Objective: To understand the allocation and use of safety seats for preschool children and explore its related factors, so as to provide a scientific reference for promoting the usage of safety seats. Methods: A stratified random cluster sampling method was used to select 3 143 parents of preschool children aged 3 to 6 from six kindergartens in Shunyi District, Beijing from January 3 to 10, 2022. An online questionnaire survey was conducted to collect and evaluate the equipment and use of child safety seats in different characteristics of preschool children, as well as their scores of health beliefs. Multiple factor Logistic regression analysis was used to investigated the related factors of safety seat configuration and use. Results: The equipping rate and usage rate of safety seats for preschool children were 66.56% and 58.45%, respectively. The proportion of equipped and used safety seats for preschool children in core families (69.52%, 62.23%) were higher than that in large families (64.35%, 55.62%), only child families ( 72.39 %, 64.87%) were higher than non only child families (61.49%, 52.86%), and urban families (71.63%, 63.04%) were higher than rural families (52.31%, 45.51%) ( χ 2=9.23, 13.86; 41.72, 46.44; 101.96 ,76.97,all P <0.05) . As the educational level of parents ( χ 2 trend =154.23,98.76) and annual income of the family ( χ 2 trend =155.78,127.69) rised, the reporting rates of the equipped and used child safety seats in the family also increased(all P <0.05 ). There were statistically significant differences in the scores of different dimensions of health beliefs for the provision ( t =-20.22-18.16) and use ( t =24.32-24.17) of safety seats for preschool children(all P <0.05). After adjusting for child sex, child age, family annual income, parental education level, family type, whether the child was an only child, and place of residence，multivariate Logistic regression analysis showed that preschool children with higher perceived susceptibility score( OR =1.11, 1.08), higher self efficacy score( OR =1.23, 1.33), and higher suggestive factors score( OR =1.08, 1.12) were more likely to have and use safety seats in their families, while preschool children with higher perceived impairments score( OR =0.82, 0.80) were less likely to have and use safety seats in their families (all P <0.05). Conclusions The installation rate of child safety seats needs to be improved, and there is also a certain gap in their use after installation. Parents of preschool children should improve susceptibility and self efficacy to safety seat equipment and use, and perceptual barriers should be reduced.

Neurological disorders such as post-stroke hemiplegia, spinal cord injury, and Parkinson disease represent a major global health burden. Brain-computer interface (BCI), which creates direct communication pathways between the nervous system and external devices, offers a promising strategy for functional restoration. The long-term efficacy of such BCI fundamentally depends on the performance of biomaterials at the neural interface. Ideal materials must concurrently satisfy biocompatibility, electrical conductivity, enduring chemical stability, and mechanical compatibility with brain tissue. This review systematically outlines the application of conductive polymers, inorganic nanomaterials, natural biomaterials, and composites in BCI, with a focus on how advanced designs, such as bionic and encapsulated electrodes, improve signal fidelity and surgical feasibility through structural innovation. It further summarizes key material-modification techniques and analyzes the complex foreign-body response orchestrated by microglia, astrocytes, and peripheral immune cells. Finally, it provides insights into future research directions and clinical translation of BCI-based neurorehabilitation, while highlighting critical challenges including long-term biosafety and the establishment of standardized evaluation frameworks, aiming to bridge the gap between laboratory innovation and effective clinical deployment.

