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Role of PTEN in Oxidative Stress and DNA Damage in the Liver of Whole-Body Pten Haplodeficient Mice
(2016)
Type 2 diabetes (T2DM) and obesity are frequently associated with non-alcoholic fatty liver disease (NAFLD) and with an elevated cancer incidence. The molecular mechanisms of carcinogenesis in this context are only partially understood. High blood insulin levels are typical in early T2DM and excessive insulin can cause elevated reactive oxygen species (ROS) production and genomic instability. ROS are important for various cellular functions in signaling and host defense. However, elevated ROS formation is thought to be involved in cancer induction. In the molecular events from insulin receptor binding to genomic damage, some signaling steps have been identified, pointing at the PI3K/AKT pathway. For further elucidation Phosphatase and Tensin homolog (Pten), a tumour suppressor phosphatase that plays a role in insulin signaling by negative regulation of PI3K/AKT and its downstream targets, was investigated here. Dihydroethidium (DHE) staining was used to detect ROS formation in immortalized human hepatocytes. Comet assay and micronucleus test were performed to investigate genomic damage in vitro. In liver samples, DHE staining and western blot detection of HSP70 and HO-1 were performed to evaluate oxidative stress response. DNA double strand breaks (DSBs) were detected by immunohistostaining. Inhibition of PTEN with the pharmacologic inhibitor VO-OHpic resulted in increased ROS production and genomic damage in a liver cell line. Knockdown of Pten in a mouse model yielded increased oxidative stress levels, detected by ROS levels and expression of the two stress-proteins HSP70 and HO-1 and elevated genomic damage in the liver, which was significant in mice fed with a high fat diet. We conclude that PTEN is involved in oxidative stress and genomic damage induction in vitro and that this may also explain the in vivo observations. This further supports the hypothesis that the PI3K/AKT pathway is responsible for damaging effects of high levels of insulin.
This study investigates a two component decomposition technique for HH/VV-polarized PolSAR (Polarimetric Synthetic Aperture Radar) data. The approach is a straight forward adaption of the Yamaguchi decomposition and decomposes the data into two scattering contributions: surface and double bounce under the assumption of a negligible vegetation scattering component in Tundra environments. The dependencies between the features of this two and the classical three component Yamaguchi decomposition were investigated for Radarsat-2 (quad) and TerraSAR-X (HH/VV) data for the Mackenzie Delta Region, Canada. In situ data on land cover were used to derive the scattering characteristics and to analyze the correlation among the PolSAR features. The double bounce and surface scattering features of the two and three component scattering model (derived from pseudo-HH/VV- and quad-polarized data) showed similar scattering characteristics and positively correlated-R2 values of 0.60 (double bounce) and 0.88 (surface scattering) were observed. The presence of volume scattering led to differences between the features and these were minimized for land cover classes of low vegetation height that showed little volume scattering contribution. In terms of separability, the quad-polarized Radarsat-2 data offered the best separation of the examined tundra land cover types and will be best suited for the classification. This is anticipated as it represents the largest feature space of all tested ones. However; the classes “wetland” and “bare ground” showed clear positions in the feature spaces of the C- and X-Band HH/VV-polarized data and an accurate classification of these land cover types is promising. Among the possible dual-polarization modes of Radarsat-2 the HH/VV was found to be the favorable mode for the characterization of the aforementioned tundra land cover classes due to the coherent acquisition and the preserved co-pol. phase. Contrary, HH/HV-polarized and VV/VH-polarized data were found to be best suited for the characterization of mixed and shrub dominated tundra.
Invasive aspergillosis (IA) is a devastating opportunistic infection and its treatment constitutes a considerable burden for the health care system. Immunocompromised patients are at an increased risk for IA, which is mainly caused by the species Aspergillus fumigatus. An early and reliable diagnosis is required to initiate the appropriate antifungal therapy. However, diagnostic sensitivity and accuracy still needs to be improved, which can be achieved at least partly by the definition of new biomarkers. Besides the direct detection of the pathogen by the current diagnostic methods, the analysis of the host response is a promising strategy toward this aim. Following this approach, we sought to identify new biomarkers for IA. For this purpose, we analyzed gene expression profiles of hematological patients and compared profiles of patients suffering from IA with non-IA patients. Based on microarray data, we applied a comprehensive feature selection using a random forest classifier. We identified the transcript coding for the S100 calcium-binding protein B (S100B) as a potential new biomarker for the diagnosis of IA. Considering the expression of this gene, we were able to classify samples from patients with IA with 82.3% sensitivity and 74.6% specificity. Moreover, we validated the expression of S100B in a real-time reverse transcription polymerase chain reaction (RT-PCR) assay and we also found a down-regulation of S100B in A. fumigatus stimulated DCs. An influence on the IL1B and CXCL1 downstream levels was demonstrated by this S100B knockdown. In conclusion, this study covers an effective feature selection revealing a key regulator of the human immune response during IA. S100B may represent an additional diagnostic marker that in combination with the established techniques may improve the accuracy of IA diagnosis.