Objective: To evaluate the classroom environmental management and CO 2 volume concentration in primary and secondary schools from Liaoning, Tianjin, and Shanghai, thereby providing a scientific basis for developing targeted strategies to improve classroom air quality. Methods: From December 16 to 26, 2024, by using stratified random cluster sampling method, the questionnaire survey was conducted in 72 primary and secondary schools (24 each of primary, junior high, and regular high schools) across Liaoning, Tianjin and Shanghai. Information on heating, ventilation and other classroom environmental management was collected. Additionally, 108 classrooms were selected for on site microclimate measurements, including temperature, humidity, wind speed and CO 2 volume concentration. Univariate analysis and multiple linear regression models were employed to explore related factors of classroom CO 2 volume concentration. Results: Among the three provinces/municipalities, 20.8% of schools regularly monitored the microclimate. The overall compliance rate for classroom CO 2 volume concentration was 17.6%. Multiple linear regression analysis showed that CO 2 volume concentration in regular and junior high school classrooms were higher than in primary school classrooms ( β=0.067, 0.046, 95%CI =0.036-0.099, 0.013-0.080); classrooms ventilated regularly in the morning and afternoon had higher CO 2 volume concentration than those ventilated during every break between classes ( β=0.043, 95%CI = 0.007- 0.080); both temperature ( β=0.010, 95%CI =0.004-0.016) and humidity ( β=0.003, 95%CI =0.002-0.004) were positively correlated with CO 2 volume concentration (all P <0.05). Conclusions Excessive CO 2 volume concentration in primary and secondary school classrooms is a prominent issue, and ventilation frequency is a key intervenable factor for controlling CO 2 levels. It is recommended to promote ventilation during every break between classes as a core management measure and to emphasize air quality supervision in regular high school classrooms.

This article presented the diagnosis and treatment of three patients from the first imported familial clustering of clonorchiasis in Shanghai Municipality, and evaluated the value of different stool examination methods in non-endemic areas of clonorchiasis. In February 2026, the first case of clonorchiasis in this family was confirmed, and subsequent epidemiological surveys revealed that four family members all had a history of traveling to Guangdong Province and consuming raw freshwater fish. Stool samples were collected from all four individuals and detected for Clonorchis sinensis eggs using both machine smear method and the modified Kato-Katz thick smear method. C. sinensis infection was detected among three individuals using the Kato-Katz method, with severe [20 448 eggs per gram (EPG)], moderate (2 376 EPG), and mild infections (960 EPG) identified, respectively, and no C. sinensis eggs were identified in the remaining one stool sample. In contrast, only one infection was detected with the machine smear method, resulting in a underdiagnosis rate of 66.67% (2/3). All three confirmed cases were cured following standardized therapy. This article indicates that imported familial clustering clonorchiasis cases are highly occult in non-endemic areas, and the machine smear method has a high risk of underdiagnosis during initial screening. A two-tier diagnostic model combining “machine smear method for initial screening + Kato-Katz method for confirmation” is recommended.

BACKGROUND:Exercise as a form of active rehabilitation can improve the dysfunction caused by peripheral nerve injury,and different exercise modalities target different lesion sites and recovery mechanisms. OBJECTIVE:To comprehensively analyze the application and mechanisms of different exercise modalities in functional recovery from peripheral nerve injury. METHODS:A computerized search was conducted in PubMed and CNKI databases for relevant literature published before January 2024.The search terms used were"peripheral nerve injury,spinal cord,exercise,cerebral cortex,muscle atrophy,mirror therapy,blood flow restriction training"in both English and Chinese.Finally,77 articles were included for review. RESULTS AND CONCLUSION:Peripheral nerve injury can cause systemic pathological changes such as skeletal muscle atrophy,corresponding spinal cord segmental lesions,and sensorimotor cortex remodeling.Aerobic exercise can improve dysfunction by enhancing the immune response,promoting glial cell polarization,and promoting the release of nerve growth factor.Blood flow restriction exercise can regulate the secretion of muscle growth factor,promote muscle growth and enhance muscle strength.Mirror movement has a good effect in activating the cerebral cortex and reducing cortical remodeling.Different exercise modalities have potential benefits in functional recovery after peripheral nerve injury;however,there are still some problems and challenges,such as the choice of exercise modalities,the control of exercise intensity and frequency,and the detailed analysis of mechanisms.

