Lactobacillus pentosus strain S-PT84 improves steatohepatitis by maintaining gut permeability
JOURNAL OF ENDOCRINOLOGY
Authors: Sakai, Yuriko; Arie, Hideyuki; Ni, Yinhua; Zhuge, Fen; Xu, Liang; Chen, Guanliang; Nagata, Naoto; Suzuki, Takuya; Kaneko, Shuichi; Ota, Tsuguhito; Nagashimada, Mayumi
Abstract
Intestinal mucosal barrier dysfunction is closely related to the pathogenesis of nonalcoholic steatohepatitis (NASH). Gut immunity has been recently demonstrated to regulate gut barrier function. The Lactobacillus pentosus strain S-PT84 activates helper T cells and natural killer/natural killer T cells. In this study, we examined the effect of S-PT84 on NASH progression induced by high-cholesterol/high-fat diet (CL), focusing on the immune responses involved in gut barrier function. C57BL/6 mice were fed a normal chow or CL diet with or without 1 x 10(10) S-PT84 for 22 weeks. S-PT84 administration improved hepatic steatosis by decreasing triglyceride and free fatty acid levels by 34% and 37%, respectively. Furthermore, S-PT84 inhibited the development of hepatic inflammation and fibrosis, suppressed F4/80(+) macrophage/Kupffer cell infiltration, and reduced liver hydroxyproline content. Administration of S-PT84 alleviated hyperinsulinemia and enhanced hepatic insulin signalling. Compared with mice fed CL diet, mice fed CL+S-PT84 had 71% more CD11c(-)CD206(+) M2 macrophages, resulting in a significantly decreased M1/M2 macrophage ratio in the liver. Moreover, S-PT84 inhibited the CL diet-mediated increase in intestinal permeability. Additionally, S-PT84 reduced the recruitment of interleukin-17-producing T cells and increased the levels of intestinal tight junction proteins, including zonula occludens-1, occludin, claudin-3, and claudin-7. In conclusion, our findings suggest that S-PT84 attenuates diet-induced insulin resistance and subsequent NASH development by maintaining gut permeability. Thus, S-PT84 represents a feasible approach to prevent the development of NASH.
Three-gene risk model in papillary renal cell carcinoma: a robust likelihood-based survival analysis
AGING-US
Authors: Wang, Yutao; Yan, Kexin; Lin, Jiaxing; Wang, Jianfeng; Zheng, Zhenhua; Li, Xinxin; Hua, Zhixiong; Bu, Yuepeng; Shi, Jianxiu; Sun, Siqing; Li, Xuejie; Liu, Yang; Bi, Jianbin
Abstract
Background: Papillary renal cell carcinoma (PRCC) accounts for 15% of all renal cell carcinomas. The molecular mechanisms of renal papillary cell carcinoma remain unclear, and treatments for advanced disease are limited. Result: We built the computing model as follows: Risk score = 1.806 * TPX2 -0.355 * TXNRD2 -0.805 * SLC6A20. The 3-year AUC of overall survival was 0.917 in the training set (147 PRCC samples) and 0.760 in the test set (142 PRCC samples). Based on the robust model, M2 macrophages showed positive correlation with risk score, while M1 macrophages were the opposite. PRCC patients with low risk score showed higher tumor mutation burden. TPX2 is a risk factor, and co-expression factors were enriched in cell proliferation and cancer-related pathways. Finally, the proliferation and invasion of PRCC cell line were decreased in the TPX2 reduced group, and the differential expression was identified. TPX2 is a potential risk biomarker which involved in cell proliferation in PRCC. Conclusion: We conducted a study to develop a three gene model for predicting prognosis in patients with papillary renal cell carcinoma. Our findings may provide candidate biomarkers for prognosis that have important implications for understanding the therapeutic targets of papillary renal cell carcinoma. Method: Gene expression matrix and clinical data were obtained from TCGA (The Cancer Genome Atlas), GSE26574, GSE2048, and GSE7023. Prognostic factors were identified using "survival" and "rbsurv" packages, and a risk score was constructed using Multivariate Cox regression analysis. The co-expression networks of the factors in model were constructed using the "WGCNA" package. The co-expression genes of factors were enriched and displayed the biological process. Based on this robust risk model, immune cells infiltration proportions and tumor mutation burdens were compared between risk groups. Subsequently, using the PRCC cell line, the role of TPX2 was determined by Cell proliferation assay, 5-Ethynyl-20deoxyuridine assay and Transwell assay.