Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective: To investigate the association between the physical fitness index (PFI) and symptoms of depressive, anxiety and stress symptoms among college students, providing a reference for mental health interventions. Methods: From June to September 2025, combined convenience and cluster random sampling approach was used to administer questionnaire surveys and perform physical fitness tests on 2 712 college students from Zhejiang Chinese Medical University. The Depression Anxiety Stress Scales-21 Items (DASS-21) was used to assess mental health status. Chi square test and multivariate Logistic regression analysis were used to determine the associations between the PFI and the PFI component indicators with depressive, anxiety and stress symptoms. Results: The prevalence of depressive, anxiety and stress among college students were 24.26%, 33.22% and 13.68%, respectively. Statistically significant differences in the prevalence of these symptoms were detected across groups differing in sleep quality, physical activity, weekly breakfast frequency, and history of low back or neck pain ( χ 2=9.33-151.83, all P <0.05). After adjusting for confounding factors, Logistic regression revealed that the moderate and high PFI groups had significantly reduced risks of depressive and anxiety compared to the low PFI group ( OR =0.73, 0.63; 0.61, 0.72, all P <0.05). Poor speed (50 m run) and lower body strength (standing long jump) emerged as common risk factors affecting anxiety and depressive symptoms in both male and female college students (all P <0.05). Increased muscle strength (sit up for 1 min) in female students reduced the risk of depressive ( OR =0.81), anxiety ( OR =0.85), and stress symptoms ( OR =0.79) (all P <0.05). Enhanced lung capacity in male students decreased the risk of depressive ( OR =0.84) and anxiety symptoms ( OR =0.85) (both P <0.05). Conclusions The PFI is negatively correlated with depressive and anxiety symptoms among college students with notable gender differences. Insufficient speed and lower body explosive power represent common risk factors for mental health among male and female college students.

Based on the analysis of the existing problems and implementation dilemmas in family doctor contracting and first-return-visits faced by primary medical institutions in China, the authors propose countermeasures to provide reference for managers of primary health care institutions.

Objective: To understand the prevalence of Lying Flat behaviors and its association with depressive symptoms among Chinese college students, so as to provide a scientific basis for promoting the physical and mental health development of adolescents. Methods: From July to October 2023, three universities were selected through convenient sampling from Jiangxi Province, Liaoning Province and Beijing City, respectively. Selfdesigned questionnaire links were distributed on campus to collect basic information and Lying Flat behaviors among college students, and the Patient Health Questionnaire-9 (PHQ-9) was utilized to screen for students with depressive symptoms. Finally, a total of 4 225 valid questionnaires were obtained. Chisquare was used to compare of report rates of Lying Flat behaviors across different demographic characteristics. Ordered Logistic regression analysis was used to explore the association between Lying Flat behaviors and depressive symptoms, with Z test used to assess variations in the strength of associations. Results: The reporting rates of academic, life, and social Lying Flat were 32.7%, 17.8% and 17.5%, respectively. And 6.7% of the participants were found of all three Lying Flat behaviors simultaneously.Among college students with three Lying Flat behaviors, the constituent ratios of no, mild, moderate and above depressive symptoms were 9.9%, 30.5% and 59.6%, respectively. Additionally, college students who had three Lying Flat behaviors were more likely to show mild, moderate and above depressive symptoms [OR(95%CI)=2.49(1.60-3.87), 7.69(5.01-11.79), P<0.01]. Conclusions Academic Lying Flat behavior is most prevalent among college students. Academic, life and social Lying Flat behaviors are all significantly positively correlated with depressive symptoms. Attention should be paid to the Lying Flat behaviors and college students psychological health conditions to promote their physical and mental health development.

Objective To investigate the clinical characteristics of carbapenem-resistant Pseudomonas aeruginosa (CRPA) infection in children and the risk factors for such infection. Methods A retrospective analysis was conducted among 60 children with CRPA infection (CRPA group) who were hospitalized in Shenzhen Children's Hospital,China Medical University,from January 2018 to September 2023,and 82 children with carbapenem-sensitive Pseudomonas aeruginosa infection during the same period were randomly selected as the control group. A multivariate logistic regression analysis was used to investigate the risk factors for CRPA infection. Results Among the 60 children with CRPA infection,31 (52％) were admitted to the intensive care unit (ICU),and the lower respiratory tract was the main detection site in 32 children (53％). The univariate analysis showed that sex,history of invasive treatment within 1 year,antibiotic use before admission,presence of underlying condition,ICU admission,invasive procedure after admission,antibiotic use for>14 days,and the type of antibiotics used of ≥3 were associated with CRPA infection (P<0.05). The multivariate logistic regression analysis showed that the history of invasive treatment within 1 year (OR=3.228,P<0.05),antibiotic use before admission (OR=4.052,P<0.05),antibiotic use for>14 days (OR=4.961,P<0.05),and the type of antibiotics used of ≥3 (OR=3.687,P<0.05) were independent risk factors for CRPA infection in children. Conclusions CRPA infection in children may be associated with a history of invasive treatment within the past year,antibiotic use before admission,duration of antibiotic use after admission,and the diversity of antibiotic types used.

