Novel, Real-Time Cell Analysis for Measuring Viral Cytopathogenesis and the Efficacy of Neutralizing Antibodies to the 2009 Influenza A (H1N1) Virus

A novel electronic cell sensor array technology, the real-time cell analysis (RTCA) system, was developed to monitor cell events. Unlike the conventional methods labeling the target cells with fluorescence, luminescence, or light absorption, the RTCA system allows for label-free detection of cell processes directly without the incorporation of labels. Here, we used this new format to measure the cytopathic effect (CPE) of the 2009 influenza A (H1N1) virus and the efficacy of neutralizing antibodies in human sera to this virus. The real-time dynamic monitoring of CPE was performed on MDCK cell cultures infected with the H1N1 virus, ranging from 5.50×102 to 5.50×107 copies/mL. The resulting CPE kinetic curves were automatically recorded and were both time and viral load dependent. The CPE kinetics were also distinguishable between different H1N1 stains, as the onset of CPE induced by the A/Shanghai/37T/2009 H1N1 virus was earlier than that of the A/Shanghai/143T/2009 H1N1 virus. Furthermore, inhibition of H1N1 virus-induced CPE in the presence of human specific anti-sera was detected and quantified using the RTCA system. Antibody titers determined using this new neutralization test correlated well with those obtained independently via the standard hemagglutination inhibition test. Taken together, this new CPE assay format provided label-free and high-throughput measurement of viral growth and the effect of neutralizing antibodies, illustrating its potential in influenza vaccine studies

Oligoasthenoteratozoospermia and Infertility in Mice Deficient for miR-34b/c and miR-449 Loci

Male fertility requires the continuous production of high quality motile spermatozoa in abundance. Alterations in all three metrics cause oligoasthenoteratozoospermia, the leading cause of human sub/infertility. Post-mitotic spermatogenesis inclusive of several meiotic stages and spermiogenesis (terminal spermatozoa differentiation) are transcriptionally inert, indicating the potential importance for the post-transcriptional microRNA (miRNA) gene-silencing pathway therein. We found the expression of miRNA generating enzyme Dicer within spermatogenesis peaks in meiosis with critical functions in spermatogenesis. In an expression screen we identified two miRNA loci of the miR-34 family (miR-34b/c and miR-449) that are specifically and highly expressed in post-mitotic male germ cells. A reduction in several miRNAs inclusive of miR-34b/c in spermatozoa has been causally associated with reduced fertility in humans. We found that deletion of both miR34b/c and miR-449 loci resulted in oligoasthenoteratozoospermia in mice. MiR-34bc/449-deficiency impairs both meiosis and the final stages of spermatozoa maturation. Analysis of miR-34bc-/-;449-/- pachytene spermatocytes revealed a small cohort of genes deregulated that were highly enriched for miR-34 family target genes. Our results identify the miR-34 family as the first functionally important miRNAs for spermatogenesis whose deregulation is causal to oligoasthenoteratozoospermia and infertility

Use of Praziquantel as an Adjuvant Enhances Protection and Tc-17 Responses to Killed H5N1 Virus Vaccine in Mice

BACKGROUND: H5N1 is a highly pathogenic influenza A virus, which can cause severe illness or even death in humans. Although the widely used killed vaccines are able to provide some protection against infection via neutralizing antibodies, cytotoxic T-lymphocyte responses that are thought to eradicate viral infections are lacking. METHODOLOGY/PRINCIPAL FINDINGS: Aiming to promote cytotoxic responses against H5N1 infection, we extended our previous finding that praziquantel (PZQ) can act as an adjuvant to induce IL-17-producing CD8(+) T cells (Tc17). We found that a single immunization of 57BL/6 mice with killed viral vaccine plus PZQ induced antigen-specific Tc17 cells, some of which also secreted IFN-γ. The induced Tc17 had cytolytic activities. Induction of these cells was impaired in CD8 knockout (KO) or IFN-γ KO mice, and was even lower in IL-17 KO mice. Importantly, the inoculation of killed vaccine with PZQ significantly reduced virus loads in the lung tissues and prolonged survival. Protection against H5N1 virus infection was obtained by adoptively transferring PZQ-primed wild type CD8(+) T cells and this was more effective than transfer of activated IFN-γ KO or IL-17 KO CD8(+) T cells. CONCLUSIONS/SIGNIFICANCE: Our results demonstrated that adding PZQ to killed H5N1 vaccine could promote broad Tc17-mediated cytotoxic T lymphocyte activity, resulting in improved control of highly pathogenic avian influenza virus infection

