Aims: To evaluate the prevalence of sleep disturbance in older adults with or without mild cognitive impairment (MCI) and associated factors among residents in rural central China. Methods: A cross-sectional survey was conducted in adults in rural areas of the Hunan province aged≥60 years. Study participants (N = 1213) included 479 individuals meeting the criteria for MCI and 734 with normal cognitive abilities. The participants completed the Athens Insomnia Scale, Stress Resilience Quotient Scale, Affect Balance Scale and Activities of Daily Living (ADL) Scale. Chi-square test, Wilcoxon rank sum analyses and multiple logistic regression were used in this study. Results: A total of 60.33% of participants with MCI demonstrated sleep disturbance (60.33%, 95% CI: 0.559-0.649), which was significantly higher than in the non-MCI group (43.73%, 95% CI: 0.759-0.838). Multiple logistic regression conducted separately in the populations of older adults with or without MCI showed that age, drinking habits, affect balance and activities of daily life were correlates of self-reported sleep disturbance in rural older adults with MCI ( B = −5.469), whereas age, ADL, living arrangement and resilience were the main influencing factors in older adults without MCI ( B = 2.991). Conclusion: Sleep disturbance is more common in older adults with MCI than without MCI in rural areas of China. The factors influencing sleep disturbances vary between older adults with or without MCI, with age and ADL representing common factors influencing sleep disturbance in both groups. Interventions focusing on the age, drinking habits, affect balance and ADL may improve sleep quality in MCI older adults.

Background: Cancer is still the leading cause of death in humans, and the fourth leading cause of death is colorectal cancer. Tumor bioinformatics has been developing in recent years, the prognosis and quality of life of patients can be improved by using relevant tools to understand the molecular pathogenesis of colorectal cancer and related prognostic markers. Methods: In this study, Bioinformatics analysis of the snp-related data of colon cancer patients from the TCGA database, it was found that the expression levels of 4 mutated genes (CTTNBP2,DAPK1, DMXL1,SPTBN2) were significantly different from those of wild type and their prognosis. In order to explore how the core genes affect the prognosis of patients, the gene expression of these core genes was analyzed. Results: It was found that the core genes are related to a variety of cancer-related pathway genes, including pi3k-akt pathway and TSC/mTOR pathway. Drug sensitivity analysis showed that SPTBN2 could be inhibited by a variety of drugs, including austocystin D, afatinib, and belinostat. Tumor immunity is closely related to tumor therapy. Through the analysis of immune infiltration of core genes, it was found that DAPK1 and DMXL2 were associated with a variety of immune cell infiltration. Conclusion: Therefore, the detection of genetic mutations and related expressions may be significant in predicting the prognosis of patients with colon cancer. Through the study of high-throughput information excavating, it was discovered that the molecular pathogenesis and prognosis of patients with colon cancer were helpful to the bioinformatics theory.