BackgroundCurrently， the incidence of depression among teenagers is on the rise， and the related academic problems are becoming increasingly serious. Short video addiction has a negative impact on teenagers' emotional issues and academic achievements. However， few studies have explored the relationship between this addiction and the learning burnout of teenagers with depression， and even fewer have focused on the role paths of impulsivity and coping disposition in this process. ObjectiveTo explore the relationship between short video addiction and learning burnout in adolescent patients with depression， as well as the pathway of impulsivity and coping disposition， so as to provide references for the intervention of learning burnout in adolescent patients with depression. MethodsA total of 191 adolescent patients who were hospitalized at The Affiliated Brain Hospital of Guangzhou Medical University from December 2024 to April 2025 and met the diagnostic criteria for depression according to the International Classification of Diseases， tenth edition （ICD-10） were selected consecutively. The Short Video Addiction Measurement Scale （SVAMS）， the Brief Barratt Impulsiveness Scale （BBIS）， the Simplified Coping Style Questionnaire （SCSQ）， and the Adolescent Student Burnout Inventory （ASBI） were used for assessment. Pearson correlation analysis was employed to examine the correlations of the scores of each scale. Model 6 of the SPSS macro Process 4.2 was employed to analyze the chained mediation pathway of impulsivity and coping disposition between short video addiction and learning burnout. ResultsA total of 173 cases （90.58%） of adolescent patients with depression completed the valid questionnaire survey. Correlation analysis showed that SCSQ coping disposition score was negatively correlated with the SVAMS score， the BBIS score， and the ASBI score （r=-0.282， -0.341， -0.431， P<0.01）， the SVAMS score was positively correlated with the BBIS score and the ASBI score （r=0.339， 0.262， P<0.01）， and the BBIS score was positively correlated with the ASBI score （r=0.486， P<0.01）. The pathway analysis showed that the direct effect of short video addiction on learning burnout was not statistically significant， but the total effect and the indirect effect were statistically significant. The effect values were 0.275 （95% CI： 0.207–0.343） and 0.193 （95% CI： 0.143–0.246）， respectively， with the indirect effect accounting for 70.18%. Impulsivity and coping disposition both played independent mediating roles between short video addiction and learning burnout， with effect values of 0.122 （95% CI： 0.090–0.156） and 0.054 （95% CI： 0.032–0.079）， accounting for 44.36% and 19.64% of the total effect， respectively. The chained mediation effect of impulsivity and coping disposition was significant， with an effect value of 0.017 （95% CI： 0.011–0.026）， accounting for 6.18% of the total effect. ConclusionAlthough short video addiction does not directly affect learning burnout in adolescent patients with depression， it may indirectly influence learning burnout through independent and chain paths of impulsivity and coping disposition. ［Funded by Guangzhou Key Clinical Specialty （Clinical Medical Research Institute）］

Objective To explore the effect of 5A nursing model combined with empowerment health education in the perioperative period of laryngeal cancer.Methods Eighty patients with laryngeal cancer admitted to Department of Otolaryngology of The First Affiliated Hospital of Naval Medical University from January 2021 to December 2022 were selected as study subjects.Forty patients admitted between January and December 2021 were assigned to control group,and 40 patients admitted between January and December 2022 were divided into observation group.The patients of both groups received unified surgical treatment.During perioperative period,the control group received routine nursing intervention,and the observation group was given 5A nursing model combined with empowerment health education on the basis of routine nursing.Self-care ability,psychological resilience,compliance rate,complication rate,and quality of life scores were compared between the two groups.The patients of both groups were intervened until 3 months after surgery.Results After 3-month intervention,the exercise of self-care agency(ESCA)scores of the observation group in the terms of self-care skills,self-responsibility,self-concept,and health knowledge were higher than those of the control group(P＜0.05).After intervention,the scores of the Connor-Davidson Resilience Scale(CD-RISC)of the observation group in the terms of resilience,self-reliance,and optimism,were higher than those in the control group(P＜0.05).After intervention,the rates of compliance behaviors in the observation group,including taking medication on time,taking regular rest,quitting smoking and alcohol,eating reasonably,exercising moderately,and taking regular reexaminations,were higher than those in the control group(P＜0.05).After intervention,the incidence of complications in the observation group was 7.50%(3/40),which was significantly lower than that in the control group(25.00%[10/40],P＜0.05).After intervention,the scores of the generic quality of life inventory-74(GQOL-74)of the observation group in the terms of physical function,psychological function,social function,and material life status were higher than those in the control group(P＜0.05).Conclusion 5A nursing model combined with empowerment health education used in the perioperative period has a good effect in patients with laryngeal cancer,which can enhance patient's self-care ability,improve psychological resilience and compliance behaviors,reduce the postoperative complications,and improve quality of life.

