Hypoxia-inducible factor 2α drives nonalcoholic fatty liver progression by triggering hepatocyte release of histidine rich glycoprotein

Mechanisms underlying progression of non-alcoholic fatty liver disease (NAFLD) are still incompletely characterized. Hypoxia and hypoxia inducible factors (HIFs) have been implicated in the pathogenesis of chronic liver diseases but the actual role of HIF-2α in the evolution of NAFLD has never been investigated in detail. In this study, we show that HIF-2α is selectively overexpressed in the cytosol and the nuclei of hepatocytes in a very high percentage (> 90%) of liver biopsies from a cohort of NAFLD patients at different stage of the disease evolution. Similar features were also observed in mice with steatohepatitis induced by feeding a methionine/choline-deficient (MCD) diet. Experiments performed in mice carrying hepatocyte-specific deletion of HIF-2α and related control littermates fed with either choline-deficient L-amino acid-refined (CDAA) or MCD diets showed that HIF-2α deletion ameliorated the evolution of NAFLD by decreasing parenchymal injury, fatty liver, lobular inflammation and the development of liver fibrosis. The improvement in NAFLD progression in HIF-2α deficient mice was related to a selective down-regulation in the hepatocyte production of Histidine-Rich Glycoprotein (HRGP), recently proposed to sustain macrophage M1 polarization. In vitro experiments confirmed that the up-regulation of hepatocyte HRGP expression was hypoxia- and HIF-2α-dependent. Finally, analyses performed on specimens from NAFLD patients indicated that HRGP was overexpressed in all patients showing hepatocyte nuclear staining for HIF-2α and revealed a significant positive correlation between HIF-2α and HRGP liver transcripts levels in these patients

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

<p>Abstract</p> <p>Background</p> <p>Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.</p> <p>Methods</p> <p>All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.</p> <p>Results</p> <p>The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.</p> <p>Conclusions</p> <p>An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.</p

Evidence of attentional impairments using virtual driving simulation in multiple sclerosis

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