Tuning plasticity of in-situ dendrite metallic glass composites via the dendrite-volume-fraction-dependent shear banding

This work performs a systematic investigation of identifying how the volume fraction of the in-situ dendrites affects the plasticity of metallic glass composites. The quasi-static uniaxial compressions show that the global plastic strain does not follows a linear rule-of-mixture with the dendrite volume faction, instead, a slow-fast slow enhancement behaviour is observed with increasing dendrite volume fraction. It is demonstrated that the nucleation and propagation of shear bands in these composites are dependent on the dendrite volume fraction. When the dendrite volume fraction exceeds a critical value, multiple shear bands emerge in a spherical plastic zone around a dendrite. It is further proposed that the percolation of these spherical plastic zones contributes to the fast increase in the plastic strain of the glass composites. Our findings offer important implications for the microstructural optimization of the metallic glass composites with desirable mechanical properties

Influence of quorum sensing signal molecules on biofilm formation in Proteus mirabilis O18

The influence of basis of quorum sensing molecules on Proteus strains is much less known as compared to Pseudomonas or Escherichia. We have previously shown that a series of acylated homoserine lactones (acyl-HSL) does not influence the ureolytic, proteolytic, or hemolytic abilities, and that the swarming motility of Proteus mirabilis rods is strain specific. The aim of the presented study was to find out if the presence of a series of acyl-HSL influences biofilm formation of P. mirabilis laboratory strain belonging to O18 serogroup. This serogroup is characterized by the presence of a unique non-carbohydrate component, namely phosphocholine. Escherichia coli and P. mirabilis O18 strains used in this work contains cloned plasmids encoding fluorescent protein genes with constitutive gene expression. In mixed biofilms in stationary and continuous flow conditions, P. mirabilis O18 overgrow whole culture. P. mirabilis O18 strain has genetically proved a presence of AI–2 quorum sensing system. Differences in biofilm structure were observed depending on the biofilm type and culture methods. From tested acylated homoserine lactones (BHL, HHL, OHL, DHL, dDHL, tDHL), a significant influence had BHL on thickness, structure, and the amount of exopolysaccharides produced by biofilms formed by P. mirabilis O18 pDsRed2

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data

Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about their biology. Yet, as more experiments are considered, a complex’s signature may become conditional and less identifiable. Previously we successfully distinguished the general proteomic signature of genuine chromosomal proteins from hitchhikers using the Random Forests (RF) machine learning algorithm. Here we test whether small protein complexes can define distinguishable signatures of their own, despite the assumption that machine learning needs large training sets. We show, with simulated and real proteomics data, that RF can detect small protein complexes and relationships between them. We identify several complexes in quantitative proteomics results of wild-type and knockout mitotic chromosomes. Other proteins covary strongly with these complexes, suggesting novel functional links for later study. Integrating the RF analysis for several complexes reveals known interdependences among kinetochore subunits and a novel dependence between the inner kinetochore and condensin. Ribosomal proteins, although identified, remained independent of kinetochore subcomplexes. Together these results show that this complex-oriented RF (NanoRF) approach can integrate proteomics data to uncover subtle protein relationships. Our NanoRF pipeline is available online

Trends in all cause and viral liver disease-related hospitalizations in people with hepatitis B or C: a population-based linkage study