Enhanced hydrogen production from thermochemical processes

To alleviate the pressing problem of greenhouse gas emissions, the development and deployment of sustainable energy technologies is necessary. One potentially viable approach for replacing fossil fuels is the development of a H2 economy. Not only can H2 be used to produce heat and electricity, it is also utilised in ammonia synthesis and hydrocracking. H2 is traditionally generated from thermochemical processes such as steam reforming of hydrocarbons and the water-gas-shift (WGS) reaction. However, these processes suffer from low H2 yields owing to their reversible nature. Removing H2 with membranes and/or extracting CO2 with solid sorbents in situ can overcome these issues by shifting the component equilibrium towards enhanced H2 production via Le Chatelier's principle. This can potentially result in reduced energy consumption, smaller reactor sizes and, therefore, lower capital costs. In light of this, a significant amount of work has been conducted over the past few decades to refine these processes through the development of novel materials and complex models. Here, we critically review the most recent developments in these studies, identify possible research gaps, and offer recommendations for future research

Failure evaluation of filament wound composite risers with isotropic liner

The use of composite materials such as carbon/epoxy for the construction of deep water risers in place of metals can lead to significant weight reduction and cost savings. In order to realize this potential, a thorough understanding of the mechanical behavior and failure modes of composite risers is required. In this study, the progressive damage analysis technique and finite element simulations are used extensively to investigate the failure of composite risers. The nonlinear behavior of composites in the pre-failure stage is taken into consideration in the bimodulus-plastic model developed in this study. The inclusion of the nonlinear behavior can result in better predictions in the finite element simulations. A predictive model is also developed to determine the tensile properties of composite materials affected by moisture. The model is based on the use of additive group contributions for polymers. The tensile properties calculated using the model agreed well with experimental data. The effect of moisture on the compressive properties of composite materials is also investigated in experiments and simulations. Failure at the liner-composite interface is also considered in this study. The failure and damage mechanisms at the interface for the grooving and grit blasting mechanical surface treatment methods are investigated and discussed. The behavior and failure of the liner-composite interface are modeled successfully in finite element simulations. The local analysis of a composite riser segment using finite element simulations is demonstrated. The progressive damage analysis method is effective in predicting failure, especially for cases where damage due to accidental load has occurred.Doctor of Philosophy (MAE

Bimodulus-plastic model for pre-failure analysis of fiber reinforced polymer composites

Fiber-reinforced polymer composites, such as carbon-epoxy composites, are found to exhibit non-linear behavior when mechanically loaded in the transverse and shear directions. Experimental studies suggest that the non-linear behavior is due to two mechanisms: (i) damage in the matrix in the form of cracks and (ii) yielding of the matrix followed by plastic deformation. In this study, a bimodulus-plastic model that includes these two different damage mechanisms to simulate the non-linearity prior to failure is proposed. The pre-failure, onset of failure and post-failure analysis with the proposed model is discussed in detail with emphasis put on the transverse and shear components. The process of determining the material properties and parameters required for defining the new model is discussed and demonstrated. The newly developed model is then validated against the experimental results from three-point flexure tests on the composites. The correlation was good showing that the proposed model was able to simulate accurately the non-linear behavior of the composites and thus predict the failure. Finally, the model is applied to a case study on the failure of a composite riser under internal pressure loads.Accepted versio

Interfacial bonding between CFRP and mechanically-treated aluminum liner surfaces for risers

The bonding between metal and carbon fiber-reinforced polymer (CFRP) composites is important in structures such as composite risers. Surface treatment of the metal is required to improve the metal-composite bonding. In this study, the effects of two mechanical surface treatment methods on the bonding between carbon/epoxy composites and aluminum are studied. The treatment methods investigated are grit blasting and grooving. Mechanical tests are performed and the test results are used with finite element simulations to study the failure and damage mechanisms at the composite-metal interface. The mechanical response and damage propagation at the metal-composite interface are modeled successfully using surface-based cohesive behavior. The finite element simulations gave insight into the way that the grooving treatment method improved the composite-metal bonding.Accepted versio

Recent Advances on the Design Automation for Performance-Optimized Fiber Reinforced Polymer Composite Components

Advanced manufacturing techniques, such as automated fiber placement and additive manufacturing enables the fabrication of fiber-reinforced polymer composite components with customized material and structural configurations. In order to take advantage of this customizability, the design process for fiber-reinforced polymer composite components needs to be improved. Machine learning methods have been identified as potential techniques capable of handling the complexity of the design problem. In this review, the applications of machine learning methods in various aspects of structural component design are discussed. They include studies on microstructure-based material design, applications of machine learning models in stress analysis, and topology optimization of fiber-reinforced polymer composites. A design automation framework for performance-optimized fiber-reinforced polymer composite components is also proposed. The proposed framework aims to provide a comprehensive and efficient approach for the design and optimization of fiber-reinforced polymer composite components. The challenges in building the models required for the proposed framework are also discussed briefly