Objective To observe the association between afterschool physical exercise and sleep quality among preschool children,and to explore the proper afterschool physical exercise model for better sleep quality.Methods A cross-sectional study was conducted.From Apr to Jun 2024,a total of 1 430 children from three public kindergartens in Minhang district were enrolled to participate in the survey.Parents were invited to complete the basic sociodemographic information,afterschool physical exercise information and the Children's Sleep Habits Questionnaire.One-way ANOVA and linear mixed effects models were used to explore the relationship between afterschool exercise and sleep quality.Results A total of 1 430 questionnaires were sent out and 1 384 were recovered with a recovery rate of 96.78%.Among them 1 366 were valid,with an effective rate of 95.52%.The average age of the children was(5.19±0.87)years old with gender ration of 1.07∶1(male:female).The prevalence of poor sleep quality was 80.60%(regarding a CSHQ total score>41 as cutoff).A one-way ANOVA indicated that time on afterschool physical exercise was significantly associated with sleep duration,Night waking,and sleep onset delay(P<0.05).After adjusting for age,gender,the only child or not,main caregiver,and parental education and occupation,linear mixed effects models showed that engaging in afterschool physical activity for at least 180 mins per week has a statistically significant predictive effect on sleep duration scores(β=-0.50,z=-4.52,95%CI:-0.72,-0.28,P<0.001),night waking scores(β=-0.16,z=-2.34,95%CI:-0.29,-0.02,P=0.020),and sleep onset delay scores(β=-0.14,z=-2.35,95%CI:-0.26,-0.02,P=0.019).Conclusion Afterschool exercise was significantly associated with sleep quality among preschool children in Minhang district of Shanghai.The time≥180 min on afterschool exercise per week in preschool children was significantly positively associated with maintaining sleep duration,reducing night wakings and shortening the latency to fall asleep.The habit of afterschool exercise and the time on afterschool exercise should be emphasized by parents and the society to improve sleep quality among preschool children.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective To observe the association between afterschool physical exercise and sleep quality among preschool children,and to explore the proper afterschool physical exercise model for better sleep quality.Methods A cross-sectional study was conducted.From Apr to Jun 2024,a total of 1 430 children from three public kindergartens in Minhang district were enrolled to participate in the survey.Parents were invited to complete the basic sociodemographic information,afterschool physical exercise information and the Children's Sleep Habits Questionnaire.One-way ANOVA and linear mixed effects models were used to explore the relationship between afterschool exercise and sleep quality.Results A total of 1 430 questionnaires were sent out and 1 384 were recovered with a recovery rate of 96.78%.Among them 1 366 were valid,with an effective rate of 95.52%.The average age of the children was(5.19±0.87)years old with gender ration of 1.07∶1(male:female).The prevalence of poor sleep quality was 80.60%(regarding a CSHQ total score>41 as cutoff).A one-way ANOVA indicated that time on afterschool physical exercise was significantly associated with sleep duration,Night waking,and sleep onset delay(P<0.05).After adjusting for age,gender,the only child or not,main caregiver,and parental education and occupation,linear mixed effects models showed that engaging in afterschool physical activity for at least 180 mins per week has a statistically significant predictive effect on sleep duration scores(β=-0.50,z=-4.52,95%CI:-0.72,-0.28,P<0.001),night waking scores(β=-0.16,z=-2.34,95%CI:-0.29,-0.02,P=0.020),and sleep onset delay scores(β=-0.14,z=-2.35,95%CI:-0.26,-0.02,P=0.019).Conclusion Afterschool exercise was significantly associated with sleep quality among preschool children in Minhang district of Shanghai.The time≥180 min on afterschool exercise per week in preschool children was significantly positively associated with maintaining sleep duration,reducing night wakings and shortening the latency to fall asleep.The habit of afterschool exercise and the time on afterschool exercise should be emphasized by parents and the society to improve sleep quality among preschool children.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Objective This study aimed to provide an effective scientific basis for prevention and control of cockroaches on aircrafts by identifying cockroach-carried pathogens,and assess the insecticidal efficacy of gel bait mediated cockroach control on aircrafts,to provide technical guidance for aircraft disinsection.Methods Cassette-trapping was used to trap cockroaches,and the carried pathogens were detected using bacterial cultivation techniques.The gel bait mediated killing rate was calculated after 1,7,and 30 d by field application of gel bait.Results A total of 411 cockroaches were captured,and all were identified as Blattella germanica.26 strains of pathogenic bacteria were isolated from the trapped cockroaches.The killing rates of cockroaches were 58.8％-96.3％with 1-30 day application of gel bait.Statistically significant differences were observed in cockroach killing rates on different days(χ2=58.95,P<0.01).Conclusions B.germanica carry a large variety of pathogenic bacteria and opportunistic pathogens and are thus important infectious disease carriers.Gel bait agents have proven to be very effective against cockroaches on aircrafts.