<p>Abstract</p> <p>Background</p> <p>Previous studies have reported an excess burden of cancer and mortality in populations with chronic hepatitis B (HBV) or C (HCV), but there are limited data comparing hospitalization rates. In this study, we compared hospitalization rates for all causes and viral liver disease in people notified with HBV or HCV in New South Wales (NSW), Australia.</p> <p>Methods</p> <p>HBV and HCV notifications were linked to their hospital (July 2000-June 2006), HIV and death records. Standardized hospitalization ratios (SHRs) were calculated using rates for the NSW population. Random effects Poisson regression was used to examine temporal trends.</p> <p>Results</p> <p>The SHR for all causes and non alcoholic liver disease was two-fold higher in the HCV cohort compared with the HBV cohort (SHRs 1.4 (95%CI: 1.4-1.4) v 0.6 (95%CI: 0.6-0.6) and 14.0 (95%CI: 12.7-15.4) v 5.4 (95%CI: 4.5-6.4), respectively), whilst the opposite was seen for primary liver cancer (SHRs 16.2 (95%CI: 13.8-19.1) v 29.1 (95%CI: 24.7-34.2)). HIV co-infection doubled the SHR except for primary liver cancer in the HCV/HIV cohort. In HBV and HCV mono-infected cohorts, all cause hospitalization rates declined and primary liver cancer rates increased, whilst rates for non alcoholic liver disease increased by 9% in the HCV cohort but decreased by 14% in the HBV cohort (<it>P </it>< 0.001).</p> <p>Conclusion</p> <p>Hospital-related morbidity overall and for non alcoholic liver disease was considerably higher for HCV than HBV. Improved treatment of advanced HBV-related liver disease may explain why HBV liver-related morbidity declined. In contrast, HCV liver-related morbidity increased and improved treatments, especially for advanced liver disease, and higher levels of treatment uptake are required to reverse this trend.</p

Expression of Osteopontin in oesophageal squamous cell carcinoma

Osteopontin is a multifunctional 34 kDa extracellular matrix protein with a cell-binding domain. It is involved cell adhesion and cell migration and is therefore considered to influence tumorigenesis and/or metastasis. The purpose of the present study was to evaluate the clinical significance of Osteopontin expression in oesophageal squamous cell carcinoma (ESCC). In the present study, we immunohistochemically investigated the relationship between Osteopontin expression and clinicopathological factors including prognosis in surgical specimens of primary tumours in 175 patients with ESCC. Osteopontin was expressed in 48% of 175 patients. Osteopontin expression was significantly correlated with lymph node metastasis, lymphatic invasion, and stage (P=0.0015, 0.037 and 0.033, respectively). Tumours with expressing Osteopontin exhibited more lymph node metastasis, lymphatic invasion and advanced stage than the tumour with negative Osteopontin expression. Five-year survival rate was better in patients with negative Osteopontin expression than in those with positive Osteopontin expression (P=0.035). However, multivariate analysis revealed that Osteopontin expression was not an independent prognostic factor. As our findings suggest that Osteopontin may play an important role in progress of ESCC, the evaluation of Osteopontin expression is useful for predicting the malignant properties of ESCC

Predicting disease-associated substitution of a single amino acid by analyzing residue interactions

<p>Abstract</p> <p>Background</p> <p>The rapid accumulation of data on non-synonymous single nucleotide polymorphisms (nsSNPs, also called SAPs) should allow us to further our understanding of the underlying disease-associated mechanisms. Here, we use complex networks to study the role of an amino acid in both local and global structures and determine the extent to which disease-associated and polymorphic SAPs differ in terms of their interactions to other residues.</p> <p>Results</p> <p>We found that SAPs can be well characterized by network topological features. Mutations are probably disease-associated when they occur at a site with a high centrality value and/or high degree value in a protein structure network. We also discovered that study of the neighboring residues around a mutation site can help to determine whether the mutation is disease-related or not. We compiled a dataset from the Swiss-Prot variant pages and constructed a model to predict disease-associated SAPs based on the random forest algorithm. The values of total accuracy and MCC were 83.0% and 0.64, respectively, as determined by 5-fold cross-validation. With an independent dataset, our model achieved a total accuracy of 80.8% and MCC of 0.59, respectively.</p> <p>Conclusions</p> <p>The satisfactory performance suggests that network topological features can be used as quantification measures to determine the importance of a site on a protein, and this approach can complement existing methods for prediction of disease-associated SAPs. Moreover, the use of this method in SAP studies would help to determine the underlying linkage between SAPs and diseases through extensive investigation of mutual interactions between residues.</p