Objective    To explore the application value of machine learning models in predicting postoperative survival of patients with thoracic squamous esophageal cancer. Methods    The clinical data of 369 patients with thoracic esophageal squamous carcinoma who underwent radical esophageal cancer surgery at the Department of Thoracic Surgery of Northern Jiangsu People's Hospital from January 2014 to September 2015 were retrospectively analyzed. There were 279 (75.6%) males and 90 (24.4%) females aged 41-78 years. The patients were randomly divided into a training set (259 patients) and a test set (110 patients) with a ratio of 7 : 3. Variable screening was performed by selecting the best subset of features. Six machine learning models were constructed on this basis and validated in an independent test set. The  performance of the models' predictions was evaluated by area under the curve (AUC), accuracy and logarithmic loss, and the fit of the models was reflected by calibration curves. The best model was selected as the final model. Risk stratification was performed using X-tile, and survival analysis was performed using the Kaplan-Meier method with log-rank test. Results    The 5-year postoperative survival rate of the patients was 67.5%. All clinicopathological characteristics of patients between the two groups in the training and test sets were not statistically different (P>0.05). A total of seven variables, including hypertension, history of smoking, history of alcohol consumption, degree of tissue differentiation, pN stage, vascular invasion and nerve invasion, were included for modelling. The AUC values for each model in the independent test set were: decision tree (AUC=0.796), support vector machine (AUC=0.829), random forest (AUC=0.831), logistic regression (AUC=0.838), gradient boosting machine (AUC=0.846), and XGBoost (AUC=0.853). The XGBoost model was finally selected as the best model, and risk stratification was performed on the training and test sets. Patients in the training and test sets were divided into a low risk group, an intermediate risk group and a high risk group, respectively. In both data sets, the differences in surgical prognosis among three groups were statistically significant (P<0.001). Conclusion    Machine learning models have high value in predicting postoperative prognosis of thoracic squamous esophageal cancer. The XGBoost model outperforms common machine learning methods in predicting 5-year survival of patients with thoracic squamous esophageal cancer, and it has high utility and reliability.

Objective To study the relationship between CDC25A (cell division cycle 25A) expression and the development of gastric adenocarcinoma. hTe effect of artesunate (Art) on CDC25A and gastric cancer cells were also investigated.Methods hTe CDC25A protein expression in gastric adenocarcinoma was detected by lfow cytometry assay. SGC-7901 cells were divided into four groups: control group and 30, 60, 120μmol/L Art groups. Cell apoptosis, cell cycle and CDC25A protein expression in SGC-7901 cells were determined by lfow cytometry atfer the treatment of different concentrations of Art (30, 60, 120μmol/L) for 24h, while the same volume of saline was used in the control.Results CDC25A protein expression level in gastric adenocarcinoma (419.69±21.91) was signiifcantly higher than that in normal gastric tissues (316.11±24.23,P<0.01). hTe cell apoptosis rates of 30, 60, 120μmol/L Art groups (5.48%±0.67%, 12.55%±1.17%, 23.43%±2.18%) were significantly higher than that of control group (0.87%±0.14 %,P<0.05), with an Art dose dependent manner. hTe cell proliferation indices of 30, 60, 120μmol/L Art groups (39.18%±0.53%, 35.71%±0.99%, 31.73%±1.02%) were signiifcantly lower than that of control group (44.12%±2.51%,P<0.01). hTe CDC25A protein expression levels of 30, 60, 120μmol/L Art groups (414.80±4.06, 397.86±3.61, 345.68±7.11) were significantly lower than that of control group (433.99±1.56,P<0.01).ConclusionhTe abnormally increased expression level of CDC25A may be involved in the development of gastric adenocarcinoma. Art can inhibit the growth of SGC-7901 cells by down-regulating the expression of CDC25A protein.