=15).Meanwhile,80 healthy women who were examined in the Second People's Hospital of Hengshui were collected as the control group.The general data such as delivery mode,previous abortion history and family history were compared between the control group and the PFD group.The levels of serum miR-4429 and miR-19-3p in each group were compared.The diagnostic value of serum miR-4429 and miR-19-3p levels in PFD was analyzed by receiver operating characteristic(ROC)analysis.Logistic regression analysis was applied to analyze the factors affecting PFD.The paired sample t-test was applied to compare the changes in serum miR-4429 and miR-19-3p levels before and after PFD treatment.Results There were significant differences between the PFD group and the control group in terms of delivery mode,previous abortion history,and PFD family history,and the differences were statistically significant(t=4.415,6.444,4.707,all P＜0.05).The serum miR-4429(0.71±0.19 vs 1.00±0.25)level in the PFD group was lower than that in the control group,while the miR-19-3p(1.44±0.35 vs 1.01±0.28)level was higher than that in the control group,and the differences was statistically significant(t=8.927,8.772,all P＜0.05).The serum miR-4429(0.73±0.22,0.74±0.16 vs 0.59±0.16)level in the POP and SUI groups was higher than that in the POP combined SUI group,while the serum miR-19-3p(1.35±0.39,1.41±0.31 vs 1.77±0.56)level in the POP group and SUI group was lower than that in the POP combined with SUI group,with significant differences(t=3.531,3.411;5.003,3.865,all P＜0.05).ROC analysis showed that the areas under curve(AUC)for miR-4429 and miR-19-3p to assist in assessing whether PFD occurs were 0.805 and 0.825,respectively.The AUC of the combined detection was 0.865.Multivariate logistic regression analysis showed that miR-19-3p was a risk factor affecting PFD,while miR-4429 was a protective factor.After treatment,serum miR-4429(0.93±0.23 vs 0.71±0.19)level in PFD patients increased,while the miR-19-3p(1.12±0.29 vs 1.44±0.35)level decreased,the diffences were statistically significant(t=6.996,6.679,all P＜0.05).Conclusion The serum miR-4429 level in patients with PFD decreased,while the miR-19-3p level increased.The levels of miR-4429 and miR-19-3p in serum were closely related to the occurrence and development of PFD diseases,which can be used as evaluation indicators to predict PFD.