Objective To analyze the relationship of pathogenesis and early management with prognosis of sylvian fissure contusion of brain caused by traffic accident. Methods A review was done on 36 cases with sylvian fissure contusion of brain caused by traffic accident, in which early improvement of respiration and management of combined injuries were performed according to injury severity and pathogenesis. Standard big bone flap craniotomy was done in 31 cases including bilateral craniotomy in 13. Of nine cases treated conservatively, four cases turned to operation due to aggravation. Results Of all, 18 cases recovery better but death occurred in eight, vegetative state in two, bad disability in two and moderate disability in six. Conclusions Early synthetic treatment, prompt decompression with standard big bone flap, paying attention to sylvian fissure contusion in the midline area, dynamic observation of injury and effective treatment can improve prognosis and reduce mortality rate.

Objective To investigate the expression of thyroid cancer-1 (TC1) and β-catenin in cervical carcinoma and precancerous lesions and their significance. Methods Immunohistochemical methods were used to examine the expression of TC1 and β-catenin in80 cervical squamous cell carcinoma (CSCC) tissues, 40 high-grade squamous intraepithelial lesions (HSIL), 40 low-grade squamous intraepithelial lesions (LSIL), and 30 normal cervical tissues. Results Although TC1 expression in CSCC was significantly higher than that in LSIL (P = 0.002) and normal cervical tissues (P ＜ 0.001), it was similar to that in HSIL (P = 0.576). TC1 expression was positively correlated with poor differentiation (P = 0.005) and advanced FIGO stage (P = 0.004) in CSCC. β-catenin expression in CSCC was significantly higher than that in LSIL (P ＜ 0.001) and normal cervical tissues (P ＜ 0.001), but was similar to that in HSIL (P = 0.907). The abnormal β-catenin expression was also correlated with poor differentiation (P = 0.025) and advanced FIGO stage (P = 0.001) in CSCC. TC1 expression was positively correlated with the abnormal β-catenin expression in CSCC (r = 0.294, P = 0.008) and cervical squamous intraepithelial lesions (r = 0.549, P ＜ 0.001). Conclusion TC1 and β-catenin expression in CSCC and HSIL was significantly higher than that in LSIL and normal cervical tissues. TC1 expression correlated with the abnormal β-catenin expression, and with poor differentiation and advanced FIGO stage of CSCC.

Objective To investigate the feasibility of using contrast-enhanced T1WI radiomics in predicting the pathological grade in rectal adenocarcinoma.Methods The MRI and pathological data of 127 patients with rectal adenocarcinoma were analyzed retrospectively.ITK-SNAP software was used to manually draw region of interest(ROI)in rectal cancer on axial T,WI enhanced images.The radiomics features were extracted by the Pyradiomics software from ROI.The task was divided into two parts:task 1("high & non-high"group)predicted the high-differentiation and moderate/low-differentiation of the tumor;task 2("moderate & low"group)predicted the tumor's moderate-differentiation and low-differentiation in"non-high"group.Maximum relevance and minimum redundancy(mRMR)method was used to screen features.The five methods including least absolute shrinkage and selection operator(LASSO),logistic regression(LR),naive Bayes(NB),random forest(RF),and support vector machine(SVM)were used to build the models,and the efficiency of each model was evaluated and compared.Results In task 1,the area under the curve(AUC)of five methods were 0.86,0.90,0.59,1.00,0.99 in the training cohort and 0.71,0.62,0.53,0.67,0.64 in the testing cohort.In task 2,the AUC of five methods in the training cohort were 0.93,0.85,0.67,0.92,0.89,and in the testing cohort were 0.86,0.80,0.50,0.78,0.71.The models constructed by LASSO in both tasks were the dominant models,the AUC of the fusion model in the testing cohort which combined with age,gender and the dominant Radiomics score(Radscore)was 0.80[95％confidence interval(CI)0.63-0.96]in task 1,and the accuracy,sensitivity and specificity were 78.94％,77.78％,and 79.31％respectively.They were 0.89(95％CI 0.74-1.00),90.00％,95.65％,and 71.43％,respectively in task 2.The calibration curves showed that the fusion models had a good goodness of fit.Conclusion Based on the establishment of two dichotomous models,the radiomics based on the contrast-enhanced T1 WI is feasible in predicting the high,moderate and low differentiation degree of rectal adenocarcinoma.