Objective:To examine the near-complete genomic analysis of norovirus (NoV) subtype GⅡ.17 [P17] outbreaks in Beijing Chaoyang District from 2014 to 2024.Methods:Data and specimens related to outbreaks of the NoV aggregation in Beijing′s Chaoyang District from 2014 to 2024 were collected. The NoV was identified using real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR). Specimens with positive nucleic acid were amplified by standard PCR, whole genome sequencing and evolutionary analysis. Amino acid site variations were compared.Results:In Chaoyang District, from 2014 to 2024, a total of 637 aggregated outbreaks caused by the NoV infection were reported, of which 584 were successfully typed. The epidemic caused by the GⅡ.17 [P17] subtype accounted for 8.79% (56/637), which was the dominant epidemic gene subtype in 2014-2015, sporadic in 2016-2019, reappeared in 2022, and significantly increased in 2024 (27.27%, 24/88). Outbreaks caused by the GⅡ.17 [P17] subtype occurred mainly from October to December, with the main sites of occurrence in primary schools and kindergartens. This study yielded 53 near-complete genome sequences of the GⅡ.17 [P17] subtype from 46 incidents in Chaoyang District. The GⅡ.17 [P17] subtype sequences of Chaoyang District from 2014 to 2024 were segmented into three subgroups on the evolutionary tree, with sequences from 2014 to 2019, 2022 to April 2024, and May to December 2024 clustered into the d, e, and b subgroups, respectively. In the VP1 region′s P2 area, particularly at the HBGA binding site, subgroups b and e exhibited mutations in 22 and two sites, while subgroups b and e showed mutations in four and one sites, predominantly in the RdRp region.Conclusion:The outbreak caused by the NoV GⅡ.17 [P17] subtype in Chaoyang District from 2014 to 2024 continues, with a significant increase in 2024, and it becomes the dominant gene subtype from October to December. The sequence formation of the NoV GⅡ.17 [P17] subtype in Chaoyang District from January to April 2022 and from May to December 2024 shows two different evolutions, with specific mutation sites, requiring continuous monitoring of the NoV GⅡ.17 [P17] subtype.

This case report summarizes the nursing experience in ensuring medication safety during intranasal esketamine spray treatment for a patient with treatment-resistant depression.Key nursing interventions included:pre-treatment assessment of concomitant medication risks,preparation of staff,environment,and medications;during treatment,strict adherence to administration protocols with simultaneous respiratory function monitoring and nasal tolerability assessment to minimize respiratory depression risk;post-treatment blood pressure surveillance combined with longitudinal symptom tracking and dynamic suicide risk evaluation for self-harm prevention;reinforcement of adverse reaction prevention and management.After completing the full 4-week treatment course(8 sessions),the patient exhibited the improved depressive symptoms and the reduced suicidal ideation,and the patient was successfully discharged.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Objective:To identify risk factors for developing infected pancreatic necrosis (IPN) in female hypertriglyceridemia-induced acute pancreatitis (HTG-AP) patients with childbearing age.Methods:A retrospective analysis was conducted on clinical data from 460 female HTG-AP patients with childbearing age admitted to Eastern Theater General Hospital of the Chinese People's Liberation Army between December 2013 and December 2022. Patients were divided into the IPN group ( n=140) and non-IPN group ( n=320) based on the occurrence of IPN. General clinical data, laboratory test results and clinical outcomes were compared between the two groups. Univariate and multivariate logistic regression models were used to analyze the risk factors for IPN in reproductive-age HTG-AP patients. Results:Among the 460 patients, 140 (30.4%) developed IPN. Compared with the non-IPN group, the IPN group had a significantly higher proportion of pregnant patients (30.0% vs 10.9%, P<0.001) and a lower proportion with a history of acute pancreatitis (12.9% vs 31.3%, P<0.001). Laboratory findings showed that patients in the IPN group had lower levels of hemoglobin and albumin, but higher levels of blood urea nitrogen and serum creatinine. Clinical outcomes showed that the IPN group had significantly higher rates of severe acute pancreatitis and mortality compared to the non-IPN group. Additionally, the median length of ICU stay and total hospital stay in the IPN group were significantly longer, at 16.5 days and 32.0 days, respectively. Univariate logistic regression analyses showed that pregnancy, previous history of acute pancreatitis, and levels of hemoglobin, total bilirubin, albumin, blood urea nitrogen and creatinine were significantly associated with IPN. Multivariate logistic regression analysis revealed that pregnancy ( OR=2.617, 95% CI 1.494-4.210, P=0.001), a history of acute pancreatitis ( OR=0.339, 95% CI 0.189-0.711, P=0.002), hemoglobin level ( OR=0.945, 95% CI 0.939-0.987, P<0.001), and blood urea nitrogen level ( OR=1.173, 95% CI 1.056-1.198, P=0.004) were independently associated with the occurrence of IPN. Conclusions:Pregnancy, a first episode of acute pancreatitis, lower hemoglobin levels and higher blood urea nitrogen levels are independent risk factors for IPN in female HTG-AP patients with childbearing age.

Objective:Systematically review the release status and characteristics of policies related to cross-regional medical insurance settlement policies in China,providing reference for promoting the convenience of medical insurance settlement services and improving management efficiency.Methods:Using content analysis,a two-dimensional framework of"policy objectives-policy tools"was constructed.A total of 127 policy documents were coded and analyzed.Results:Demand-based tools were applied most frequently(43.6%),followed by environmental and supply-based tools.Policy objectives mainly focused on improving service convenience,supported by expanding coverage and ensuring regulatory security.Conclusions:China's cross-regional medical insurance settlement policies have improved service accessibility and strengthened institutional supervision while gradually expanding coverage.However,deficiencies remain in assessment refinement and emergency mechanisms.Greater interdepartmental coordination is needed to enhance regulatory linkage and ensure the safe operation of medical insurance funds.