Image_1_Irbesartan Ameliorates Lipid Deposition by Enhancing Autophagy via PKC/AMPK/ULK1 Axis in Free Fatty Acid Induced Hepatocytes.TIF

Irbesartan has shown significant therapeutic effects in hypertensive patients with non-alcoholic fatty liver disease (NAFLD). To determine the underlying mechanisms of its action, we established an in vitro model of NAFLD by treating human and mouse hepatocytes with free fatty acids (FFAs) and angiotensin (Ang) II. Irbesartan significantly reversed AngII/FFA-induced lipid deposition and mitochondrial dysfunction by restoring ATP production and the mitochondrial membrane potential (MMP), and decreasing the levels of reactive oxygen species (ROS) and inflammatory markers. In addition, irbesartan also increased the autophagy flux, in terms of increased numbers of autolysosomes and autophagosomes, and the upregulation and mitochondrial localization of the autophagic proteins Atg5 and LC3BII/I. Activation of protein kinase C (PKC) and inhibition of the autophagic flux exacerbated mitochondrial dysfunction in the steatotic hepatocytes. Furthermore, AngII upregulated PKC which inhibited AMPK phosphorylation via direct interaction with the AngII receptor AT1-R. Irbesartan inhibited PKC and activated AMPK and its downstream effector ULK1, thereby inducing autophagy, decreasing lipid deposition, and restoring mitochondrial function. Taken together, irbesartan triggers autophagy via the PKC/AMPK/ULK1 axis to ameliorate the pathological changes in the steatotic hepatocytes.</p

Association between TLR2 and TLR4 Gene Polymorphisms and the Susceptibility to Inflammatory Bowel Disease: A Meta-Analysis

<div><p>Background</p><p>The associations between toll-like receptor 2 (TLR2) and toll-like receptor 4(TLR4) polymorphisms and inflammatory bowel disease (IBD) susceptibility remain controversial. A meta-analysis was performed to assess these associations.</p><p>Methods</p><p>A systematic search was performed to identify all relevant studies relating TLR2 and TLR4 polymorphisms and IBD susceptibility. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Subgroup analyses were performed by ethnicity and publication quality.</p><p>Results</p><p>Thirty-eight eligible studies, assessing 10970 cases and 7061 controls were included. No TLR2 Arg677Trp polymorphism was found. No significant association was observed between TLR2 Arg753Gln polymorphism and Crohn’s disease (CD) or ulcerative colitis (UC) in all genetic models. Interestingly, TLR4 Asp299Gly polymorphism was significantly associated with increased risk of CD and UC in all genetic models, except for the additive one in CD. In addition, a statistically significant association between TLR4 Asp299Gly polymorphism and IBD was observed among high quality studies evaluating Caucasians, but not Asians. Associations between TLR4 Thr399Ile polymorphisms and CD risk were found only in the allele and dominant models. The TLR4 Thr399Ile polymorphism was associated with UC risk in pooled results as well as subgroup analysis of high quality publications assessing Caucasians, in allele and dominant models.</p><p>Conclusions</p><p>The meta-analysis provides evidence that TLR2 Arg753Gln is not associated with CD and UC susceptibility in Asians; TLR4 Asp299Gly is associated with CD and UC susceptibility in Caucasians, but not Asians. TLR4 Thr399Ile may be associated with IBD susceptibility in Caucasians only. Additional well-powered studies of Asp299Gly and other TLR4 variants are warranted.</p></div

Image_1_The Interaction Between lncRNA SNHG6 and hnRNPA1 Contributes to the Growth of Colorectal Cancer by Enhancing Aerobic Glycolysis Through the Regulation of Alternative Splicing of PKM.TIF

