Is Hepatocellular Carcinoma in Fatty Liver Different to Non-Fatty Liver?

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in Australia and is recognised to play a role in the development of hepatocellular carcinoma (HCC). There are no clear guidelines regarding screening for HCC in NAFLD. The aim of this retrospective study was to compare the characteristics and survival rates of NAFLD-HCC to patients with non-NAFLD-HCC to help guide future research in this area. METHODS: A total of 152 HCC patients with either NAFLD (n = 36) or non-NAFLD (n = 116) were retrospectively analysed from the HCC database and medical records. Chi-square and independent t-test were used to compare baseline characteristics and Kaplan-Meier curves and Cox models were used for survival analysis. RESULTS: Patients with NAFLD-HCC were more likely to be diagnosed due to symptoms rather than through screening, and at an older age, compared with non-NAFLD HCC. The median survival rates were lower in NAFLD-HCC (17.2 months) than in those with non-NAFLD-HCC (23.5 months). CONCLUSION: There is a rise in the number of HCC cases in patients with NAFLD, and this has significant implications for hepatologists as they are presented with more advanced diseases and have poorer outcomes. Future studies on HCC will need to identify this group earlier in order to have an impact on the HCC survival rate.

Thalamic Kv 7 channels: pharmacological properties and activity control during noxious signal processing.

BACKGROUND AND PURPOSE: The existence of functional K(v)7 channels in thalamocortical (TC) relay neurons and the effects of the K(+)-current termed M-current (I(M)) on thalamic signal processing have long been debated. Immunocytochemical evidence suggests their presence in this brain region. Therefore, we aimed to verify their existence, pharmacological properties and function in regulating activity in neurons of the ventrobasal thalamus (VB). EXPERIMENTAL APPROACH: Characterization of K(v)7 channels was performed by combining in vitro, in vivo and in silico techniques with a pharmacological approach. Retigabine (30 µM) and XE991 (20 µM), a specific K(v)7 channel enhancer and blocker, respectively, were applied in acute brain slices during electrophysiological recordings. The effects of intrathalamic injection of retigabine (3 mM, 300 nL) and/or XE991 (2 mM, 300 nL) were investigated in freely moving animals during hot-plate tests by recording behaviour and neuronal activity. KEY RESULTS: K(v)7.2 and K(v)7.3 subunits were found to be abundantly expressed in TC neurons of mouse VB. A slow K(+)-current with properties of IM was activated by retigabine and inhibited by XE991. K(v)7 channel activation evoked membrane hyperpolarization, a reduction in tonic action potential firing, and increased burst firing in vitro and in computational models. Single-unit recordings and pharmacological intervention demonstrated a specific burst-firing increase upon I(M) activation in vivo. A K(v)7 channel-mediated increase in pain threshold was associated with fewer VB units responding to noxious stimuli, and increased burst firing in responsive neurons. CONCLUSIONS AND IMPLICATIONS: K(v)7 channel enhancement alters somatosensory activity and may reflect an anti-nociceptive mechanism during acute pain processing.

Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique.

BACKGROUND: Understanding gene interactions is a fundamental question in systems biology. Currently, modeling of gene regulations using the Bayesian Network (BN) formalism assumes that genes interact either instantaneously or with a certain amount of time delay. However in reality, biological regulations, both instantaneous and time-delayed, occur simultaneously. A framework that can detect and model both these two types of interactions simultaneously would represent gene regulatory networks more accurately. RESULTS: In this paper, we introduce a framework based on the Bayesian Network (BN) formalism that can represent both instantaneous and time-delayed interactions between genes simultaneously. A novel scoring metric having firm mathematical underpinnings is also proposed that, unlike other recent methods, can score both interactions concurrently and takes into account the reality that multiple regulators can regulate a gene jointly, rather than in an isolated pair-wise manner. Further, a gene regulatory network (GRN) inference method employing an evolutionary search that makes use of the framework and the scoring metric is also presented. CONCLUSION: By taking into consideration the biological fact that both instantaneous and time-delayed regulations can occur among genes, our approach models gene interactions with greater accuracy. The proposed framework is efficient and can be used to infer gene networks having multiple orders of instantaneous and time-delayed regulations simultaneously. Experiments are carried out using three different synthetic networks (with three different mechanisms for generating synthetic data) as well as real life networks of Saccharomyces cerevisiae, E. coli and cyanobacteria gene expression data. The results show the effectiveness of our approach.