Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective: To explore the balance of peripheral blood T helper 17 cells/regulatory T cell (Th17/Treg) ratio and the polarization ratio of M1 and M2 macrophages in lower extremity arteriosclerosis obliterans (ASO). Methods: A rat model of lower extremity ASO was established, and blood samples from patients with lower extremity ASO before and after surgery were obtained. ELISA was used to detect interleukin 6 (IL-6), IL-10, and IL-17. Real-time RCR and Western blot analyses were used to detect Foxp3, IL-6, IL-10, and IL-17 expression. Moreover, flow cytometry was applied to detect the Th17/Treg ratio and M1/M2 ratio. Results: Compared with the control group, the iliac artery wall of ASO rats showed significant hyperplasia, and the concentrations of cholesterol and triglyceride were significantly increased (P<0.01), indicating the successful establishment of ASO. Moreover, the levels of IL-6 and IL-17 in ASO rats were pronouncedly increased (P<0.05), while the IL-10 level was significantly decreased (P<0.05). In addition to increased IL-6 and IL-17 levels, the mRNA and protein levels of Foxp3 and IL-10 in ASO rats were significantly decreased compared with the control group. The Th17/Treg and M1/M2 ratios in the ASO group were markedly increased (P<0.05). These alternations were also observed in ASO patients. After endovascular surgery (such as percutaneous transluminal angioplasty and arterial stenting), all these changes were significantly improved (P<0.05). Conclusions: The Th17/Treg and M1/M2 ratios were significantly increased in ASO, and surgery can effectively improve the balance of Th17/Treg, and reduce the ratio of M1/M2, and the expression of inflammatory factors.

Gastrointestinal stromal tumor(GIST),with a certain malignant potential,are currently the most common subepithelial tumors of the gastrointestinal tract.Early diagnosis and prediction of malignant potential are very important for the formulation of a treatment plan and determining the prognosis of GIST.Deep learning technology has made significant progress in the diagnosis of digestive tract diseases,and it can also effectively assist physicians in diagnosing GIST and predicting their malignant potential,preoperatively.The application of deep learning technology in the diagnosis of GIST includes CT,gastrointestinal endoscopy and endoscopic ultrasound.This paper aims to review the application of deep learning technology in the diagnosis and prediction of malignant potential of GIST.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

Objective To explore the potential mechanism of carvacrol on inhibiting the formation of biofilm of hy-pervirulent Klebsiella pneumoniae(hvKP).Methods The possible mechanisms of carvacrol were analyzed based on the detection of its effects on the formation and morphology of biofilms,changes in extracellular polysaccharide and capsule polysaccharide content,as well as changes in the expression levels of biofilm-related genes rmpA2,mag A,mrkA,mrkB,and treC of hvKP.Results The minimum inhibitory concentration of carvacrol on hvKP was 512 μg/mL,with an obvious inhibitory effect on the biofilm formation of hvKP,presenting a concentration-depen-dent effect.Under the scanning electron microscope,it was observed that the biofilm structure was loose and the in-tercellular connections were not dense under the intervention of carvacrol.The Congo Red adsorption test and m-hydroxybiphenyl colorimetric method showed that carvacrol could reduce the content of capsule polysaccharides of hvKP,but didn't affect the total extracellular polysaccharide content.Fluorescence quantitative polymerase chain reaction(PCR)showed that under the effect of carvacrol at sub-inhibitory concentration,the synthesis of capsule polysaccharide,expression levels of sugar transport system and pili adhesion-related genes all decreased by more than 50％.Conclusion Carvacrol has a significant inhibitory effect on the formation of biofilm in hvKP,and its mechanism may be related to the decrease of synthesis of capsule polysaccharide as well as expression of biofilm-re-lated genes,such as sugar transport system and pili adhesion.

Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Objective:To compare the effects of left bundle branch area pacing (LBBaP) versus traditional right ventricular pacing (RVP) on left ventricular function in patients after dual-chamber pacemaker implantation.Methods:A retrospective cohort study was conducted on patients who underwent dual-chamber pacemaker implantation from March 2017 to April 2021 in Beijing Anzhen Hospital. The patients were divided into the LBBaP group and RVP group based on the placement of the ventricular lead. Follow-up was conducted until March 2022, comparing baseline and follow-up echocardiographic parameters, pacing parameters, and the incidence and timing of complications between the two groups. The complications included ventricular electrode perforation, dislocation, pericardial effusion, tricuspid valve perforation, etc.Results:A total of 163 patients aged (68.3±13.5) years were included, including 82 (50.3%) men, with 80 patients in the LBBaP group and 83 in the RVP group. Baseline left ventricular end-diastolic diameter ((50.49±4.95) mm vs. (47.43±8.15) mm, P=0.01) and left atrium (LA) ((33.14±5.94) mm vs. (30.18±3.92) mm, P=0.001) in the LBBaP group were significantly higher than those in the RVP group. Follow-up LA diameter ((37.10±6.70) mm vs. (40.10±8.90) mm, P=0.016) showed a statistically significant difference in the LBBaP group compared to the RVP group. There was no statistically significant difference between the two groups in baseline QRS duration( P=0.490). Postoperative QRS duration in the LBBaP group was significantly lower ((110.69±24.01) ms vs. (139.65±29.85) ms, P<0.010). Intraoperative threshold in the LBBaP group was significantly higher ((0.83±0.32) V/0.48 ms vs. (0.71±0.23) V/0.48 ms, P=0.004), while impedance was lower ((754.53±205.59) Ω vs. (905.41±302.75) Ω, P<0.01). Comparing with the RVP group, postoperative ventricular pacing ratio (VP) ((87.39±20.92) % vs. (79.49±25.76) %, P=0.034), threshold ((0.90±0.38) V/0.48 ms vs. (0.69±0.27) V/0.48 ms, P<0.01) in the LBBaP group were higher, and impedance ((507.45±77.37) Ω vs. (620.52±197.29) Ω, P<0.01) in the LBBaP group was lower. Postoperative follow-up period was 5 to 51 months, with a median follow-up time of 17 months. No statistically significant difference in overall complications between the LBBaP and RVP groups was found (13.8% (11/80) vs. 7.2% (6/83), P>0.05). The median time to occurrence of complications after surgery was significantly earlier in the LBBaP group (29.74 (95% CI 27.21-32.26) months vs. 46.17 (95% CI 42.48-49.86) months, P=0.030). Conclusion:LBBaP demonstrates more stable pacing parameters, substantial improvement in clinical left ventricular function, with a relatively higher threshold compared to traditional RVP, and complications occurs relatively early.

Objective To explore the relevant risk factors of H.pylori infection,and provide reference for prevention and treatment of H.pylori in this area,and further provide theoretical basis for the prevention and treatment of gastric cancer.Methods A total of 1200 residents in four districts of Haikou city were investigated by questionnaire and urea 14 C breath test by holistic stratified random sampling to calculate the population infection rate and analyze the risk factors of infection.Results The total infection rate was 32.5％,which was lower than the national H.pylori infection rate.No consumption of fruits and vegetables,no habit of washing hands before meals,and people with gastrointestinal symptoms,are independent risk factors of H.pylori infection.No consumption of pickled products is of great significance to prevent H.pylori infection.Conclusion The prevalence of H.pylori infection in the population of Haikou is lower than the national average,and H.pylori infection is closely related to the poor living habits of residents.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]