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Hepatitis C virus (HCV) infection is associated with alterations in host lipid and insulin signaling cascades, which are partially explained by a dependence of the HCV life cycle on key molecules in these metabolic pathways. Yet, little is known on the role in the HCV life cycle of glycogen synthase kinase 3 (GSK3), one of the most important kinases in cellular metabolism. Therefore, the impact of GSK3 on the HCV life cycle was assessed in human hepatoma cell lines harboring subgenomic genotype 1b and 2a replicons or producing cell culture-derived HCV genotype 2a by exposure to synthetic GSK3 inhibitors, GSK3 gene silencing, overexpression of GSK3 constructs and immunofluorescence analyses. In addition, the role of GSK3 in hepatitis E virus (HEV) replication was investigated to assess virus specificity of the observed findings. We found that both inhibition of GSK3 function by synthetic inhibitors as well as silencing of GSK3β gene expression resulted in a decrease of HCV replication and infectious particle production, whereas silencing of the GSK3α isoform had no relevant effect on the HCV life cycle. Conversely, overexpression of GSK3β resulted in enhanced HCV replication. In contrast, GSK3β had no effect on replication of subgenomic HEV replicon. The pro-viral effect of GSK3β on HCV replication was mediated by supporting expression of microRNA-122 (miR-122), a micro-RNA which is mandatory for wild-type HCV replication, as GSK3 inhibitors suppressed miR-122 levels and as inhibitors of GSK3 had no antiviral effect on a miR-122-independent HCV mutant. In conclusion, we have identified GSK3β is a novel host factor supporting HCV replication by maintaining high levels of hepatic miR-122 expression.
Platelets participate in the development of liver fibrosis in animal models, but little is known about the benefit of antiplatelet agents in preventing liver fibrosis in humans. We therefore explored the relationship between the use of antiplatelet agents and liver fibrosis in a prospective cohort study of patients at high risk of liver fibrosis and cardiovascular events. Consecutive patients undergoing elective coronary angiography at the University Hospital Frankfurt were prospectively included in the present study. Associations between use of antiplatelet agents (acetyl salicylic acid, P2Y12 receptor antagonists) and liver fibrosis were assessed in regression models, and the relationship between platelet‐derived growth factor beta (PDGF‐β) serum concentration, platelets, liver fibrosis, and use of antiplatelet agents was characterized. Out of 505 included patients, 337 (67%) received antiplatelet agents and 134 (27%) had liver fibrosis defined as a FibroScan transient elastography (TE) value ≥7.9 kPa. Use of antiplatelet agents was inversely associated with the presence of liver fibrosis in univariate and multivariate analyses (multivariate odds ratio [OR], 0.67; 95% confidence interval [CI], 0.51‐0.89; P = 0.006). Use of antiplatelet agents was also inversely associated with FibroTest values (beta, –0.38; SD beta, 0.15; P = 0.02). Furthermore, there was a significant correlation between platelet counts and PDGF‐β serum concentration (rho, 0.33; P < 0.0001), but PDGF‐β serum levels were not affected by antiplatelet agents. Conclusion: There is a protective association between the use of antiplatelet agents and occurrence of liver fibrosis. A randomized controlled trial is needed to explore causality and the potential of antiplatelet agents as antifibrotic therapy in patients at risk for liver fibrosis progression.
Background: Liver cirrhosis is associated with profound immunodysfunction, i.e. a parallel presence of chronic systemic inflammation and immunosuppression, which can result in acute-on-chronic liver failure (ACLF). Omega-3 fatty acids are precursors of pro-resolving mediators and support the resolution of inflammation.
Objective: The aim of this study was to determine plasma levels of omega-3 fatty acids in patients with liver cirrhosis and ACLF.
Methods: Patients with liver cirrhosis with and without ACLF were enrolled in a prospective cohort study and analyzed post-hoc for the present sub-study. Clinical data and biomaterials were collected at baseline and at day 7, 28 and after 3 months of follow-up. Plasma concentrations of arachidonic acid (ARA) and docosahexaenoic acid (DHA), which represent key omega-6 and -3 fatty acids, respectively, were quantified and associated with markers of systemic inflammation and severity of liver cirrhosis.
Results: A total of 117 patients were included in the present analyses. Of those, 26 (22.2%), 51 (43.6%) and 40 (34.2%) patients had compensated or decompensated liver cirrhosis, and ACLF. Plasma levels of ARA and DHA were similar in patients with compensated cirrhosis, decompensated cirrhosis, and ACLF. Furthermore, no significant association between plasma ARA or DHA and C-reactive protein or peripheral blood leukocytes were observed (P>0.05).
Conclusion: In our study plasma levels of key omega-3 and omega-6 fatty acid are neither associated with the severity of liver cirrhosis nor with liver-cirrhosis-associated systemic inflammation.
Most studies in the life sciences and other disciplines involve generating and analyzing numerical data of some type as the foundation for scientific findings. Working with numerical data involves multiple challenges. These include reproducible data acquisition, appropriate data storage, computationally correct data analysis, appropriate reporting and presentation of the results, and suitable data interpretation.
Finding and correcting mistakes when analyzing and interpreting data can be frustrating and time-consuming. Presenting or publishing incorrect results is embarrassing but not uncommon. Particular sources of errors are inappropriate use of statistical methods and incorrect interpretation of data by software. To detect mistakes as early as possible, one should frequently check intermediate and final results for plausibility. Clearly documenting how quantities and results were obtained facilitates correcting mistakes. Properly understanding data is indispensable for reaching well-founded conclusions from experimental results. Units are needed to make sense of numbers, and uncertainty should be estimated to know how meaningful results are. Descriptive statistics and significance testing are useful tools for interpreting numerical results if applied correctly. However, blindly trusting in computed numbers can also be misleading, so it is worth thinking about how data should be summarized quantitatively to properly answer the question at hand. Finally, a suitable form of presentation is needed so that the data can properly support the interpretation and findings. By additionally sharing the relevant data, others can access, understand, and ultimately make use of the results.
These quick tips are intended to provide guidelines for correctly interpreting, efficiently analyzing, and presenting numerical data in a useful way.