MiR-501-3p/SPC24 axis affects cell proliferation, migration, invasion, apoptosis, and prognosis in renal cell carcinoma

It has been confirmed that the expression of miR-501-3p is closely related to the behavior of several cancers. This study aimed to elucidate the effects of miR-501-3p/SPC24 axis on the behavior of renal cancer cells and to identify its prognostic value in renal cancer. First, the expression of miR-501-3p in the renal cell carcinoma (RCC) cell line was detected using real-time quantitative polymerase chain reaction (RT-qPCR). Second, cell function identification experiments were performed, including CCK-8, scratch, transwell invasion, and flow cytometry assays. Several databases were applied to explore the possible mechanism of miR-501-3p tumor suppressor effect in RCC. To explore the value of miR-501-3p/SPC24 axis in predicting renal cancer patient overall survival (OS), GEPIA (http://gepia.cancer-pku.cn/index.html) was used. Finally, western blot was performed to detect the expression level of SPC24 in renal cancer cells predicted by bioinformatics analysis. Dual-Luciferase Reporter Assay was used to verify if SPC24 is a target of mir-501-3p. MiR-501-3p was found to be down-regulated in cancer cells and tissues and to play a role in suppressing tumor cell proliferation, cell viability, cell migration, and cell invasion, while promoting apoptosis. We also found that high expression levels of SPC24 were associated with shorter OS time in patients diagnosed with renal cell carcinoma. In addition, the results of TCGA data analysis and western blot showed that the tumor suppressor effect of miR-501-3p may be achieved by targeting SPC24. The MiR-501-3p/SPC24 axis affects cell proliferation, migration, invasion, apoptosis, and prognosis in renal cell carcinoma

Reliability Analysis of Loess Landslide Considering the Change of Groundwater Level

Abstract The reliability analysis of landslide is very important for the early warning and prevention of landslide. In this paper, Monte-Carlo method is used to analyze groundwater level, the variation coefficient of c and ϕ, and paleosol layer impact on the reliability of landslide in Jingyang South tableland. The reliability analysis results are as follows: (1) With the increase of groundwater level, the probability of landslide failure increases and the safety factor decreases. When the depth of groundwater level is 61m, the failure probability is 2.46%, and the average safety factor is 1.166; when the groundwater depth is 31.6 m, the average safety factor is 0.791, and the failure probability is 98.94%. (2) The coefficient of variation “δ” is positively related to the failure probability of landslide, and negatively related to the reliability index. When δ &lt; 0.05, the increasing trend of failure probability and the decreasing trend of reliability index are most significant. (3) Paleosol layer has certain influence on Reliability. When the groundwater depth is less than 35.3 m, the average safety factor with paleosol layer is less than that without paleosol, but the failure probability is higher. When the groundwater depth is more than 35.3 m, it shows the opposite relationship.</jats:p

The impact of individual and social environmental factors on the health of elderly migrants in China: an analysis based on social-ecological systems theory

Abstract Background With the increasing number of elderly migrants in China, ensuring their health and access to healthcare services have become a significant public health challenge. The social environment of elderly migrants is composed of multiple interconnected systems, each of which exerts a complex and multidimensional influence on their health. This study investigates how individual and social environmental factors affect the health of elderly migrants in China. Methods Data from 4,744 respondents were obtained from the 2017 China Migrants Dynamic Survey. Guided by social-ecological systems theory, we explored the relationship between individual and social environmental factors and the health outcomes of elderly migrants using binary logistic regression models. Results Individual factors, such as gender, age, education level, and average monthly household income, were found to significantly affect the self-rated health of the respondents. Furthermore, social environmental factors, including types of social interactions, the establishment of health records, the amount of health knowledge acquired, and travel time to medical institutions, also had a notable influence on the health of elderly migrants. Conclusions This study suggests that individual and social environmental factors significantly influence the health of elderly migrants. To improve their health, targeted strategies should focus on fostering diverse social networks, enhancing comprehensive health education, optimizing public health services, and creating an equitable institutional framework