Objective To understand the prevalence characteristics of influenza and changes of influenza virus strains,and provide reference for the prevention and control of influenza in the province.Methods Surveillance da-ta about influenza in Hunan Province from 2014 to 2023 were exported from China Influenza Surveillance Informa-tion System.Differences in the percentage of influenza-like illness(ILI)cases(percentage of influenza-like cases[ILI％]in outpatient and emergency department visits)among different years and different populations,as well as the positive rate of influenza virus in ILI specimens were compared.Results From 2014 to 2023,over 2.65 million cases of ILI were reported,with an ILI％of 4.70％.ILI％among different years presented statistically significant differences(P＜0.001).People aged 0-14 years old were the main population with ILI,accounting for 82.90％.The positive rate of influenza virus in ILI specimens was 14.14％,the positive rate of influenza virus among diffe-rent years and age groups were both significantly different(both P＜0.001).The main prevalent influenza strains from 2014 to 2023 included types A(H1N1),A(H3N2),B(Victoria),and B(Yamagata),alternating among di-fferent years.However,type B(Yamagata)strains were not detected from 2020 to 2023.There were basically two influenza prevalence seasons every year,namely winter-spring and summer.Conclusion People＜15 years old are the main population of influenza,and the prevalence peaks are in winter-spring and summer.From 2021 to 2023,the prevalence alternates mainly among 3 types:A(H1N1),A(H3N2),and B(Victoria).

Objective To propose a sperm classification model based on convolutional neural network to enhance the accuracy of sperm morphological classification.Methods A FT-EfficientNet model was constructed using EfficientNetB0 as the base model,which was fine-tuned by data preprocessing enhancement,transfer learning and cosine decay.Classification experi-ments were performed on the sperm public datasets SCIAN-Morpho and HuSHeM,and the datasets were segmented and vali-dated using 5-fold cross-validation.The classification results by the FT-EfficientNet model were compared with those by the cascade ensemble of support vector machines(CE-SVM)model,the adaptive patch-based dictionary learning(APDL)model,fine tuning of visual geometry group(FT-VGG)model,morphological classification of human sperm heads(MH-HSH)model and transfer learning(TL)model.Ablation experiments were performed in the SCIAN-Morpho dataset to verify the effect of different fine-tuning methods on the model.Results The FT-EfficientNet model proposed had the accuracy,precision and F1 score on the SCIAN-Morpho validation set being 64.1％,63.8％and 64.8％,respectively,which were better than CE-SVM,APDL,FT-VGG and MC-HSH models.The recall rate of the model proposed(65.2％)was slightly lower than that of MC-HSH model(68.0％).The accuracy,precision,F1 score and recall rate on the HuSHeM validation set was 95.4％,95.8％,95.4％and 96.0％,respectively,which were slightly lower than those of TL model while better than those of CE-SVM,APDL,FT-VGG and MC-HSH models.Ablation experiments showed the FT-EfficientNet model behaved the best in fine-tuning.Conclusion The sperm classification model based on convolutional neural network facilitates sperm morphology classification with high accuracy and performance.[Chinese Medical Equipment Journal,2024,45(10):7-13]

The synergistic antibacterial strategy of peroxidase mediated chemodynamic therapy(CDT)and photothermal therapy(PTT)has been proven to effectively resist bacteria.However,the antibacterial effect against Pseudomonas aeruginosa is severely limited due to the factors such as short lifespan of reactive oxygen species(ROS)(<200 ns)and limited diffusion distance(about 20?200 nm).In this study,glucopyranose functionalized MoO3-x(P-MoO3-x)nanoenzyme was successfully synthesized using a one-pot hydrothermal method.This nanoenzyme exhibited both peroxidase-like activity and a photothermal effect.The combined antibacterial performance and biological safety of P-MoO3-x was analyzed and verified.By utilizing specific interactions with glucopyranose and lectin,P-MoO3-x nanoenzyme could target the surface of Pseudomonas aeruginosa.This targeted approach effectively shortened the range of hydroxyl radicals,significantly enhancing the antibacterial effect against Pseudomonas aeruginosa.Under photothermal action,P-MoO3-x could reach the optimal reaction effect at 70℃.Even at low concentrations of hydrogen peroxide(50 μmol/L),it released more hydroxyl radicals.In vitro antibacterial analysis experiments demonstrated that the inactivation efficiency of the P-MoO3-x antibacterial system against Pseudomonas aeruginosa(106 CFU/mL)exceeded 99%.Furthermore,in vivo experiments confirmed the significant therapeutic effects of P-MoO3-x in treating methicillin-resistant Staphylococcus aureus(MRSA)infected wounds and promoting wound healing,without producing toxicity to cells.In conclusion,P-MoO3-x exhibited excellent antibacterial ability and good biocompatibility,making it a promising anti-infective nanoenzyme with broad application prospects.