Background: Recently, increased expression of TET1 has been shown to inhibit tumor development in many studies. Therefore, a meta-analysis was conducted to assess the prognostic role of TET1 in solid tumors. Methods: PubMed, Embase, and the Web of Science (last updated on June 13, 2019) were searched and 16 eligible studies involving 3100 patients were eventually taken forward into the meta-analysis. Results: Pooled results indicated that higher TET1 expression in cancer tissues was associated with improved overall survival (OS) [hazard ratio (HR) = 0.736, 95% confidence interval (95% CI) = 0.542–0.998, P = .049]. In the subgroup analysis, higher TET1 expression in respiratory tumors (HR = 0.778, 95% CI = 0.639–0.946, P = .012) and breast cancer in Asian patients (HR = 0.326, 95% CI = 0.199–0.533, P < .001) were significantly associated with better OS. In addition, the association between high TET1 expression and prolonged OS was also statistically significant in the following subgroups; data source from samples (HR = 0.561, 95% CI = 0.384–0.819, P = .003), reported in text (HR = 0.539, 95% CI = 0.312–0.931, P = .027), TET1 protein (HR = 0.635, 95% CI = 0.409–0.984, P = .042), Asians (HR = 0.563, 95% CI = 0.376–0.844, P = .005). Conclusion: This meta-analysis displays that high expression levels of TET1 in tissues is significantly associated with better survival in patients with solid tumors. This finding can be used as evidence to the tone that TET1 may be a useful target for the treatment of patients with solid tumors in the future.
Fibrosis contributes to graft loss in chronic renal allograft injury. Endothelial‐to‐mesenchymal transition (EndMT) plays an important role in the development of fibrosis following kidney transplantation. Autophagy plays an important role in the homeostasis of diverse cell types including endothelial cells. Here we demonstrate that inhibition of autophagy by treatment with 3-methyladenine (3-MA) or by silencing autophagy-related (ATG)5 promoted interleukin (IL)-6–dependent EndMT in human umbilical vein endothelial cells (HUVECs) and human renal glomerular endothelial cells (HRGECs), and autophagy inactivation was associated with EndMT in patients with chronic allograft dysfunction. IL-6 level was significantly higher in the culture medium of HUVECs transfected with ATG5 siRNA or treated with 3-MA compared to the respective control groups. IL-6 application induced EndMT in HUVECs and HRGECs, whereas antibody-mediated neutralization of IL-6 suppressed EndMT induced by ATG5 silencing. The protective role of curcumin (Cur) against allograft fibrosis was confirmed in a rat kidney transplantation model of F344 donors to Lewis recipients. Curcumin—a natural polyphenol compound with known antifibrotic effects in various tissues—alleviated IL-6–induced EndMT and promoted autophagy in the allografted organ and in HUVECs. This is the first demonstration of the role of autophagy in renal allograft fibrosis; our findings indicate that curcumin can alleviate chronic renal allograft injury by suppressing IL-6–dependent EndMT via activation of autophagy.
The volume of the data has been rocketed since the new information era arrives. How to protect information privacy and detect the threat whenever the intrusion happens has become a hot topic. In this essay, we are going to look into the latest machine learning techniques (including deep learning) which are applicable in intrusion detection, malware detection, and vulnerability detection. And the comparison between the traditional methods and novel methods will be demonstrated in detail. Specially, we would examine the whole experiment process of representative examples from recent research projects to give a better insight into how the models function and cooperate. In addition, some potential problems and improvements would be illustrated at the end of each section.
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