Sodium ; Wastewater ; Potassium ; Diet ; Blood Pressure ; China ; Sodium, Dietary ; Sodium Chloride, Dietary

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

Protein as the allergens could lead to allergy. In addition, a widespread class of allergens were known as glycans of N-glycoprotein. N-glycoprotein contained oligosaccharide linked by covalent bonds with protein. Recently,studies implicated that allergy was associated with glycans of heterologous N-glycoprotein found in food, inhalants, insect toxins, etc. The N-glycan structure of N-glycoprotein allergen has exerted an influence on the binding between allergens and IgE, while the recognition and presentation of allergens by antigen-presenting cells (APCs) were also affected. Some researches showed thatN-glycan structure of allergen was remodeled by N-glycosidase, such as cFase I, gpcXylase, as binding of allergen and IgE partly decreased. Thus, allergic problems caused by N-glycoproteins could potentially be solved by modifying or altering the structure ofN-glycoprotein allergens, addressing the root of the issue. Mechanism of N-glycans associated allergy could also be elaborated through glycosylation enzymes, alterations of host glycosylation. This article hopes to provide a separate insight for glycoimmunology perspective, and an alternative strategy for clinical prevention or therapy of allergic diseases.

Objective To investigate the effects of Astragalus polysaccharides(HPS)on farnitol X receptor(FXR)-small heterodimer chaperone receptor(SHP)signaling pathway and key proteins of glucose and lipid metabolism in diabetic rats.Methods Twelve male Wistar rats were randomly selected as blank group,and the remaining 60 rats were fed with a one-time intrabitoneal injection of streptozotocin(STZ,50 mg·kg-1)combined with a high-sugar and high-fat diet to replicate the diabetic rat model.The model rats were randomly divided into model group,positive control group(400 mg·kg-1·d-1 Bifidobacterium quadruple viable bacterial tablet suspension),experimental-H,-M,-L groups(200,100 and 50 mg·kg-1·d-1 HPS suspension),respectively.Blank group and model group were given equal volume of pure water once a day for 8 weeks.Blood glucose(Glu)was measured before and after gavage.Real-time fluorescent polymerase chain reaction(RT-PCR),Western blot were used to detect the mRNA and protein expression level of FXR,SHP,antiperoxisomal proliferator-activated receptor α(PPARα),antiphosphoenolpyruvate carboxylkinase(PEPCK),sterol regulatory receptor binding protein-1c(SREBP-1c),glucose 6 phosphatase(G6Pase).Results Glu levels in normal group,model group,positive control group and experimental-H group after treatment were(7.66±0.61),(29.25±1.64),(23.31±3.02),(19.31±5.13)mmol·L-1,respectively;the relative expression levels of FXR mRNA in liver tissues were 1.00±0.04,0.44±0.03,0.61±0.06,0.87±0.03,respectively;the relative expression levels of SHP mRNA were 1.00±0.04,0.40±0.01,0.67±0.01,0.67±0.02;the relative expression levels of G6Pase mRNA in liver tissues were 1.00±0.06,3.00±0.08,1.87±0.03,1.44±0.05,respectively;the relative expression levels of PEPCK mRNA in liver tissues were 1.00±0.04,1.88±0.03,1.31±0.02,1.23±0.04,respectively;the relative expression levels of SREBP-1c mRNA in liver tissues were 1.00±0.04,1.90±0.01,1.26±0.03,1.06±0.04;the relative expression levels of PPARα mRNA in liver tissues were 1.00±0.02,0.16±0.01,0.45±0.01,0.96±0.03,respectively.Compared with blank group,positive control group and experimental-H group,there were statistically significant differences in the above indexes between model group and blank group(all P＜0.01).The protein expression trend of FXR,SHP,G6Pase,PEPCK,SREBP-1c,PPARα was consistent with mRNA expression.Conclusion HPS may regulate FXR-SHP signaling pathway in liver tissue,inhibit the expression of key proteins of glucose and lipid metabolism,promote lipid oxidation,improve Glu and protect liver tissue in diabetic rats.