Biometric recognition technology has developed rapidly and highly integrated with clinical diagnostics,phenotypic genomics,genomics,and big data analytics,facilitating not only precise personal identification but also demonstrating significant potential in health maintenance,particularly for military personnel.Global research has increasingly focused on uncovering the complex associations between biometric traits and key health determinants,such as disease susceptibility,psychological states,and physiological functions,to further harness biometrics in proactive health management.This paper provided a comprehensive overview of the latest progress and emerging applications of biometric technology in healthcare and military medicine,aiming to offer a scientific reference supporting the strategic development of biometrics research,its application promotion,and population-wide health management enhancement.

Objective: To create a prediction model for stroke risk among middle-aged and elderly populations, so as to provide a basis for early identification of high-risk population for stroke. Methods: From October to December 2023, residents aged ≥45 years in Chongchuan District, Nantong City, Jiangsu Province were selected using a multi-stage stratified random sampling method. The demographic information, life behavior, and chronic disease data were collected through a questionnaire survey. The standardized prevalence of stroke was calculated using data from the seventh National Population Census. The subjects were randomly divided into the training set and the internal validation set according to the ratio of 8∶2. The basic demographic information, life behavior, and chronic diseases of residents aged ≥45 years in Rugao City were collected from July to August 2023 as the external validation set. Predictive factors were selected using multivariable logistic regression model, and a nomogram for stroke among residents aged ≥45 years was established. The prediction effect was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curve, and Hosmer-Lemeshow goodness of fit test. Results: A total of 6 290 residents aged ≥45 years were included, including 2 975 males (47.30%) and 3 315 females (52.70%). The average age was (61.90±10.20) years. The prevalence of stroke was 3.80%, and the standardized prevalence was 3.36%. The multivariable logistic regression showed that age, smoking, hypertension, and hyperlipidemia were predictors of stroke risk among residents aged ≥45 years, and the prediction model was ln[p/(1-p)]=-4.619+0.046×age+0.383×smoking+0.887×hypertension+0.678×hyperlipidemia. The AUC values of the training set, internal validation set, and external validation set were 0.748, 0.755, and 0.738, respectively. The consistency indexes were 0.748, 0.755, and 0.738, respectively. The Hosmer-Lemeshow goodness of fit test showed a good fitting effect (P>0.05). Conclusion The prediction model based on age, smoking, hypertension, and hyperlipidemia has good discrimination and calibration, and can be used to predict the risk of stroke among middle-aged and elderly populations aged ≥45 years.