A population-based study to investigate host genetic factors associated with hepatitis B infection and pathogenesis in the Chinese population

Background Hepatitis B virus (HBV) infection is a significant public health problem that may lead to chronic liver disease, cirrhosis, and hepatocellular carcinoma (HCC). Approximately 30% of the world\u27s population has been infected with HBV and approximately 350 million (5–6%) are persistent carriers. More than 120 million Chinese are infected with HBV. The role of host genetic factors and their interactions with environmental factors leading to chronic HBV infection and its complications are not well understood. We believe that a better understanding of these factors and interactions will lead to more effective diagnostic and therapeutic options. Methods/Design This is a population-based, case-control study protocol to enroll 2200 Han Chinese from medical centers in northern and western China. Adult subjects in the following groups are being enrolled: healthy donors (n = 200), HBV infected persons achieving virus clearance (n = 400), asymptomatic HBV persistent carriers (n = 400), chronic hepatitis B cases (n = 400), decompensated liver cirrhosis with HBV infection cases (n = 400), and hepatocellular carcinoma with HBV infection cases (n = 400). In addition, for haplotype inference and quality control of sample handling and genotyping results, children of 1000 cases will be asked to provide a buccal sample for DNA extraction. With the exception of adult patients presenting with liver cirrhosis or HCC, all other cases and controls will be 40 years or older at enrollment. A questionnaire is being administered to capture dietary and environmental risk factors. Both candidate-gene and genome-wide association approaches will be used to assess the role of single genetic factors and higher order interactions with other genetic or environmental factors in HBV diseases. Conclusion This study is designed and powered to detect single gene effects as well as gene-gene and environmental-gene interactions. The identification of allelic polymorphisms in genes involved in the pathway leading to chronic viral infection, liver cirrhosis and, ultimately, hepatocellular carcinoma would provide insights to those factors leading to HBV replication, liver inflammation, fibrosis, and the carcinogenic process. An understanding of the contribution of host genetic factors and their interactions may inform public health policy, improve diagnostics and clinical management, and provide targets for drug development

Evolution and Taxonomic Classification of Human Papillomavirus 16 (HPV16)-Related Variant Genomes: HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67

Human papillomavirus 16 (HPV16) species group (alpha-9) of the Alphapapillomavirus genus contains HPV16, HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67. These HPVs account for 75% of invasive cervical cancers worldwide. Viral variants of these HPVs differ in evolutionary history and pathogenicity. Moreover, a comprehensive nomenclature system for HPV variants is lacking, limiting comparisons between studies.DNA from cervical samples previously characterized for HPV type were obtained from multiple geographic regions to screen for novel variants. The complete 8 kb genomes of 120 variants representing the major and minor lineages of the HPV16-related alpha-9 HPV types were sequenced to capture maximum viral heterogeneity. Viral evolution was characterized by constructing phylogenic trees based on complete genomes using multiple algorithms. Maximal and viral region specific divergence was calculated by global and pairwise alignments. Variant lineages were classified and named using an alphanumeric system; the prototype genome was assigned to the A lineage for all types.The range of genome-genome sequence heterogeneity varied from 0.6% for HPV35 to 2.2% for HPV52 and included 1.4% for HPV31, 1.1% for HPV33, 1.7% for HPV58 and 1.1% for HPV67. Nucleotide differences of approximately 1.0% - 10.0% and 0.5%-1.0% of the complete genomes were used to define variant lineages and sublineages, respectively. Each gene/region differs in sequence diversity, from most variable to least variable: noncoding region 1 (NCR1) /noncoding region 2 (NCR2) >upstream regulatory region (URR)> E6/E7 > E2/L2 > E1/L1.These data define maximum viral genomic heterogeneity of HPV16-related alpha-9 HPV variants. The proposed nomenclature system facilitates the comparison of variants across epidemiological studies. Sequence diversity and phylogenies of this clinically important group of HPVs provides the basis for further studies of discrete viral evolution, epidemiology, pathogenesis and preventative/therapeutic interventions