Immunotherapy had completely changed the treatment for patients with advanced non-small cell lung cancer.However,due to its low response rate as a monotherapy,many patients had not been able to benefit from the treatment.The combination of immunotherapy with anti-angiogenic drugs and chemotherapy might have helped to address this issue,and the regimen of atezolizumab with bevacizumab,carboplatin,and paclitaxel(ABCP)had been approved as a first-line treatment for advanced metastatic non-small cell lung cancer,holding great potential for application.This review had summarized the antitumor mechanisms of the ABCP regimen,had concluded the current status of its clinical application for different subgroups and treatment sequences,the safety and cost-effectiveness of the regimen,as well as the possibilities for alternative drug choices within the ABCP regimen and the development of new drugs,providing a reference for the personalized application of the ABCP regimen in patients with non-small cell lung cancer.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.

Objective:Operational efficiency and influencing factors of China's basic medical insurance system from 2020 to 2021 is conducted to provide reference for improving the operational efficiency and optimizing the input-output relationship.Methods:The super-efficiency SBM model based on unexpected output and the Malmquist index are used to measure the static and dynamic efficiency of resident medical insurance in 31 provinces in China,and Tobit regression analysis is employed to analyze the influencing factors.Results:The overall operational efficiency of resident medical insurance still needs improvement.The operational efficiency of resident medical insurance in the central and western regions is lower than that in the eastern region,and the gap is significant.Different levels and regions have differentiated main constraints on the operational efficiency of resident medical insurance.In terms of dynamic efficiency,the total factor productivity of resident medical insurance operation shows an increasing trend,mainly due to technological progress.In terms of influencing factors,the degree of aging,the level of medical expenses and the level of medical insurance supervision have a significant impact on the operational efficiency.Suggestions:Efforts should be made to bridge regional disparities,promote the equitable development of medical insurance,reasonably control the level of medical expenses,strengthen the supervision of medical insurance funds,and implement active aging policies.

The incidence of intrahepatic cholangiocarcinoma (ICC) continues to rise, and there are no effective drugs to treat it. The immune microenvironment plays an important role in the development of ICC and is currently a research hotspot. Icaritin (ICA) is an innovative traditional Chinese medicine for the treatment of advanced hepatocellular carcinoma. It is considered to have potential immunoregulatory and anti-tumor effects, which is potentially consistent with the understanding of "Fuzheng" in the treatment of tumor in traditional Chinese medicine. However, whether ICA can be used to treat ICC has not been reported. Therefore, in this study, sgp19/kRas, an in situ ICC mouse model with intact immune system, was selected to evaluate the efficacy of ICA in the treatment of ICC in vivo for the first time, and the effects of ICA on the tumor immune microenvironment of ICC mice were analyzed by flow cytometry. This experiment was approved by the Experimental Animal Ethics Committee of Capital Medical University (approval number: AEEI-2023-138). In this study, sgp19/kRas ICC mouse model was treated with oral gavage of 100 mg·kg^-1 ICA. We found that ICA significantly inhibited tumor growth and tumor cell proliferation in the sgp19/kRas ICC mouse model after 3 weeks of treatment. Flow cytometry analysis indicated that ICA treatment markedly reduced the proportion of M2 macrophages and increased the number of CD3⁺CD4⁺ T cells. In vitro experiments demonstrated that ICA promoted macrophage polarization towards the M1 phenotype while inhibiting polarization towards the M2 phenotype. Furthermore, transcriptomic analysis suggested that ICA enhanced Toll-like receptor 9 (TLR9) expression, influencing macrophage nitric oxide metabolism synthesis pathways and receptor-related activities, thereby regulating macrophage polarization. In summary, this study demonstrates that ICA treatment significantly delays tumor progression in sgp19/kRas ICC mouse models. Mechanistically, ICA may achieve its anti-ICC effects by upregulating TLR9 receptor expression levels, promoting macrophage polarization towards the M1 phenotype, and altering the tumor immune microenvironment.

