999 resultados para Human norovirus


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Insulin receptor (IR) signaling is critical to controlling nutrient uptake and metabolism. However, only a low-resolution (3.8 Å) structure currently exists for the IR ectodomain, with some segments ill-defined or unmodeled due to disorder. Here, we revise this structure using new diffraction data to 3.3 Å resolution that allow improved modeling of the N-linked glycans, the first and third fibronectin type III domains, and the insert domain. A novel haptic interactive molecular dynamics strategy was used to aid fitting to low-resolution electron density maps. The resulting model provides a foundation for investigation of structural transitions in IR upon ligand binding.

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The paper presents an innovative approach to modelling the causal relationships of human errors in rail crack incidents (RCI) from a managerial perspective. A Bayesian belief network is developed to model RCI by considering the human errors of designers, manufactures, operators and maintainers (DMOM) and the causal relationships involved. A set of dependent variables whose combinations express the relevant functions performed by each DMOM participant is used to model the causal relationships. A total of 14 RCI on Hong Kong’s mass transit railway (MTR) from 2008 to 2011 are used to illustrate the application of the model. Bayesian inference is used to conduct an importance analysis to assess the impact of the participants’ errors. Sensitivity analysis is then employed to gauge the effect the increased probability of occurrence of human errors on RCI. Finally, strategies for human error identification and mitigation of RCI are proposed. The identification of ability of maintainer in the case study as the most important factor influencing the probability of RCI implies the priority need to strengthen the maintenance management of the MTR system and that improving the inspection ability of the maintainer is likely to be an effective strategy for RCI risk mitigation.

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Currently, there are nine known human herpesviruses and these viruses appear to have been a very common companion of humans throughout the millenia. Of human herpesviruses, herpes simplex viruses 1 and 2 (HSV-1, HSV-2), causative agents of herpes labialis and genital herpes, and varicella-zoster virus (VZV), causative agent of chicken pox, are also common causes of central nervous system (CNS) infections. In addition, human cytomegalovirus (CMV), Epstein-Barr virus (EBV) and human herpesviruses 6A, 6B, and 7 (HHV-6A, HHV-6B, HHV-7), all members of the herpesvirus family, can also be associated with encephalitis and meningitis. Accurate diagnostics and fast treatment are essential for patient recovery in CNS infections and therefore sensitive and effective diagnostic methods are needed. The aim of this thesis was to develop new potential detection methods for diagnosing of human herpesvirus infections, especially in immunocompetent patients, using the microarray technique. Therefore, methods based on microarrays were developed for simultaneous detection of HSV-1, HSV-2, VZV, CMV, EBV, HHV-6A, HHV-6B, and HHV-7 nucleic acids, and for HSV-1, HSV-2, VZV, and CMV antibodies from various clinical samples. The microarray methods developed showed potential for efficiently and accurately detecting human herpesvirus DNAs, especially in CNS infections, and for simultaneous detection of DNAs or antibodies for multiple different human herpesviruses from clinical samples. In fact, the microarray method revealed several previously unrecognized co-infections. The microarray methods developed were sensitive and provided rapid detection of human herpesvirus DNA, and therefore the method could be applied to routine diagnostics. The microarrays might also be considered as an economical tool for diagnosing human herpesvirus infections.

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This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

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Three overlapping assembled epitopes of beta hCG have been mapped using MAb probes and a single step solid phase radioimmunoassay. These epitopes have been shown to be at receptor binding region comprising of the loop region beta Cys93-Cys100. Importance of disulphide bonds in maintaining integrity of these epitopes is assessed. Two MAbs (INN 58 and INN 22) interact with the beta region as well as the alpha C-terminal peptide, while the other MAb INN 24 interacts with only the beta region. Cross-reactivity pattern with beta hCG and hLH as web as the reported crystal structure of hCG substantiates the epitope identification. The results demonstrate utility of MAbs as probes in investigations on three-dimensional structure of gonadatropins.

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Ambient temperature is one of the basic parameters characterising human comfort: are we too hot, too cold, or just right? The impact of temperature goes beyond comfort: inadequate temperature and temperature variations have consequences on human health, as the increasing numbers of studies have demonstrated. The topic is of particular significance at the times when climate change shifts the traditional – as we know them- temperature zones, and brings much wider temperature variations. For these reasons the impact of temperature on health has been one of the most popular topics among the articles submitted and published in Science of the Total Environment over the last few years. This Virtual Special Issue compiles 18 articles published in our journal on this topic since 2012. It is worth briefly summarizing the rich scientific insights brought by these articles, as well as broader considerations, particularly those extending to management, discussed by the authors of the articles.