Objective To explore the feasibility of radiomics features combined with different machine learning methods based on CT scans to predict lymphovascular and perineural invasion in patient with gastric cancer.Methods A total of 142 patients with gas-tric cancer lymphovascular confirmed by operative pathological examination were retrospectively selected.Among all patients,there were 96 positive cases and 46 negative cases.Among 137 patients with perineural invasion,there were 76 positive cases and 61 nega-tive cases.The 3D-Slicer package was used for delineation,and the Pyradiomics package was used to extract radiomics features.All data were randomly divided into training set and test set in an 8∶2 ratio.Intraclass correlation coefficient(ICC),Pearson correla-tion analysis,least absolute shrinkage and selection operator(LASSO)algorithm were used for feature selection.Support vector machine(SVM),K-nearest neighbor(KNN),decision tree(DT),random forest(RF),extreme tree(ET),extreme gradient boosting(XGBoost),and LightGBM were used to compare the models of lymphovascular and perineural invasion,respectively.Receiver operating characteris-tic(ROC)curve and area under the curve(AUC)were used to evaluate the predictive performance of these models.Results The lymphovascular group AUC of SVM,KNN,DT,RF,ET,XGBoost,and LightGBM in the training set were 0.926,0.753,1.000,0.999,1.000,1.000,and 0.917,and the AUC in the test set were 0.894,0.692,0.456,0.678,0.753,0.650,and 0.650,respectively.The perineural invasion group AUC of SVM,KNN,DT,RF,ET,XGBoost,and LightGBM in the training set were 0.864,0.794,1.000,1.000,1.000,1.000,and 0.866,and the AUC in the test set were 0.861,0.706,0.700,0.672,0.731,0.667,and 0.678,respectively.Conclusion Based on venous phase CT radiomics features combined with machine learning methods,it is feasible to predict lymphovascu-lar and perineural invasion of gastric cancer preoperatively.Among the variousmachine learning methods,SVM shows the best predictive performance for lymphovascular and perineural invasion in patient with gastric cancer.

Objective To explore the mechanism of Gualou Xiebai Baijiu Decoction(GXB)in improving atherosclerosis(AS)in mice by regulating the gut microbiota(GM)and its metabolites.Methods Thirty-two male ApoE-/-mice were divided randomly into a Blank group,Model group,atorvastatin(Ato)group,and GXB group(n=8 mice per group).AS was established in all mice,except the Blank group,and the respective treatments were administered by gavage.Aortic plaques were detected by Oil red O staining and pathological changes in aortic tissue were detected by hematoxylin and eosin staining.The GM was analyzed using 16S rRNA gene sequencing technology,and mouse GM metabolites,including trimethylamine oxide(TMAO),short-chain fatty acids(SCFA),and serum levels of triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and nitric oxide(NO)were determined.Results Compared with the Blank group,mice in the Model and Ato groups showed an increase in AS plaque area(P＜0.05).Serum levels of TG,TC,and LDL-C were increased(P＜0.001)while levels of HDL-C and NO were decreased(P＜0.01,P＜0.001)in the Model group compared with the Blank group.The plaque area was decreased(P＜0.05),serum levels of TG,TC,and LDL-C were decreased(P＜0.001),and NO levels were increased(P＜0.01)in the Ato and GXB groups,while HDL-C levels were increased in the GXB group(P＜0.05)compared with the Model group.Plaque area was decreased(P＜0.05)and the NO level was increased(P＜0.01)in the GXB group compared with the Ato group.A total of 6345 characteristic sequences were obtained from 16S rRNA analysis.α-Diversity analysis indicated that GXB reduced the richness of the GM in AS mice(P＜0.001)and improved its uniformity(P＜0.05).β-Diversity analysis suggested that the microbial community structure in the GXB group was similar to that in the Blank group.The abundance of microbial communities differed among the groups at the phylum and genus levels.At the phylum level,the abundance of Proteobacteria was increased(P＜0.01)in AS mice,while GXB intervention reduced the abundance of Proteobacteria(P＜0.01)and increased the abundance of Verrucomimicrobiota(P＜0.05).At the genus level,GXB effectively increased the abundance of Akkermansia(P＜0.05).SCFAs were significantly increased(P＜0.01)and TMAO levels were significantly decreased(P＜0.01)in the GXB group compared with the Model group.Conclusions GXB can regulate the intestinal flora and intestinal flora metabolites SCFA and TMAO to improve AS.Akkermansia may be a key bacterial genus of the gut microbiota through which GXB may improve AS.