Objective: To examine the mediating effect of frailty on social isolation and cognitive function among the elderly. Methods: Demographic information, smoking, alcohol consumption and cognitive function of the elderly at ages of 60 years and older were collected from the China Health and Retirement Longitudinal Study 2020. Social isolation and frailty were evaluated using social isolation index and frailty index, respectively. The mediating effect of frailty on social isolation and cognitive function was analyzed using the Process program, and the significance of the mediating role was tested using the Bootstrap test. Results: A total of 2 822 individuals were enrolled, including 1 483 males (52.55%) and 1 339 females (47.45%). There were 2 497 (88.48%) and 325 (11.52%) individuals at ages of 60-<75 years and ≥75 years, respectively. The median cognitive function score was 14 (interquartile range, 16) points. There were 432 cases with social isolation (15.31%), with a median social isolation index of 10 (interquartile range, 5) points. The median frailty index was 0.11 (interquartile range, 0.15). There were 1 111 individuals without frailty, accounting for 39.37%; 1 214 individuals with pre-frailty, accounting for 43.02%; and 497 individuals with frailty, accounting for 17.61%. Mediating effect analysis showed that social isolation affected cognitive function directly and negatively with the effect value of -0.773 (95%CI: -0.899 to -0.647), and also affected cognitive function by frailty indirectly and negatively with the effect value of -0.147 (95%CI: -0.188 to -0.110), with the mediating effect contributed 15.98% of the total effect. Conclusion Frailty can directly or indirectly affect cognitive function among elderly through social isolation.

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

The aim of this study is to establish a simple and accurate method for vaccine immune e-valuation of porcine pseudorabies virus.In this research,PRV-gD recombinant protein was ex-pressed from mammalian cell HEK-293F as coating antigen,and then the reaction conditions of gD-iELISA were optimized according to checkerboard titration method.The gD-iELISA was used to detect the antibody levels of 211 clinical pig serum samples and the consistency with the neu-tralizing antibody levels wasanalyzed.The results showed that the antigen coating concentration was 0.90 mg/L;the serum to be detected was diluted 1∶100 and incubated at 37 ℃ for 30 min;goat anti-pig IgG-HRP antibody was diluted 1∶55 000 and incubated at 37 ℃ for 30 min;TMB sub-strate was developed at 37 ℃ for 20 min.The method could detect 1∶6 400 diluted PRV positive serum.The results of CSFV,PRRSV,PCV-2,PEDV and FMDV positive sera were all negative by gD-iELISA,and there was no cross-reaction between the method and the above positive sera.The coincidence rate of gD-iELISA and commercial kits was 95.26％,and the intra-and inter-batch co-efficients of variation were both less than 10％.Correlation analysis showed that the correlation coefficient(r)between gD antibody level and neutralizing antibody level was significantly greater than that of gB antibody level,and the gD antibody level had a good linear relationship with the neutralizing antibody level.The results indicated that gD-iELISA was more suitable for vaccine im-mune evaluation of PRV than gB-iELISA.Therefore,the method will have a good prospect of ap-plication in the immunization control of the PRV.

Objective:To propose the application of recognizing bone species by touching blindly (ARBTB) and verify its application effect in human anatomy experimental courses.Methods:The study included experiment 1 and experiment 2, and the research objects were 60 students majoring in clinical medicine in Batch 2019 and 60 students majoring in preventive medicine in Batch 2018, respectively. The research objects in each experiment were randomized into mainstream teaching method group and ARBTB group, with 30 students in each group. In experiment 1, after students studying for the same hours, both of two groups carried out the same test, and then the average scores of the two groups were compared. In experiment 2, the average time spent by the two groups of students in osteology learning was compared.Results:In experiment 1, ARBTB group's average score of the test was significantly higher than that of the mainstream teaching group ( P<0.001). In experiment 2, the ARBTB group took much less time in osteology learning than the mainstream teaching group ( P<0.001). Conclusion:Compared with the mainstream teaching method, ARBTB is more effective in osteology learning, which is worth popularizing.

Objective To assess the predictive value of FBG concentration in-hospital outcome in the old patients with AMI.Methods 256 old patients (≥60 years old) with AMI precluding that with history of diabetes were divided into two groups according to serum FBG level:group A,n = 136,FBG ≥7.0mmol/L;group B,n = 120,FBG < 7.0mmol/L FBG concentrations after 7 days,mortality and total cardiac affairs in-hospital were recorded. Results:Among the two group,there were no significance in age,history of hypertension,hyperlipdemia. Compared with group B,the patients with high FBG levels in 7th day were more than group A, about 21% of group A(P< 0.05). Numbers of disease vessels were more than group A(P < 0.05). Cardiac shock,in-hospital mortality and total cordial affairs were significanfly higher in group A(12%vs0% in cardiac shock, 12%vs4% in mortality ,61%vs34% in MACE)(P< 0.05). Conclusion A part of the old patient with high FBG concentrations and AMI have impaired glucose metabolism, admission glucose levels are predictive for in hospital mortality and total cardial affairs.