Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam.

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years

Physiological Effects of Superoxide Dismutase on Altered Visual Function of Retinal Ganglion Cells in db/db Mice

Background: The C57BLKS/J db/db (db/db) mouse is a widely used type 2 diabetic animal model, and this model develops early inner retinal neuronal dysfunction beginning at 24 weeks. The neural mechanisms that mediate early stage retinal dysfunction in this model are unknown. We evaluated visual response properties of retinal ganglion cells (RGCs) during the early stage of diabetic insult (8, 12, and 20 wk) in db/db mice and determined if increased oxidative stress plays a role in impaired visual functions of RGCs in 20 wk old db/db mice. Methodology/Principal Findings: In vitro extracellular single-unit recordings from RGCs in wholemount retinas were performed. The receptive field size, luminance threshold, and contrast gain of the RGCs were investigated. Although ONand OFF-RGCs showed a different time course of RF size reduction, by 20 wk, the RF of ON- and OFF-RGCs were similarly affected. The LT of ON-RGCs was significantly elevated in 12 and 20 wk db/db mice compared to the LT of OFF-RGCs. The diabetic injury also affected contrast gains of ON- and OFF-RGCs differently. The generation of reactive oxidative species (ROS) in fresh retina was estimated by dihydroethidium. Superoxide dismutase (SOD) (300 unit/ml) was applied in Ames medium to the retina, and visual responses of RGCs were recorded for five hours. ROS generation in the retinas of db/db mice increased at 8wk and continued to progress at 20 wk of ages. In vitro application of SOD improved visual functions in 20 wk db/db mice but the SOD treatment affected ON- and OFF-RGCs differently in db/m retina

Phospholipase C-ε Regulates Epidermal Morphogenesis in Caenorhabditis elegans

Migration of cells within epithelial sheets is an important feature of embryogenesis and other biological processes. Previous work has demonstrated a role for inositol 1,4,5-trisphosphate (IP3)-mediated calcium signalling in the rearrangement of epidermal cells (also known as hypodermal cells) during embryonic morphogenesis in Caenorhabditis elegans. However the mechanism by which IP3 production is stimulated is unknown. IP3 is produced by the action of phospholipase C (PLC). We therefore surveyed the PLC family of C. elegans using RNAi and mutant strains, and found that depletion of PLC-1/PLC-ε produced substantial embryonic lethality. We used the epithelial cell marker ajm-1::gfp to follow the behaviour of epidermal cells and found that 96% of the arrested embryos have morphogenetic defects. These defects include defective ventral enclosure and aberrant dorsal intercalation. Using time-lapse confocal microscopy we show that the migration of the ventral epidermal cells, especially of the leading cells, is slower and often fails in plc-1(tm753) embryos. As a consequence plc-1 loss of function results in ruptured embryos with a Gex phenotype (gut on exterior) and lumpy larvae. Thus PLC-1 is involved in the regulation of morphogenesis. Genetic studies using gain- and loss-of-function alleles of itr-1, the gene encoding the IP3 receptor in C. elegans, demonstrate that PLC-1 acts through ITR-1. Using RNAi and double mutants to deplete the other PLCs in a plc-1 background, we show that PLC-3/PLC-γ and EGL-8/PLC-β can compensate for reduced PLC-1 activity. Our work places PLC-ε into a pathway controlling epidermal cell migration, thus establishing a novel role for PLC-ε

Constraint-based modeling analysis of the metabolism of two Pelobacter species

BACKGROUND: Pelobacter species are commonly found in a number of subsurface environments, and are unique members of the Geobacteraceae family. They are phylogenetically intertwined with both Geobacter and Desulfuromonas species. Pelobacter species likely play important roles in the fermentative degradation of unusual organic matters and syntrophic metabolism in the natural environments, and are of interest for applications in bioremediation and microbial fuel cells. RESULTS: In order to better understand the physiology of Pelobacter species, genome-scale metabolic models for Pelobacter carbinolicus and Pelobacter propionicus were developed. Model development was greatly aided by the availability of models of the closely related Geobacter sulfurreducens and G. metallireducens. The reconstructed P. carbinolicus model contains 741 genes and 708 reactions, whereas the reconstructed P. propionicus model contains 661 genes and 650 reactions. A total of 470 reactions are shared among the two Pelobacter models and the two Geobacter models. The different reactions between the Pelobacter and Geobacter models reflect some unique metabolic capabilities such as fermentative growth for both Pelobacter species. The reconstructed Pelobacter models were validated by simulating published growth conditions including fermentations, hydrogen production in syntrophic co-culture conditions, hydrogen utilization, and Fe(III) reduction. Simulation results matched well with experimental data and indicated the accuracy of the models. CONCLUSIONS: We have developed genome-scale metabolic models of P. carbinolicus and P. propionicus. These models of Pelobacter metabolism can now be incorporated into the growing repertoire of genome scale models of the Geobacteraceae family to aid in describing the growth and activity of these organisms in anoxic environments and in the study of their roles and interactions in the subsurface microbial community

Identification of a Highly Conserved H1 Subtype-Specific Epitope with Diagnostic Potential in the Hemagglutinin Protein of Influenza A Virus

