There were 3 000 Zhuangs,1 102 Miaos, and 1 283 Yaos in Baise City of Guangxi,who were enrolled in this population sampling stratfying survey. Height, weight, blood pressure, fasting blood glucose, and lipids were determined, and compared with those of 2 000 Hans of the same town. The prevalence of hypertension and metablic syndrome in Zhuang inhabitants was high, so were the disorders of glycemia and lipidemia, while in Miao and Yao minorities, the prevalences were comparatively lower. The awareness, treatment, and control of hypertension in these minorities were insufficient.

Objective:To construct A novel scoring model of immune signatures for colon cancer based on machine learning,which improve the survival prediction and immune therapy.Methods:Screening immune signatures from 1 301 immune-related genes(IRG)by the combined strategy of Lasso+bootstrap+multi Cox to calculate IRG scores of colon cancer patients from TCGA databases,and comprehensive the differences on function,prognostic status and immune therapy between high IRG scores group and IRG scores group.Results:Groups based on IRG scores were significantly different on the prognostic status of colon cancer patients,which were validated by other independent datasets.The IRG scores also could assess the effect of immune therapy of colon cancer.Conclusion:This study provides ideas for immune therapy and researches of colon cancer based on immune genes,and IRG scores can be used to assess the prognosis of colon cancer patients.