Muramidases found in the foregut microbiome of the Tammar wallaby can direct cell aggregation and biofilm formation

We describe here the role of muramidases present in clones of metagenomic DNA that result in cell aggregation and biofilm formation by Escherichia coli. The metagenomic clones were obtained from uncultured Lachnospiraceae-affiliated bacteria resident in the foregut microbiome of the Tammar wallaby. One of these fosmid clones (p49C2) was chosen for more detailed studies and a variety of genetic methods were used to delimit the region responsible for the phenotype to an open reading frame of 1425 bp. Comparative sequence analysis with other fosmid clones giving rise to the same phenotype revealed the presence of muramidase homologues with the same modular composition. Phylogenetic analysis of the fosmid sequence data assigned these fosmid inserts to recently identified, but uncultured, phylogroups of Lachnospiraceae believed to be numerically dominant in the foregut microbiome of the Tammar wallaby. The muramidase is a modular protein containing putative N-acetylmuramoyl--alanine amidase and an endo-β-N-acetylglucosaminidase catalytic module, with a similar organization and functional properties to some Staphylococcal autolysins that also confer adhesive properties and biofilm formation. We also show here that the cloned muramidases result in the production of extracellular DNA, which appears to be the key for biofilm formation and autoaggregation. Collectively, these findings suggest that biofilm formation and cell aggregation in gut microbiomes might occur via the concerted action of carbohydrate-active enzymes and the production of extracellular DNA to serve as a biofilm scaffold.

Rapid analysis of GSTM1, GSTT1 and GSTP1 polymorphisms using real-time polymerase chain reaction

Polymorphisms of glutathione transferases (GST) are important genetic determinants of susceptibility to environmental carcinogens (Rebbeck, 1997). The GSTs are a multigene family of dimeric enzymes involved in detoxification, and, in a few cases, the bioactivation of a variety of xenobiotics (Hayes et al., 1995). The cytosolic GST enzyme family consists of four major classes of enzymes, referred to as alpha, mu, pi and theta. Several members of this family (for example, GSTM1, GSTT1 and GSTP1) are polymorphic in human populations (Wormhoudt et al., 1999). Molecular epidemiology studies have examined the role of GST polymorphisms as susceptibility factors for environmentally and/or occupationally induced cancers (Wormhoudt et al., 1999). In particular, case-control studies showed a relationship between the GSTM1 null genotype and the development of cancer in association with smoking habits, which has been shown for cancers of the respiratory and gastrointestinal tracts as well as other cancer types (Miller et al., 1997). Only a few molecular epidemiological studies addressed the role of GSTT1 and GSTP1 polymorphisms in cancer susceptibility. Since GSTP1 is a key player in biotransformation/bioactivation of benzo(a)pyrene, GSTP1 may be even more important than GSTM1 in the prevention of tobacco-induced cancers (Harries et al., 1997; Harris et al., 1998). To date, this relationship has not been sufficiently addressed in humans. Comprehensive molecular epidemiological studies may add to the current knowledge of the role of GST polymorphisms in cancer susceptibility and extent of the knowledge gained from approaches that used phenotyping, such as GSTM1 activity as it relates to trans-stilbene oxide, or polymerase chain reaction (PCR) based genotyping of polymorphic isoenzymes (Bell et al., 1993; Pemble et al., 1994; Harries et al., 1997).

Determination of urinary thymidine glycol using affinity chromatography, HPLC and post-column reaction detection : a biomarker of oxidative DNA damage upon kidney transplantation

Reactive oxygen species are generated during ischaemia-reperfusion of tissue. Oxidation of thymidine by hydroxyl radicals (HO) leads to the formation of 5,6-dihydroxy-5,6-dihydrothymidine (thymidine glycol). Thymidine glycol is excreted in urine and can be used as biomarker of oxidative DNA damage. Time dependent changes in urinary excretion rates of thymidine glycol were determined in six patients after kidney transplantation and in six healthy controls. A new analytical method was developed involving affinity chromatography and subsequent reverse-phase high-performance liquid chromatography (RP-HPLC) with a post-column chemical reaction detector and endpoint fluorescence detection. The detection limit of this fluorimetric assay was 1.6 ng thymidine glycol per ml urine, which corresponds to about half of the physiological excretion level in healthy control persons. After kidney transplantation the urinary excretion rate of thymidine glycol increased gradually reaching a maximum around 48 h. The excretion rate remained elevated until the end of the observation period of 10 days. Severe proteinuria with an excretion rate of up to 7.2 g of total protein per mmol creatinine was also observed immediately after transplantation and declined within the first 24 h of allograft function (0.35 + 0.26 g/mmol creatinine). The protein excretion pattern, based on separation of urinary proteins on sodium dodecyl sulphate-polyacrylamide gel electrophorosis (SDS-PAGE), as well as excretion of individual biomarker proteins, indicated nonselective glomerular and tubular damage. The increased excretion of thymidine glycol after kidney transplantation may be explained by ischaemia-reperfusion induced oxidative DNA damage of the transplanted kidney.

Canards in advection-reaction-diffusion systems in one spatial dimension

This thesis contains a mathematical investigation of the existence of travelling wave solutions to singularly perturbed advection-reaction-diffusion models of biological processes. An enhanced mathematical understanding of these solutions and models is gained via the identification of canards (special solutions of fast/slow dynamical systems) and their role in the existence of the most biologically relevant, shock-like solutions. The analysis focuses on two existing models. A new proof of existence of a whole family of travelling waves is provided for a model describing malignant tumour invasion, while new solutions are identified for a model describing wound healing angiogenesis.