Background: Small nucleolar RNA host gene 6 (SNHG6) acts as a carcinogenic gene in colorectal cancer (CRC). However, previous studies on the mechanism by which long non-coding RNA (lncRNA) SNHG6 exerts its carcinogenic effect in CRC have not involved the direct interaction between SNHG6 and proteins, which is a very important carcinogenic mechanism of lncRNAs. Hence, our study conducted a comprehensive RNA-binding proteins–mass spectrometry (ChIRP–MS) analysis on SNHG6 to further explore its carcinogenic mechanism in CRC.Methods: Proteins that interact with SNHG6 were found using ChIRP–MS analysis and were used to construct the protein–protein interactive (PPI) network using STRING, while the core module of the PPI network was identified using the MCODE plugin in Cytoscape. Pathway enrichment analyses, using WebGestalt, were performed on proteins and RNAs that were found to be associated with the expression of SNHG6 or which directly interacted with SNHG6. Finally, CatRAPID, miRbase, and TargetScanHuman were used to identify the sites of interaction between SNHG6, heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), and pyruvate kinase M (PKM) mRNA.Results: The expression of SNHG6 in CRC was found to be higher than that of normal tissues and was positively correlated with a poor prognosis (p Conclusion: SNHG6 was found to be able to target the mRNA of PKM as well as induce hnRNPA1 to specifically splice PKM mRNA, which increased the proportion of PKM2/PKM1, which may be an important carcinogenic mechanism in CRC that proceeds through the enhancement of aerobic glycolysis in CRC cells.</p

Funnel plots for studies evaluating TLR4 399 polymorphisms and risk of CD included in the meta-analysis.

<p>(a) Trim and fill data for all studies on TLR4 299 polymorphisms and UC risk in the dominant model; (b) Trim and fill data for high quality studies on TLR4 299 polymorphisms and UC risk in the dominant model. Imputed data (squares) are imaginary values to compensate for non-symmetric funnel plot.</p

Data_Sheet_1_The Interaction Between lncRNA SNHG6 and hnRNPA1 Contributes to the Growth of Colorectal Cancer by Enhancing Aerobic Glycolysis Through the Regulation of Alternative Splicing of PKM.docx

Background: Small nucleolar RNA host gene 6 (SNHG6) acts as a carcinogenic gene in colorectal cancer (CRC). However, previous studies on the mechanism by which long non-coding RNA (lncRNA) SNHG6 exerts its carcinogenic effect in CRC have not involved the direct interaction between SNHG6 and proteins, which is a very important carcinogenic mechanism of lncRNAs. Hence, our study conducted a comprehensive RNA-binding proteins–mass spectrometry (ChIRP–MS) analysis on SNHG6 to further explore its carcinogenic mechanism in CRC.Methods: Proteins that interact with SNHG6 were found using ChIRP–MS analysis and were used to construct the protein–protein interactive (PPI) network using STRING, while the core module of the PPI network was identified using the MCODE plugin in Cytoscape. Pathway enrichment analyses, using WebGestalt, were performed on proteins and RNAs that were found to be associated with the expression of SNHG6 or which directly interacted with SNHG6. Finally, CatRAPID, miRbase, and TargetScanHuman were used to identify the sites of interaction between SNHG6, heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), and pyruvate kinase M (PKM) mRNA.Results: The expression of SNHG6 in CRC was found to be higher than that of normal tissues and was positively correlated with a poor prognosis (p Conclusion: SNHG6 was found to be able to target the mRNA of PKM as well as induce hnRNPA1 to specifically splice PKM mRNA, which increased the proportion of PKM2/PKM1, which may be an important carcinogenic mechanism in CRC that proceeds through the enhancement of aerobic glycolysis in CRC cells.</p

Galbraith plot of the association between TLR4 299 polymorphism and UC risk in Caucasians.

<p>Each figure represents a unique article in this meta-analysis. The figures outside the three lines were spotted as the outlier and the possible source of heterogeneity in the analysis pooled from the total available numbers. (a) Galbraith plot results of TLR4 299 polymorphisms and UC risk in the dominant model; (b) Galbraith plot results of TLR4 299 polymorphisms and UC risk in the allele model.</p

Flow chart showing literature search for studies of TLR2 and TLR4 polymorphism in relation to risk of CD and UC.

<p>Flow chart showing literature search for studies of TLR2 and TLR4 polymorphism in relation to risk of CD and UC.</p

Forest plot showing the association between TLR2 and TLR4 polymorphisms and CD and UC risk.

<p>Squares represent the effect size for the odds ratios of CD or UC risk among subjects. Error bars represent 95% confidence intervals (CI). Diamonds represent pooled estimates within each analysis. (a) TLR2 polymorphisms and CD/UC in dominant model; (b) TLR4 polymorphisms and CD/UC in dominant model.</p

Scale for methodologic Quality Assessment of the Single Nucleotide Polymorphism association studies of IBD.

<p>Scale for methodologic Quality Assessment of the Single Nucleotide Polymorphism association studies of IBD.</p

Quality assessment of studies included.

<p>Quality assessment of studies included.</p