ObjectiveTo analyze the incidence and spatiotemporal distribution of typhus fever in Baoshan City, Yunnan Province from 2005 to 2023, to identify high-risk populations and regions, so as to provide a scientific basis for optimizing the allocation of local prevention and control resources and developing targeted intervention measures. MethodsData of typhus fever cases in Baoshan City from 2005 to 2023 were obtained from the Infectious Disease Information Management System of the Chinese Center for Disease Control and Prevention. Descriptive epidemiological methods were used to analyze the temporal, spatial and demographic distribution of typhus fever cases. Spatial clustering was assessed using spatial dynamic window scan statistics (circular and elliptical windows), flexible spatial scan statistics, and local spatial autocorrelation methods (including local Moran’s I, local Geary’s C, and Getis-Ord G_i*). Retrospective spatiotemporal scan statistics were employed to detect spatiotemporal clusters. ResultsA total of 1 099 typhus fever cases were reported in Baoshan City from 2005 to 2023. The incidence rate peaked at 6.31/ 100 000 in 2007, followed by a decline until reaching its lowest level at 0.21/100 000 in 2015 , and subsequently rebounded during 2016‒2023. The highest proportion of cases was among children under 10 years of age (31.12%), and the top three occupations of cases were farmers, students, and children, accounting for 88.62% of all cases. Cases occurred predominantly between June and September each year. The incidence was relatively high in Jiucheng Town (62.58/100 000), Yaoguan Town (57.15/100 000), and Dianyang Town (46.81/100 000) of Shidian County. Spatial clustering analyses indicated that high-risk areas were mainly located in the southern part of Baoshan City, showing a south-to-north trend. Spatiotemporal scan analyses identified five clusters, with the most likely cluster centered around Yaoguan Town, covering ten towns (subdistricts) during the period 2007‒2010. ConclusionThe incidence of typhus fever in Baoshan City exhibits a clear seasonal and spatial clustering pattern, with peak incidence occurring in summer and autumn. Spatially, cases are primarily distributed in the southern part of Baoshan City, and high-risk clusters exhibit a south-to-north trend. Farmers, students, and children are the high-risk groups.

ObjectiveTo explore the mechanism through which Banxia Baizhu Tianmatang ameliorates cognitive impairment in epileptic rats induced by lithium chloride-pilocarpine by regulating the neuroinflammatory reaction mediated by NOD-like receptor protein 3 （NLRP3） inflammasomes. MethodsSixty male SD rats were randomly allocated into blank， model， carbamazepine （0.125 g·kg^-1·d^-1）， Banxia Baizhu Tianmatang （1.04 g·kg^-1·d^-1）， and carbamazepine （0.125 g·kg^-1·d^-1） + Banxia Baizhu Tianmatang （1.04 g·kg^-1·d^-1） groups （n=12）. After the modeling of epilepsy， rats were administrated with corresponding agents by gavage for 12 weeks. At the 6th and 12th week of the intervention， the rats’ hyper-excited behavior was evaluated by the stylus experiment， and at the 12^th week of intervention， the cognitive function was evaluated by Barnes maze. At the same time， the seizure frequency and severity grade （Racine score） were recorded. The serum and hippocampus tissue samples were collected after anesthesia for the following tests. Nissl staining was used to evaluate the degree of neuronal damage in the hippocampal CA1 area. The content of malondialdehyde （MDA） in the hippocampus was determined by the thiobarbituric acid （TBA） method. Serum levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-18 （IL-18） were quantified by enzyme-linked immunosorbent assay （ELISA）. Immunohistochemical method was adopted to detect the expression of apoptosis-associated speck-like protein containing a card （ASC） in the hippocampus. Western blot was employed to quantitatively analyze the protein levels of NLRP3， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， and brain-derived neurotrophic factor （BDNF） in the hippocampus. ResultsThe model group showed increased stylus scores at the 6th and 12^th week after modeling， a decreased Barnes maze strategy score at the 12^th week， a prolonged incubation period （P<0.05）， elevated serum levels of inflammatory factors （P<0.05）， decreased neurons with scattered arrangement and large gaps in the hippocampus， increased content of MDA in the hippocampus （P<0.05）， an increased positive expression of ASC， and up-regulated protein levels of Caspase-1， NLRP3， and BDNF （P<0.05）. Compared with the model group， the intervention with Banxia Baizhu Tianmatang for 12 weeks was accompanied by a decreased stylus score， epileptic seizures with a decreased score， a decreased number， and shortened duration， an increased Barnes maze strategy score， shortened escape latency （P<0.01）， declined serum levels of inflammatory factors （P<0.05）， regular morphology of hippocampal neurons， reduced MDA content in the hippocampus （P<0.05）， a decreased positive expression of ASC， and down-regulated protein levels of Caspase-1， NLRP3， and BDNF （P<0.05， P<0.01）. In addition， compared with the carbamazepine group， Banxia Baizhu Tianmatang + carbamazepine showed improved performance in controlling the seizure， improved the cognitive behavior score and morphology of hippocampal neurons， alleviated the oxidative stress products， lowered the levels of inflammatory factors， reduced the positive expression of ASC in the hippocampus， and down-regulated the expression of Caspase-1， NLRP3 and BDNF， with no significant differences. ConclusionBanxia Baizhu Tianmatang may reduce neuroinflammation， control epileptic seizures， and ameliorate cognitive impairment by inhibiting the expression of NLRP3 inflammasomes.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Objective To investigate the efficacy of leaflet augmentation technique to repair the recurrent mitral valve (MV) regurgitation after mitral repair in children. Methods A retrospective analysis was conducted on the clinical data of children who underwent redo MV repair for recurrent regurgitation after initial MV repair, using a leaflet augmentation technique combined with a standardized repair strategy at Fuwai Hospital, Chinese Academy of Medical Sciences, from 2018 to 2022. The pathological features of the MV, key intraoperative procedures, and short- to mid-term follow-up outcomes were analyzed. Results A total of 24 patients (12 male, 12 female) were included, with a median age of 37.6 (range, 16.5–120.0) months. The mean interval from the initial surgery was (24.9±17.0) months. All children had severe mitral regurgitation preoperatively. The cardiopulmonary bypass time was (150.1±49.5) min, and the aortic cross-clamp time was (94.0±24.2) min. There were no early postoperative deaths. During a mean follow-up of (20.3±9.1) months, 3 (12.5%) patients developed moderate or severe mitral regurgitation (2 severe, 1 moderate). One (4.2%) patient died during follow-up, and one (4.2%) patient underwent a second MV reoperation. The left ventricular end-diastolic diameter was significantly reduced postoperatively compared to preoperatively [ (43.5±8.6) mm vs. (35.8±7.8)mm, P<0.001]. Conclusion The leaflet augmentation technique combined with a standardized repair strategy can achieve satisfactory short- to mid-term outcomes for the redo mitral repair after previous MV repair. It can be considered a safe and feasible technical option for cases with complex valvular lesions and severe pathological changes.

