Eph receptors and their ligands : promising molecular biomarkers and therapeutic targets in prostate cancer

Although at present, there is a high incidence of prostate cancer, particularly in the Western world, mortality from this disease is declining and occurs primarily only from clinically significant late stage tumors with a poor prognosis. A major current focus of this field is the identification of new biomarkers which can detect earlier, and more effectively, clinically significant tumors from those deemed “low risk”, as well as predict the prognostic course of a particular cancer. This strategy can in turn offer novel avenues for targeted therapies. The large family of Receptor Tyrosine Kinases, the Ephs, and their binding partners, the ephrins, has been implicated in many cancers of epithelial origin through stimulation of oncogenic transformation, tumor angiogenesis, and promotion of increased cell survival, invasion and migration. They also show promise as both biomarkers of diagnostic and prognostic value and as targeted therapies in cancer. This review will briefly discuss the complex roles and biological mechanisms of action of these receptors and ligands and, with regard to prostate cancer, highlight their potential as biomarkers for both diagnosis and prognosis, their application as imaging agents, and current approaches to assessing them as therapeutic targets. This review demonstrates the need for future studies into those particular family members that will prove helpful in understanding the biology and potential as targets for treatment of prostate cancer.

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

A simulation-based large deflection and inelastic analysis of steel frames under fire

This paper presents an accurate and robust geometric and material nonlinear formulation to predict structural behaviour of unprotected steel members at elevated temperatures. A fire analysis including large displacement effects for frame structures is presented. This finite element formulation of beam-column elements is based on the plastic hinge approach to model the elasto-plastic strain-hardening material behaviour. The Newton-Raphson method allowing for the thermal-time dependent effect was employed for the solution of the non-linear governing equations for large deflection in thermal history. A combined incremental and total formulation for determining member resistance is employed in this nonlinear solution procedure for the efficient modeling of nonlinear effects. Degradation of material strength with increasing temperature is simulated by a set of temperature-stress-strain curves according to both ECCS and BS5950 Part 8, which implicitly allows for creep deformation. The effects of uniform or non-uniform temperature distribution over the section of the structural steel member are also considered. Several numerical and experimental verifications are presented.

Strategies and challenges for systematically mapping biologically significant molecular pathways regulating carcinoma epithelial-mesenchymal transition

Enormous progress has been made towards understanding the role of specific factors in the process of epithelial-mesenchymal transition (EMT); however, the complex underlying pathways and the transient nature of the transition continues to present significant challenges. Targeting tumour cell plasticity underpinning EMT is an attractive strategy to combat metastasis. Global gene expression profiling and high-content analyses are among the strategies employed to identify novel EMT regulators. In this review, we highlight several approaches to systematically interrogate key pathways involved in EMT, with particular emphasis on the features of multiparametric, high-content imaging screening strategies that lend themselves to the systematic discovery of highly significant modulators of tumour cell plasticity.

Blast response of reinforced concrete pile using fully coupled computer simulation techniques

Pile foundations transfer loads from superstructures to stronger sub soil. Their strength and stability can hence affect structural safety. This paper treats the response of reinforced concrete pile in saturated sand to a buried explosion. Fully coupled computer simulation techniques are used together with five different material models. Influence of reinforcement on pile response is investigated and important safety parameters of horizontal deformations and tensile stresses in the pile are evaluated. Results indicate that adequate longitudinal reinforcement and proper detailing of transverse reinforcement can reduce pile damage. Present findings can serve as a benchmark reference for future analysis and design.

Molecular mechanisms of cisplatin resistance in lung cancer

Cisplatin is one of the most potent anticancer agents, displaying significant clinical activity against a variety of solid tumours. To date, cisplatin-based combination treatment remains the most effective systemic chemotherapy for non-small cell lung cancer (NSCLC) patients. Unfortunately, the outcome of cisplatin therapy in NSCLC has reached a plateau due to the development of both intrinsic and acquired resistance that have become a major obstacle in the use of cisplatin in the clinical setting. The molecular mechanisms that underlie chemoresistance are largely unknown. Mechanisms of acquired resistance to cisplatin include reduced intracellular accumulation of the drug, enhanced drug inactivation by metallothionine and glutathione, increased repair activity of DNA damage, and altered expression of oncogenes and regulatory proteins. Cisplatin-induced cytotoxicity is mediated through the induction of apoptosis and cell cycle arrest as a result of cisplatin-DNA adduct formation, which in turn, activates multiple signaling pathways and mediators. These include p53, Bcl-2 family, caspases, cyclins, CDKs, MAPK and PI3K/Akt. Increased expression of anti-apoptotic genes and mutations in the intrinsic apoptotic pathway may also contribute to the inability of cells to detect DNA damage or to induce apoptosis. This chapter will provide an insight into the mechanisms involved in cisplatin resistance and a better understanding of the molecular basis of the cellular response to cisplatin-based chemotherapy in lung cancer.

Process modelling and simulation of tissue damage during mechanical peeling of pumpkin as a tough skinned vegetable

Food waste is a current challenge that both developing and developed countries face. This project applied a novel combination of available methods in Mechanical, agricultural and food engineering to address these challenges. A systematic approach was devised to investigate possibilities of reducing food waste and increasing the efficiency of industry by applying engineering concepts and theories including experimental, mathematical and computational modelling methods. This study highlights the impact of comprehensive understanding of agricultural and food material response to the mechanical operations and its direct relation to the volume of food wasted globally.

A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

Molecular characterization of "Candidatus Parilichlamydia carangidicola," a novel Chlamydia-like epitheliocystis agent in yellowtail kingfish, Seriola lalandi (Valenciennes), and the proposal of a new family, "Candidatus Parilichlamydiaceae" fam. nov. (order Chlamydiales).

