ObjectiveTo verify the protective effect and pharmacological mechanism of Qishen granules against doxorubicin-induced cardiotoxicity， thus providing a basis for developing new drug options for clinical treatment of cardio-oncology disease. MethodsFifty mice were randomly assigned into a normal group （n=10） and a modeling group （n=40）. The model was established by intravenous injection of doxorubicin （5 mg·kg^-1） via the tail vein， once a week for 4 consecutive weeks. The normal group was injected with an equal volume of normal saline during the same period. The modeled mice were further assigned into four groups： doxorubicin （no drug control）， low-dose （3.33 mg·kg^-1） Qishen granules， high-dose （6.67 mg·kg^-1） Qishen granules， and enalapril （15 mg·kg^-1）. Mice were administrated with corresponding drugs by gavage for 4 consecutive weeks. At the end of the experiment， echocardiography， histopathological staining， and live-cell imaging were employed to determine relevant indicators， on the basis of which the protective effect of Qishen granules against doxorubicin-induced cardiotoxicity was evaluated. ResultsCompared with the normal group， doxorubicin treatment reduced the left ventricular ejection fraction （LVEF） （P<0.05） and caused pathological changes including disarrangement of cardiomyocytes， increased cell spacing， cardiomyocyte hypertrophy， and increased apoptosis in the heart tissue. Meanwhile， doxorubicin prolonged the mitochondria-lysosome contact time， downregulated the expression of TBC1 domain family member 15 （TBC1D15） （P<0.01）， upregulated the levels of microtubule-associated protein 1 light chain 3 （LC3） and sequestosome 1 （p62） （P<0.01）， and induced mitochondrial cristae breakage， resulting in mitochondrial dysfunction. Compared with the doxorubicin group， intervention with Qishen granules reversed the above indicators. It not only increased the LVEF （P<0.01） and alleviated pathological damage to the heart， but also upregulated the expression of TBC1D15 （P<0.01）， shortened the mitochondria-lysosome contact time （P<0.05）， and downregulated the protein levels of LC3 and p62. When TBC1D15 in cells was knocked down， the autophagy-activating and mitochondrion-protecting effects of Qishen granules partially disappeared. ConclusionQishen granules upregulate the expression of TBC1D15 to shorten the mitochondria-lysosome contact time， thereby activating autophagy and ultimately exerting a protective effect against doxorubicin-induced cardiotoxicity.

ObjectiveTo verify the protective effect and pharmacological mechanism of Qishen granules against doxorubicin-induced cardiotoxicity， thus providing a basis for developing new drug options for clinical treatment of cardio-oncology disease. MethodsFifty mice were randomly assigned into a normal group （n=10） and a modeling group （n=40）. The model was established by intravenous injection of doxorubicin （5 mg·kg^-1） via the tail vein， once a week for 4 consecutive weeks. The normal group was injected with an equal volume of normal saline during the same period. The modeled mice were further assigned into four groups： doxorubicin （no drug control）， low-dose （3.33 mg·kg^-1） Qishen granules， high-dose （6.67 mg·kg^-1） Qishen granules， and enalapril （15 mg·kg^-1）. Mice were administrated with corresponding drugs by gavage for 4 consecutive weeks. At the end of the experiment， echocardiography， histopathological staining， and live-cell imaging were employed to determine relevant indicators， on the basis of which the protective effect of Qishen granules against doxorubicin-induced cardiotoxicity was evaluated. ResultsCompared with the normal group， doxorubicin treatment reduced the left ventricular ejection fraction （LVEF） （P<0.05） and caused pathological changes including disarrangement of cardiomyocytes， increased cell spacing， cardiomyocyte hypertrophy， and increased apoptosis in the heart tissue. Meanwhile， doxorubicin prolonged the mitochondria-lysosome contact time， downregulated the expression of TBC1 domain family member 15 （TBC1D15） （P<0.01）， upregulated the levels of microtubule-associated protein 1 light chain 3 （LC3） and sequestosome 1 （p62） （P<0.01）， and induced mitochondrial cristae breakage， resulting in mitochondrial dysfunction. Compared with the doxorubicin group， intervention with Qishen granules reversed the above indicators. It not only increased the LVEF （P<0.01） and alleviated pathological damage to the heart， but also upregulated the expression of TBC1D15 （P<0.01）， shortened the mitochondria-lysosome contact time （P<0.05）， and downregulated the protein levels of LC3 and p62. When TBC1D15 in cells was knocked down， the autophagy-activating and mitochondrion-protecting effects of Qishen granules partially disappeared. ConclusionQishen granules upregulate the expression of TBC1D15 to shorten the mitochondria-lysosome contact time， thereby activating autophagy and ultimately exerting a protective effect against doxorubicin-induced cardiotoxicity.

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.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

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.

Objective To explore a nomogram of intratumor and peritumor radiomics based on enhanced CT venous phase to pre-operatively predict the pathological grade of poorly differentiated esophageal squamous cell carcinoma(ESCC).Methods A retro-spective selection was made of 266 ESCC patients confirmed by pathology(76 cases of poorly differentiated;190 cases of non-poorly differentiated),and all patients were randomly divided into training set(n=186),validation set(n=80),and full data set(n=266).Tumors were segmented on the enhanced CT venous phase to create three-dimensional region of interest(ROI)of intratumor,peritu-mor 0.3 cm,and intratumor+peritumor 0.3 cm.A total of 2 553 radiomics features were extracted.After feature dimensionality reduc-tion,XGboost machine learning algorithm was utilized to rank the top fifteen features.Stepwise forward multiple logistic regression was employed to identify the most significant features.The radiomics scores of the intratumor,peritumor 0.3 cm,and intratumor+peritu-mor 0.3 cm were calculated.The diagnostic efficacy of the model was evaluated using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).Results The nomogram constructed based on radiomics scores of intratumor,peritumor 0.3 cm,intratumor+peritumor 0.3 cm in the training set for preoperative prediction of poorly differentiated ESCC had an AUC of 0.899[95％confidence interval(CI)0.846-0.938],and it was well validated in the vali-dation set(AUC 0.869,95％CI 0.775-0.934)and the full data set(AUC 0.889,95％CI 0.845-0.924).Additionally,calibration curves and DCA indicated that the nomogram achieved good calibration ability in the three cohorts and offered greater clinical net benefit.Conclusion The nomogram based on enhanced CT venous phase intratumor and peritumor radiomics achieves a high and stable diagnostic efficacy for preoperatively predicting poorly differentiated ESCC,which may help with individualized surgical selec-tion and management before surgery.

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 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.