Aryl hydrocarbon receptor （AhR） plays an important role in the development and progression of liver diseases. This article elaborates on the structure of AhR and its function in liver development and provides a detailed analysis of its molecular mechanisms in diseases such as metabolic associated fatty liver disease， alcoholic liver disease， viral hepatitis， drug-induced liver injury， autoimmune hepatitis， liver cirrhosis， and liver cancer. This article also reviews the research advances in AhR agonists and antagonists and analyzes their potential application prospects in disease treatment. At the same time， it points out that although AhR is a promising therapeutic target， there are still various challenges in its clinical application. It is suggested that future research should focus on developing AhR modulators with high specificity and low toxicity and further explore its mechanism of action in different liver diseases.

Objective To establish a prediction model for the occurrence of non-occupational carbon monoxide poisoning events in Beijing, and to provide scientific basis and theoretical support for the prevention and warning of poisoning events. Methods Based on the monitoring data of non-occupational carbon monoxide poisoning events in Beijing from 2016 to 2024, the seasonal ARIMA model and seasonal index model were established to analyze the data and predict the occurrence of events. Results Between 2016 and 2024, a total of 436 cases of non-occupational carbon monoxide poisoning were reported in Beijing, showing a downward trend. The established SARIMA model and seasonal index model were SARIMA (1,0,0) (1,1,0) 12, Yt = (-0.0339t+5.8863) × St, and the average relative errors were 65.42% and 29.19%, respectively. In terms of months, the SARIMA model had better predictive performance during April and summer (June to August), while the seasonal index model was superior in other months. By combining the two models, the predicted number of events in 2025 was as follows: 3, 2, 2, 3, 1, 5, 2, 7, 1, 1, 1, and 2. Conclusion The seasonal index model has the best prediction effect on the non-occupational carbon monoxide poisoning events in Beijing throughout the year, and the number of summer events predicted by SARIMA model is closer to the actual values. The two models can be combined to predict the trend of non-occupational carbon monoxide poisoning, which provides a scientific basis for the prevention and control of carbon monoxide poisoning in the future.