Objective: To systematically evaluate the prevalence and influencing factors of screen exposure among preschool children in China, so as to provide evidence for formulating scientific intervention strategies. Methods: Retrieve relevant studies on screen exposure among preschool children from PubMed, Web of Science, Embase, Cochrane Library, China Biomedical Literature Database, CNKI, VIP, and Wanfang databases from the time of estaldishment to June 29, 2025. Meta analysis was performed using Stata 16.0 software. Results: A total of 43 studies were included. Meta analysis showed that the prevalence of screen exposure among preschool children in China was 46.0% (95% CI = 38.9 %-53.1%, P <0.01). Girls, non only child, father s age<35 years, both parents having an educational level of high school or below, being cared for by grandparents, rural residence, parents having no exercise habit, parental support for the use of screen devices, and parental screen time>1 h/d were influencing factors for screen exposure among preschool children [ OR (95% CI ) were 0.85(0.78-0.92), 1.09(1.04-1.15), 1.45(1.22-1.71), 1.38(1.24- 1.54 ), 1.78(1.32-2.40), 1.39(1.16-1.65), 1.38(1.13-1.69), 1.67(1.40-1.98), 1.70(1.38-2.10), 1.59(1.04-2.43), all P <0.05]. Conclusion The prevalence of screen exposure among preschool children in China is relatively high, and relevant child health promotion strategies should be formulated to reduce its occurrence.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Reactive oxygen species (ROS) are major contributors to radiation therapy-induced side effects in cancer patients. A fusion antioxidant enzyme comprising glutathione S-transferase (GST), superoxide dismutase 1 (SOD1), and a transmembrane peptide has been shown to effectively mitigate ROS-induced damage. To enhance its targeting capability, the fusion protein was further modified by incorporating a matrix metalloproteinase-2/9 substrate peptide (X) and the transmembrane peptide R9, yielding the antioxidant enzyme GST-SOD1-X-R9 (GS1XR). This modification reduced its transmembrane ability in tumor cells, thereby selectively protecting normal cells from oxidative stress. However, the use of non-human GST poses potential immunogenicity risks. In this study, we employed seamless cloning technology to construct an expression vector containing the human GST gene to replace the non-human GST gene, and then expressed and purified novel fusion antioxidant enzymes GS1R and GS1XR. The protective effects of newly constructed GS1R and GS1XR against hydrogen peroxide (H₂O₂)-induced oxidative damage in L-02 cells were then evaluated using GS1 as a control. Enzymatic activity assays revealed that the specific activity of GST in GS1XR remained unchanged compared to the unmodified protein, while SOD activity was enhanced. Exposure to 200 μmol/L H₂O₂ transiently activated the nuclear factor-erythroid 2-related factor 2 (Nrf2) pathway; however, this activation diminished after 24 h, reducing cell viability to 48.4%. Both GS1R and GS1XR effectively scavenged intracellular ROS, directly counteracting oxidative stress and promoting Nrf2 nuclear translocation, thereby activating antioxidant pathways and restoring cell viability to normal levels. The two enzymes showed comparable efficacy. In contrast, GS1, lacking transmembrane capability, was restricted to scavenging extracellular ROS and provided only limited protection. In conclusion, both novel fusion antioxidant enzymes demonstrated significant potential in safeguarding normal cells from ROS-mediated oxidative damage. The findings provide a foundation for further investigation in related field.
Humans ; Oxidative Stress/drug effects* ; Hydrogen Peroxide ; Antioxidants/metabolism* ; Glutathione Transferase/metabolism* ; Recombinant Fusion Proteins/pharmacology* ; Superoxide Dismutase-1 ; Reactive Oxygen Species/metabolism* ; Superoxide Dismutase/biosynthesis*

ObjectiveTo analyze the evolutionary characteristics and genetic variations of the HA (hemagglutinin) and NA (neuraminidase) genes of influenza A(H1N1) viruses in Shanghai during 2024, to investigate their transmission patterns, and to evaluate their potential impact on vaccine effectiveness. MethodsFrom January to October 2024, throat swab specimens were collected from influenza like illness (ILI) patients at 4 hospitals in Shanghai. Real-time fluorescence ploymerase chain reaction (RT-PCR) was used for virus detection and isolation of H1N1 influenza viruses. Forty influenza A(H1N1) virus strains were sequenced using Illumina NovaSeq 6000 platform, followed by phylogenetic analyses, genetic distance analysis, and amino acid variation analyses of HA and NA genes. ResultsPhylogenetic tree of the HA and NA genes revealed that the 40 influenza A(H1N1) virus strains circulating in Shanghai in 2024 exhibited no significant geographic clustering, with a broad origin of strains and complex transmission chains. Genetic distance analyses demonstrated that the average intra-group genetic distances of HA and NA genes among the Shanghai strains were 0.005 1±0.000 6 and 0.004 6±0.000 6, respectively, which were comparable to or higher than those observed in global surveillance strains. Both HA and NA genes displayed frequent mutations. Compared to the 2023‒2024 and 2024‒2025 Northern Hemisphere A(H1N1) vaccine strains (WHO-recommended), the HA proteins of 40 Shanghai strains exhibited amino acid substitutions at positions 120, 137, 142, 169, 216, 223, 260, 277, 356 and 451, with critical mutations at positions 137 and 142 located within the Ca2 antigenic determinant. Furthermore, mutations in the NA protein were observed at positions 13, 50, 200, 257, 264, 339 and 382. ConclusionThe genetic background of the 2024 Shanghai influenza A(H1N1) virus strains is complex and diverse, and antigenic variation may affect vaccine effectiveness. Therefore, it is recommended to enhance genomic surveillance of influenza viruses, evaluate vaccine suitability, and implement more targeted prevention and control strategies against imported influenza viruses.