Resolving the conflicts of sustainable world heritage landscapes in cities : fully open or limited access for visitors?

World Heritage Landscapes (WHLs) are receiving increased attention from researchers, urban planners, managers, and policy makers and many heritage values and resources are becoming irreversibly lost. This phenomenon is especially prominent for WHLs located in cities, where greater development opportunities are involved. Decision making for sustainable urban landscape planning, conservation and management of WHLs often takes place from an economic perspective, especially in developing countries. This, together with the uncertain source of funding to cover WHL operating and maintenance costs, has resulted in many urban managers seeking private sector funding either in the form of visitor access fees or leasing part of the site for high-rental facilities such as five star hotels, clubs and expensive restaurants. For the former, this can result in low-income urban citizens being unable to afford the access fees and hence contradicting the principle of equal access for all; while, for the latter, the principle of open access for all is equally violated. To resolve this conflict, a game model is developed to determine how urban managers should allocate WHL spaces to maximize the combination of economic, social and ecological benefits and cultural values. A case study is provided of the Hangzhou's West Lake Scenic Area, a WHL located at the centre of Hangzhou city, in which several high-rental facilities have recently been closed down by the local authorities due to charges of elitism and misuse of public funds by government officials. The result shows that the best solution is to lease a small space with high rents and leave the remainder of the site to the public. This solution is likely to be applicable only in cities with a strong economy.

In-plane graphene/boron-nitride heterostructure as efficient metal-free electrocatalyst for the oxygen reduction reaction

Exploiting metal-free catalysts for the oxygen reduction reaction (ORR) and understanding their catalytic mechanisms are vital for the development of fuel cells (FCs). Our study has demonstrated that in-plane heterostructures of graphene and boron nitride (G/BN) can serve as an efficient metal-free catalyst for the ORR, in which the C-N interfaces of G/BN heterostructures act as reactive sites. The formation of water at the heterointerface is both energetically and kinetically favorable via a fourelectron pathway. Moreover, the water formed can be easily released from the heterointerface, and the catalytically active sites can be regenerated for the next reaction. Since G/BN heterostructures with controlled domain sizes have been successfully synthesized in recent reports (e.g. Nat. Nanotechnol., 2013, 8, 119), our results highlight the great potential of such heterostructures as a promising metal-free catalyst for ORR in FCs.

The chain reaction

Synopsis and review of the Australian feature film The Chain Reaction, directed by Ian Barry.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

A Crank--Nicolson ADI spectral method for a two-dimensional riesz space fractional nonlinear reaction-diffusion equation

In this paper, a new alternating direction implicit Galerkin--Legendre spectral method for the two-dimensional Riesz space fractional nonlinear reaction-diffusion equation is developed. The temporal component is discretized by the Crank--Nicolson method. The detailed implementation of the method is presented. The stability and convergence analysis is strictly proven, which shows that the derived method is stable and convergent of order $2$ in time. An optimal error estimate in space is also obtained by introducing a new orthogonal projector. The present method is extended to solve the fractional FitzHugh--Nagumo model. Numerical results are provided to verify the theoretical analysis.

Limitations of a laboratory scale model in predicting optimal pilot scale conditions for dilute acid pretreatment of sugarcane bagasse

Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

Charge mediated semiconducting-to-metallic phase transition in molybdenum disulphide monolayer and hydrogen evolution reaction in New 1T’ phase

The phase transition of single layer molybdenum disulphide (MoS2) from semi-conducting 2H to metallic 1T and then to 1T' phases, and the effect of the phase transition on hydrogen evolution reaction (HER) are investigated within this work by density functional theory. Experimentally, 2H-MoS2 has been widely used as an excellent electrode for HER and can get charged easily. Here we find that the negative charge has a significant impact on the structural phase transition in a MoS2 monolayer. The thermodynamic stability of 1T-MoS2 increases with the negative charge state, comparing with the 2H-MoS2 structure before phase transition and the kinetic energy barrier for a phase transition from 2H to 1T decreases from 1.59 eV to 0.27 eV when 4 e- are injected per MoS2 unit. Additionally, 1T phase is found to transform into the distorted structure (1T' phase) spontaneously. On their activity toward hydrogen evolution reaction, 1T'-MoS2 structure hydrogen coverage shows comparable hydrogen evolution reaction activity to the 2H-MoS2 structure. If the charge transfer kinetics is taken into account, the catalytic activity of 1T'-MoS2 is superior to that of 2H-MoS2. Our finding provides a possible novel method for phase transition of MoS2, and enriches understanding of the catalytic properties of MoS2 for HER.

Numerical treatment of a two-dimensional variable-order fractional nonlinear reaction-diffusion model

A two-dimensional variable-order fractional nonlinear reaction-diffusion model is considered. A second-order spatial accurate semi-implicit alternating direction method for a two-dimensional variable-order fractional nonlinear reaction-diffusion model is proposed. Stability and convergence of the semi-implicit alternating direct method are established. Finally, some numerical examples are given to support our theoretical analysis. These numerical techniques can be used to simulate a two-dimensional variable order fractional FitzHugh-Nagumo model in a rectangular domain. This type of model can be used to describe how electrical currents flow through the heart, controlling its contractions, and are used to ascertain the effects of certain drugs designed to treat arrhythmia.

A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.