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In this thesis, the genetic variation of human populations from the Baltic Sea region was studied in order to elucidate population history as well as evolutionary adaptation in this region. The study provided novel understanding of how the complex population level processes of migration, genetic drift, and natural selection have shaped genetic variation in North European populations. Results from genome-wide, mitochondrial DNA and Y-chromosomal analyses suggested that the genetic background of the populations of the Baltic Sea region lies predominantly in Continental Europe, which is consistent with earlier studies and archaeological evidence. The late settlement of Fennoscandia after the Ice Age and the subsequent small population size have led to pronounced genetic drift, especially in Finland and Karelia but also in Sweden, evident especially in genome-wide and Y-chromosomal analyses. Consequently, these populations show striking genetic differentiation, as opposed to much more homogeneous pattern of variation in Central European populations. Additionally, the eastern side of the Baltic Sea was observed to have experienced eastern influence in the genome-wide data as well as in mitochondrial DNA and Y-chromosomal variation – consistent with linguistic connections. However, Slavic influence in the Baltic Sea populations appears minor on genetic level. While the genetic diversity of the Finnish population overall was low, genome-wide and Y-chromosomal results showed pronounced regional differences. The genetic distance between Western and Eastern Finland was larger than for many geographically distant population pairs, and provinces also showed genetic differences. This is probably mainly due to the late settlement of Eastern Finland and local isolation, although differences in ancestral migration waves may contribute to this, too. In contrast, mitochondrial DNA and Y-chromosomal analyses of the contemporary Swedish population revealed a much less pronounced population structure and a fusion of the traces of ancient admixture, genetic drift, and recent immigration. Genome-wide datasets also provide a resource for studying the adaptive evolution of human populations. This study revealed tens of loci with strong signs of recent positive selection in Northern Europe. These results provide interesting targets for future research on evolutionary adaptation, and may be important for understanding the background of disease-causing variants in human populations.

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Plasma phospholipid transfer protein (PLTP) plays a crucial role in high-density lipoprotein (HDL) metabolism and reverse cholesterol transport (RCT). It mediates the generation of pre-beta-HDL particles, enhances the cholesterol efflux from peripheral cells to pre-beta-HDL, and metabolically maintains the plasma HDL levels by facilitating the transfer of post-lipolytic surface remnants of triglyceride-rich lipoproteins to HDL. In addition to the antiatherogenic properties, recent findings indicate that PLTP has also proatherogenic characteristics, and that these opposite characteristics of PLTP are dependent on the site of PLTP expression and action. In human plasma, PLTP exists in a high-activity (HA-PLTP) and a low-activity form (LA-PLTP), which are associated with macromolecular complexes of different size and composition. The aims of this thesis were to isolate the two PLTP forms from human plasma, to characterize the molecular complexes in which the HA- and LA-PLTP reside, and to study the interactions of the PLTP forms with apolipoproteins (apo) and the ability of apolipoproteins to regulate PLTP activity. In addition, we aimed to study the distribution of the two PLTP forms in a Finnish population sample as well as to find possible regulatory factors for PLTP by investigating the influence of lipid and glucose metabolism on the balance between the HA- and LA-PLTP. For these purposes, an enzyme-linked immunosorbent assay (ELISA) capable of determining the serum total PLTP concentration and quantitating the two PLTP forms separately was developed. In this thesis, it was demonstrated that the HA-PLTP isolated from human plasma copurified with apoE, whereas the LA-PLTP formed a complex with apoA-I. The separation of these two PLTP forms was carried out by a dextran sulfate (DxSO4)-CaCl2 precipitation of plasma samples before the mass determination. A similar immunoreactivity of the two PLTP forms in the ELISA could be reached after a partial sample denaturation by SDS. Among normolipidemic Finnish individuals, the mean PLTP mass was 6.6 +/- 1.5 mg/l and the mean PLTP activity 6.6 +/- 1.7 umol/ml/h. Of the serum PLTP concentration, almost 50% represented HA-PLTP. The results indicate that plasma HDL levels could regulate PLTP concentration, while PLTP activity could be regulated by plasma triglyceride-rich very low-density lipoprotein (VLDL) concentration. Furthermore, new evidence is presented that PLTP could also play a role in glucose metabolism. Finally, both PLTP forms were found to interact with apoA-I, apoA-IV, and apoE. In addition, both apoE and apoA-IV, but not apoA-I, were capable of activating the LA-PLTP. These findings suggest that the distribution of the HA- and LA-PLTP in human plasma is subject to dynamic regulation by apolipoproteins.