Objective To investigate the function of sorafenib on the growth of hepatocellular carcinoma by establishing subcutaneous transplantation tumor model with nude mice.To explore the effect of sorafenib on circadian clock gene expression in hepatoma cells.Methods Mouse tumor model was established by implanting hepatocarcinoma cell (HepG2) subcutaneously in Balb/C nude mice.Sixteen experimental mice were randomly divided into two groups:sorafenib treatment group (n =8) and solvent control group (n =8).The nude mice were treated with sorafenib (100 mg/kg) and DMSO daily by intragastric administration,respectively.The volume of tumors was recorded every 3 days.The expressions level of circadian clock genes (Per1,Per2,Per3,CLOCK,Cry1,Cry2,BMAL1 and CKIε) were detected by real-time polymerase chain reaction (Real-time PCR).The correlations between the size of the xenografts and the expressions of the circadian clock genes were further analyzed.Results Compared with the control group,the tumor size in the sorafenib treatment group were significantly smaller comparing with the control group.Results of Real-time PCR showed that the expression level of Per1,Cry1 and BMAL1 mRNA was remarkably decreased in the treatment group (Per1,P =0.02;Cry1,P =0.002;BMAL1,P =0.035),the differences were statistically significant.Correlation analysis showed that the size of subcutaneous transplantation tumorsin nude mice was negatively correlated with the expressions of Per1,Per2,Cry1 and Cry2 mRNA in control group.While,the size of subcutaneous transplantation tumors was negatively correlated with the expressions of Per2,Per3 and BMAL1 levels in the sorafenib treatment group.Conclusions There is a negative correlation between the expression levels of some biological clock genes and the size of transplantation tumor in nude mice.Sorafenib treatment significantly inhibited the growth of hepatocellular carcinoma in nude mice and down-regulation the expressions of Per1,Cry1 and BMAL1 mRNA in hepatoma cells.

Objective:To investigate the prevalence and the risk factors of Helicobacter pylori( H. pylori) infection in Qinghai Province with a multi-center cross-sectional study. Methods:From May to December in 2021, stratified sampling was conducted in Xining City, Haidong agricultural district, Hainan Tibetan Autonomous Prefecture, Haibei Tibetan Autonomous Prefecture and Yushu Tibetan Autonomous Prefecture by 20 centers, including the Affiliated Hospital of Qinghai University, Qinghai Red Cross Hospital and Qinghai Renji Hospital, etc. A questionnaire survey was carried out among the individuals undergoing routine health checkups. The questionnaire included general information, lifestyle and family history, etc. 13C-urea breath test was performed to diagnose H. pylori infection. Chi-square test, trend Chi-square test, segmentation method and multivariate logistic regression analysis were performed for statistical analysis. Results:The infection rate of H. pylori in Qinghai area was 53.6% (2 531/4 724). The age distribution of infection was statistically significant ( χ2=15.95, P=0.007), the infection rate in individuals aged 15 to<30 was higher than that of individuals aged 60 to< 75 (57.6%, 626/1 086 vs.49.5%, 231/467), and the difference was statistically significant ( χ2=8.83, P=0.003). With the increase of age, the infection rate decreased in female over 30 years old ( χ2trend=5.89, P=0.015). There were statistically significant differences in H. pylori infection rate among different ethnic groups ( χ2=28.13, P<0.001); the infection rate of Tibetan population was higher than that of Han population (62.9%, 313/498 vs. 51.5%, 1 804/3 503), and the difference was statistically significant ( χ2=22.56, P<0.001). The H. pylori infection rate in people living at an altitude >3 500 m was higher than that of people living at an altitude between 1 500 m and 3 500 m (61.8%, 327/529 vs. 52.5%, 2 204/4 195), and the difference was statistically significant ( χ2=16.25, P<0.001). Compared with those without corresponding habits, the infection rate of H. pylori was higher in smokers (62.1%, 1 081/1 740 vs. 48.6%, 1 450/2 984), in people who had the habit of eating hand grabbed mutton (55.4%, 967/1 744 vs. 52.5%, 1 564/2 980), raw garlic (55.5%, 968/1 744 vs. 52.4%, 1 563/2 980), spicy food (55.6%, 1 471/2 647 vs. 51.0%, 1 060/2 077), sweet food (55.2%, 1 187/2 149 vs. 52.2%, 1 344/2 575), the infection rate of tea drinkers was lower (50.5%, 1 135/2 247 vs. 56.4%, 1 396/2 477), and the differences were statistically significant ( χ2=80.94, 3.89, 9.63, 4.36, 4.13 and 16.19, all P<0.05). The results of logistic regression analysis indicated that Tibetan ( OR=1.379, 95% confidence interval (95% CI) 1.120 to 1.699), the Hui people ( OR=1.362, 95% CI 1.117 to 1.662), living at an altitude over 3 500 m ( OR=1.355, 95% CI 1.107 to 1.657), smoking ( OR=1.847, 95% CI 1.629 to 2.094), and spicy food ( OR=1.224, 95% CI 1.084 to 1.382) were independent risk factors of H. pylori infection (all P<0.05). Conclusions:The infection rate of H. pylori in Qinghai Province is higher than the average level in inland China. The infection rate of people with different ages, nationalities, altitudes of residence, occupations, living and eating habits were different. The infection rate of female over 30 years old is decreasing year by year. The infection risk is high in Hui people and Tibetan, spicy food lovers, smokers and people living at an altitude >3 500 m.

Objective The Kellinghaus grading method was used to manually read and grade the thin-layer CT of sternal end of clavicle,and a variety of traditional statistical methods as well as machine learning methods were used to construct age estimation models for adolescents and adults in early adulthood,to explore the value of the application of machine learning technology in the study of age estimation of the Han Chinese population in Sichuan.Methods Thin-section CT images of the chest were retrospectively collected from 491 individuals aged 10～30 years,and the collected samples were assigned a reading grade with reference to the Kellinghaus grading method.10%of the xases were randomly selected as the test set,and the remaining data were used as the training set to construct a variety of traditional statistical regression models and machine learning models for estimating the age of adolescents and adults in early adulthood,and the performance of the models was evaluated by using the mean absolute error(MAE).Results The statistical regression model with the best efficacy was the cubic regression model,with an MAE value of 1.34 for males and 1.57 for females;of the three machine learning models,the Random Forest model had the best predictive efficacy for males,with an MAE value of 1.39,and the Support Vector model had the best predictive efficacy for females,with an MAE value of 1.51.Conclusion In the construction of age estimation models for sternal end of clavicle,the machine learning model has a certain improvement in the accuracy of age prediction,but there is no obvious advantage compared with the traditional statistical regression model,and the use of the machine learning method in age estimation based on sternal end of clavicle still needs further exploration.