Three cohorts of farmed yellowtail kingfish (Seriola lalandi) from South Australia were examined for Chlamydia-like organisms associated with epitheliocystis. To characterize the bacteria, 38 gill samples were processed for histopathology, electron microscopy, and 16S rRNA amplification, sequencing, and phylogenetic analysis. Microscopically, the presence of membrane-enclosed cysts was observed within the gill lamellae. Also observed was hyperplasia of the epithelial cells with cytoplasmic vacuolization and fusion of the gill lamellae. Transmission electron microscopy revealed morphological features of the reticulate and intermediate bodies typical of members of the order Chlamydiales. A novel 1,393-bp 16S chlamydial rRNA sequence was amplified from gill DNA extracted from fish in all cohorts over a 3-year period that corresponded to the 16S rRNA sequence amplified directly from laser-dissected cysts. This sequence was only 87% similar to the reported "Candidatus Piscichlamydia salmonis" (AY462244) from Atlantic salmon and Arctic charr. Phylogenetic analysis of this sequence against 35 Chlamydia and Chlamydia-like bacteria revealed that this novel bacterium belongs to an undescribed family lineage in the order Chlamydiales. Based on these observations, we propose this bacterium of yellowtail kingfish be known as "Candidatus Parilichlamydia carangidicola" and that the new family be known as "Candidatus Parilichlamydiaceae."

Molecular characterization of "Candidatus Similichlamydia latridicola" gen. nov., sp. nov. (Chlamydiales: "Candidatus Parilichlamydiaceae"), a novel Chlamydia-like epitheliocystis agent in the striped trumpeter, Latris lineata (Forster)

Histological analysis of gill samples taken from individuals of Latris lineata reared in aquaculture in Tasmania, Australia, and those sampled from the wild revealed the presence of epitheliocystis-like basophilic inclusions. Subsequent morphological, in situ hybridization, and molecular analyses were performed to confirm the presence of this disease and discovered a Chlamydia-like organism associated with this condition, and the criteria set by Fredericks and Relman's postulates were used to establish disease causation. Three distinct 16S rRNA genotypes were sequenced from 16 fish, and phylogenetic analyses of the nearly full-length 16S rRNA sequences generated for this bacterial agent indicated that they were nearly identical novel members of the order Chlamydiales. This new taxon formed a well-supported clade with "Candidatus Parilichlamydia carangidicola" from the yellowtail kingfish (Seriola lalandi). On the basis of sequence divergence over the 16S rRNA region relative to all other members of the order Chlamydiales, a new genus and species are proposed here for the Chlamydia-like bacterium from L. lineata, i.e., "Candidatus Similichlamydia latridicola" gen. nov., sp. nov.

Multilocus sequence analysis provides insights into molecular epidemiology of Chlamydia pecorum infections in Australian sheep, cattle and koalas

Chlamydia pecorum is a significant pathogen of domestic livestock and wildlife. We have developed a C. pecorum-specific multilocus sequence analysis (MLSA) scheme to examine the genetic diversity of and relationships between Australian sheep, cattle, and koala isolates. An MLSA of seven concatenated housekeeping gene fragments was performed using 35 isolates, including 18 livestock isolates (11 Australian sheep, one Australian cow, and six U.S. livestock isolates) and 17 Australian koala isolates. Phylogenetic analyses showed that the koala isolates formed a distinct clade, with limited clustering with C. pecorum isolates from Australian sheep. We identified 11 MLSA sequence types (STs) among Australian C. pecorum isolates, 10 of them novel, with koala and sheep sharing at least one identical ST (designated ST2013Aa). ST23, previously identified in global C. pecorum livestock isolates, was observed here in a subset of Australian bovine and sheep isolates. Most notably, ST23 was found in association with multiple disease states and hosts, providing insights into the transmission of this pathogen between livestock hosts. The complexity of the epidemiology of this disease was further highlighted by the observation that at least two examples of sheep were infected with different C. pecorum STs in the eyes and gastrointestinal tract. We have demonstrated the feasibility of our MLSA scheme for understanding the host relationship that exists between Australian C. pecorum strains and provide the first molecular epidemiological data on infections in Australian livestock hosts.

Mechanism based emulation of dynamic simulation models : concept and application in hydrology

Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.

Improved molecular tools for sugar cane biotechnology

Sugar cane is a major source of food and fuel worldwide. Biotechnology has the potential to improve economically-important traits in sugar cane as well as diversify sugar cane beyond traditional applications such as sucrose production. High levels of transgene expression are key to the success of improving crops through biotechnology. Here we describe new molecular tools that both expand and improve gene expression capabilities in sugar cane. We have identified promoters that can be used to drive high levels of gene expression in the leaf and stem of transgenic sugar cane. One of these promoters, derived from the Cestrum yellow leaf curling virus, drives levels of constitutive transgene expression that are significantly higher than those achieved by the historical benchmark maize polyubiquitin-1 (Zm-Ubi1) promoter. A second promoter, the maize phosphonenolpyruvate carboxylate promoter, was found to be a strong, leaf-preferred promoter that enables levels of expression comparable to Zm-Ubi1 in this organ. Transgene expression was increased approximately 50-fold by gene modification, which included optimising the codon usage of the coding sequence to better suit sugar cane. We also describe a novel dual transcriptional enhancer that increased gene expression from different promoters, boosting expression from Zm-Ubi1 over eightfold. These molecular tools will be extremely valuable for the improvement of sugar cane through biotechnology.