Objective:To investigate the interactive effect of mismatch repair (MMR) protein status and adverse clinicopathological features on prognosis of stage Ⅰ-Ⅲ colon cancer.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 650 patients with colon cancer of stage Ⅰ-Ⅲ who were admitted to 7 hospitals in China from January 2016 to December 2017 were collected. There were 963 males and 687 females, aged 62(53,71)years. Patients were classified as 230 cases of MMR deficiency (dMMR) and 1 420 cases of MMR proficiency (pMMR) based on their MMR protein status. Observation indicators: (1) comparison of clinicopathological characteristics between patients of different MMR protein status; (2) analysis of factors affecting the survival outcomes of patients of dMMR; (3) analysis of factors affecting the survival outcomes of patients of pMMR; (4) interaction analysis of MMR and adverse clinicopathological features on survival outcomes. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the Mann-Whitney U test. The random forest interpolation method was used for missing values in data interpolation. Univariate analysis was conducted using the COX proportional risk regression model, and multivariate analysis was conducted using the COX stepwise regression with forward method. The coefficient of multiplication interaction effect was obtained using the interaction term coefficient of COX proportional risk regression model. Evaluation of additive interaction effects was conducted using the relative excess risk due to interaction ( RERI). Results:(1) Comparison of clinicopathological characteristics between patients of different MMR protein status. There were significant differences in age, T staging, the number of lymph node harvest, the number of lymph node harvest <12, high grade tumor between patients of dMMR and pMMR ( P<0.05). (2) Analysis of factors affecting the survival outcomes of patients of dMMR. Results of multivariate analysis showed that T staging, N staging, the number of lymph node harvest <12 were independent factors affecting the disease-free survival (DFS) of colon cancer patients of dMMR ( hazard ratio=3.548, 2.589, 6.702, 95% confidence interval as 1.460-8.620, 1.064-6.301, 1.886-23.813, P<0.05). Age and N staging were independent factors affecting the overall survival (OS) of colon cancer patients of dMMR ( hazard ratio=1.073, 10.684, 95% confidence interval as 1.021-1.126, 2.311-49.404, P<0.05). (3) Analysis of factors affecting the survival outcomes of patients of pMMR. Results of multivariate analysis showed that age, T staging, N staging, vascular tumor thrombus were independent factors affecting the DFS of colon cancer patients of pMMR ( hazard ratio=1.018, 2.214, 2.598, 1.549, 95% confidence interval as 1.006-1.030, 1.618-3.030, 1.921-3.513, 1.118-2.147, P<0.05). Age, T staging, N staging, high grade tumor were independent factors affecting the OS of colon cancer patients of pMMR ( hazard ratio=1.036, 2.080, 2.591, 1.615, 95% confidence interval as 1.020-1.052, 1.407-3.075, 1.791-3.748, 1.114-2.341, P<0.05). (4) Interaction analysis of MMR and adverse clinicopathological features on survival outcomes. Results of interaction analysis showed that the multiplication interaction effect between the number of lymph node harvest <12 and MMR protein status was significant on DFS of colon cancer patients ( hazard ratio=3.923, 95% confidence interval as 1.057-14.555, P<0.05). The additive interaction effects between age and MMR protein status, between high grade tumor and MMR protein status were significant on OS of colon cancer patients ( RERI=-0.033, -1.304, 95% confidence interval as -0.049 to -0.018, -2.462 to -0.146). Conclusions:There is an interaction between the MMR protein status and the adverse clinicopathological features (the number of lymph node harvest <12, high grade tumor) on prognosis of colon cancer patients of stage Ⅰ-Ⅲ. In patients of dMMR, the number of lymph node harvest <12 has a stronger predictive effect on poor prognosis. In patients of pMMR, the high grade tumor has a stronger predictive effect on poor prognosis.

Objective To study the ability of radial basis function neural network(RBFNN)with different implementations for electrical impedance tomography(EIT)under real brain shapes,to evaluate the advantages and disadvantages of different approaches,and to provide a reference for the selection of practical imaging methods.Methods COMSOL Multiphysics was used to establish a multilayer 2D model with real structure based on brain CT and an EIT simulation dataset.The effects of the exact RBFNN,the orthogonal least squares-based RBFNN(OLS RBFNN)and the K-Means-based BRFNN(K-Means RBFNN)on the image reconstruction result were explored with the dataset constructed.The root mean square error(RMSE)and image correlation coefficient(ICC)were adopted to evaluate the imaging results.Results EIT could be completed with all the three RBFNNs without noise,and the exact RBFNN had the best results with average ICC and RMSE of 0.784 and 0.467,respectively,in the test set.The OLS RBFNN had the best imaging results at a hidden node of 50,with an average ICC and RMSE of 0.788 and 0.462,respectively.The K-Means RBFNN achieved the best imaging results at noise levels of 30,40,50,60,70 and 80 dB with stable ICC and RMSE and high robustness.Conclusion All the three RBFNNs can be used for brain EIT image reconstruction with their own advantages and disadvantages,and the RBFNN has to be selected for EIT reconstruc-tion based on considerations on actual conditions.[Chinese Medical Equipment Journal,2024,45(10):1-6]