Subtype specificity of influenza A virus (IAV) is determined by its two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). For HA, 16 distinct subtypes (H1–H16) exist, while nine exist for NA. The epidemic strains of H1N1 IAV change frequently and cause annual seasonal epidemics as well as occasional pandemics, such as the notorious 1918 influenza pandemic. The recent introduction of pandemic A/H1N1 IAV (H1N1pdm virus) into humans re-emphasizes the public health concern about H1N1 IAV. Several studies have identified conserved epitopes within specific HA subtypes that can be used for diagnostics. However, immune specific epitopes in H1N1 IAV have not been completely assessed. In this study, linear epitopes on the H1N1pdm viral HA protein were identified by peptide scanning using libraries of overlapping peptides against convalescent sera from H1N1pdm patients. One epitope, P5 (aa 58–72) was found to be immunodominant in patients and to evoke high titer antibodies in mice. Multiple sequence alignments and in silico coverage analysis showed that this epitope is highly conserved in influenza H1 HA [with a coverage of 91.6% (9,860/10,767)] and almost completely absent in other subtypes [with a coverage of 3.3% (792/23,895)]. This previously unidentified linear epitope is located outside the five well-recognized antigenic sites in HA. A peptide ELISA method based on this epitope was developed and showed high correlation (χ2 = 51.81, P<0.01, Pearson correlation coefficient R = 0.741) with a hemagglutination inhibition test. The highly conserved H1 subtype-specific immunodominant epitope may form the basis for developing novel assays for sero-diagnosis and active surveillance against H1N1 IAVs

Identification of a Highly Conserved H1 Subtype-Specific Epitope with Diagnostic Potential in the Hemagglutinin Protein of Influenza A Virus

Subtype specificity of influenza A virus (IAV) is determined by its two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). For HA, 16 distinct subtypes (H1–H16) exist, while nine exist for NA. The epidemic strains of H1N1 IAV change frequently and cause annual seasonal epidemics as well as occasional pandemics, such as the notorious 1918 influenza pandemic. The recent introduction of pandemic A/H1N1 IAV (H1N1pdm virus) into humans re-emphasizes the public health concern about H1N1 IAV. Several studies have identified conserved epitopes within specific HA subtypes that can be used for diagnostics. However, immune specific epitopes in H1N1 IAV have not been completely assessed. In this study, linear epitopes on the H1N1pdm viral HA protein were identified by peptide scanning using libraries of overlapping peptides against convalescent sera from H1N1pdm patients. One epitope, P5 (aa 58–72) was found to be immunodominant in patients and to evoke high titer antibodies in mice. Multiple sequence alignments and in silico coverage analysis showed that this epitope is highly conserved in influenza H1 HA [with a coverage of 91.6% (9,860/10,767)] and almost completely absent in other subtypes [with a coverage of 3.3% (792/23,895)]. This previously unidentified linear epitope is located outside the five well-recognized antigenic sites in HA. A peptide ELISA method based on this epitope was developed and showed high correlation (χ2 = 51.81, P<0.01, Pearson correlation coefficient R = 0.741) with a hemagglutination inhibition test. The highly conserved H1 subtype-specific immunodominant epitope may form the basis for developing novel assays for sero-diagnosis and active surveillance against H1N1 IAVs

Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning

Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning

Gut microbiota in experimental murine model of Graves’ orbitopathy established in different environments may modulate clinical presentation of disease

Background Variation in induced models of autoimmunity has been attributed to the housing environment and its effect on the gut microbiota. In Graves’ disease (GD), autoantibodies to the thyrotropin receptor (TSHR) cause autoimmune hyperthyroidism. Many GD patients develop Graves’ orbitopathy or ophthalmopathy (GO) characterized by orbital tissue remodeling including adipogenesis. Murine models of GD/GO would help delineate pathogenetic mechanisms, and although several have been reported, most lack reproducibility. A model comprising immunization of female BALBc mice with a TSHR expression plasmid using in vivo electroporation was reproduced in two independent laboratories. Similar orbital disease was induced in both centers, but differences were apparent (e.g., hyperthyroidism in Center 1 but not Center 2). We hypothesized a role for the gut microbiota influencing the outcome and reproducibility of induced GO. Results We combined metataxonomics (16S rRNA gene sequencing) and traditional microbial culture of the intestinal contents from the GO murine model, to analyze the gut microbiota in the two centers. We observed significant differences in alpha and beta diversity and in the taxonomic profiles, e.g., operational taxonomic units (OTUs) from the genus Lactobacillus were more abundant in Center 2, and Bacteroides and Bifidobacterium counts were more abundant in Center 1 where we also observed a negative correlation between the OTUs of the genus Intestinimonas and TSHR autoantibodies. Traditional microbiology largely confirmed the metataxonomics data and indicated significantly higher yeast counts in Center 1 TSHR-immunized mice. We also compared the gut microbiota between immunization groups within Center 2, comprising the TSHR- or βgal control-immunized mice and naïve untreated mice. We observed a shift of the TSHR-immunized mice bacterial communities described by the beta diversity weighted Unifrac. Furthermore, we observed a significant positive correlation between the presence of Firmicutes and orbital-adipogenesis specifically in TSHR-immunized mice. Conclusions The significant differences observed in microbiota composition from BALBc mice undergoing the same immunization protocol in comparable specific-pathogen-free (SPF) units in different centers support a role for the gut microbiota in modulating the induced response. The gut microbiota might also contribute to the heterogeneity of induced response since we report potential disease-associated microbial taxonomies and correlation with ocular disease