Insights into a multidrug resistant Escherichia coli pathogen of the globally disseminated ST131 lineage : genome analysis and virulence mechanisms

Escherichia coli strains causing urinary tract infection (UTI) are increasingly recognized as belonging to specific clones. E. coli clone O25b:H4-ST131 has recently emerged globally as a leading multi-drug resistant pathogen causing urinary tract and bloodstream infections in hospitals and the community. While most molecular studies to date examine the mechanisms conferring multi-drug resistance in E. coli ST131, relatively little is known about their virulence potential. Here we examined E. coli ST131 clinical isolates from two geographically diverse collections, one representing the major pathogenic lineages causing UTI across the United Kingdom and a second representing UTI isolates from patients presenting at two large hospitals in Australia. We determined a draft genome sequence for one representative isolate, E. coli EC958, which produced CTX-M-15 extended-spectrum β-lactamase, CMY-23 type AmpC cephalosporinase and was resistant to ciprofloxacin. Comparative genome analysis indicated that EC958 encodes virulence genes commonly associated with uropathogenic E. coli (UPEC). The genome sequence of EC958 revealed a transposon insertion in the fimB gene encoding the activator of type 1 fimbriae, an important UPEC bladder colonization factor. We identified the same fimB transposon insertion in 59% of the ST131 UK isolates, as well as 71% of ST131 isolates from Australia, suggesting this mutation is common among E. coli ST131 strains. Insertional inactivation of fimB resulted in a phenotype resembling a slower off-to-on switching for type 1 fimbriae. Type 1 fimbriae expression could still be induced in fimB-null isolates; this correlated strongly with adherence to and invasion of human bladder cells and bladder colonisation in a mouse UTI model. We conclude that E. coli ST131 is a geographically widespread, antibiotic resistant clone that has the capacity to produce numerous virulence factors associated with UTI.

Conjugation of carcinogens by 6 class glutathione S-transferases : mechanisms and relevance to variations in human risk

Conjugation of chemicals with glutathione (GSH) can lead to decreased or increased toxicity. A genetic deficiency in the GSH S-transferase μ class gene M1 has been hypothesized to lead to greater risk of lung cancer in smokers. Recently a gene deletion polymorphism involving the human θ enzyme T1 has been described; the enzyme is present in erythrocytes and can be readily assayed. A rat θ class enzyme, 5-5, has structural and catalytic similarity and the protein was expressed in the Salmonella typhimurium tester strain TA1535. Expression of the cDNA vector increased the mutagenicity of ethylene dibromide and several methylene dihalides. Mutations resulting from the known GSH S-transferase substrate 1,2-epoxy-3-(4′nitrophenoxy)propane were decreased in the presence of the transferase. Expression of transferase 5-5 increased mutations when 1,2,3,4-diepoxybutane (butadiene diepoxide), 4-bromo-1,2-epoxybutane, or 1,3-dichloracetone were added. The latter compound is a model for the putative 1,2-dibromo-3-chloropropane oxidation product 1-bromo-3-chloroacetone. These genotoxicity and genotyping assays may be of use in further studies of the roles of GSH S-transferase θ enzymes in bioactivation and detoxication and any changes in risk due to polymorphism.

Detecting approximate clones in business process model repositories

Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.

A high and low fear phenotype mouse model

Fear-related illnesses such as post-traumatic stress disorder (PTSD) impose a tremendous burden on individual quality of life, families, and the national economy. In the military population, 17-20% of services members returning from deployment are diagnosed with PTSD. While treatments have improved for PTSD and are helpful for some, many people continue to suffer despite therapy. The aim of this research is to examine fear memory behaviourally and at the cellular level in the amygdala by using a unique inter-cross strain of high and low fear phenotype mice. An extended outcross C57BL/6J x DBA/2J (F8) are selected for high or low Pavlovian fear memory to context and cue. On presentation of either the original learning context or the cue (tone) mice display high or low levels of freezing as a behavioural measure of fear. In order to identify key aspects of the cellular basis of this difference in fear memory behaviour we are making measurements of protein levels and neuron numbers of a known pathway involved in the consolidation of a long term fear memory (pMAPK). Ongoing studies aim to determine if high fear behaviour is associated with differential signalling in the lateral amygdala compared to low fear behaviour. Additionally, by blocking this pathway in the lateral amygdala (LA), we aim to reduce fear behaviour following Pavlovian fear conditioning. This research will help to unravel the cellular mechanisms underlying high fear behaviour and advance the field toward targeted treatment and improved outcomes, ultimately improving human quality of life.

Toward a model for forming psychological safety climate in construction project management

The nature of construction projects and their delivery exposes participants to accidents and dangers. Safety climate serves as a frame of reference for employees to make sense of safety measures in the workplace and adapt their behaviors. Though safety climate research abounds, fewer efforts are made to investigate the formation of a safety climate. An effort to explore forming psychological safety climate, an operationalization of safety climate at the individual level, is an appropriate starting point. Taking the view that projects are social processes, this paper develops a conceptual framework of forming the psychological safety climate, and provides a preliminary validation. The model suggests that management can create the desired psychological safety climate by efforts from structural, perceptual, interactive, and cultural perspectives. Future empirical research can be built on the model to provide a more comprehensive and coherent picture of the determinants of safety climate.

A model to estimate the durability performance of both normal and light-weight concrete

There has been an increasing focus on the development of test methods to evaluate the durability performance of concrete. This paper contributes to this focus by presenting a study that evaluates the effect of water accessible porosity and oven-dry unit weight on the resistance of both normal and light-weight concrete to chloride-ion penetration. Based on the experimental results and regression analyses, empirical models are established to correlate the total charge passed and the chloride migration coefficient with the basic properties of concrete such as water accessible porosity, oven dry unit weight, and compressive strength. These equations can be broadly applied to both normal and lightweight aggregate concretes. The model was also validated by an independent set of experimental results from two different concrete mixtures. The model provides a very good estimate on the concrete’s durability performance in respect to the resistance to chloride ion penetration.

Macro- and micronutrient disposition in an ex vivo model of extracorporeal membrane oxygenation

Background Extracorporeal membrane oxygenation (ECMO) circuits have been shown to sequester circulating blood compounds such as drugs based on their physicochemical properties. This study aimed to describe the disposition of macro- and micronutrients in simulated ECMO circuits. Methods Following baseline sampling, known quantities of macro- and micronutrients were injected post oxygenator into ex vivo ECMO circuits primed with the fresh human whole blood and maintained under standard physiologic conditions. Serial blood samples were then obtained at 1, 30 and 60 min and at 6, 12 and 24 h after the addition of nutrients, to measure the concentrations of study compounds using validated assays. Results Twenty-one samples were tested for thirty-one nutrient compounds. There were significant reductions (p < 0.05) in circuit concentrations of some amino acids [alanine (10%), arginine (95%), cysteine (14%), glutamine (25%) and isoleucine (7%)], vitamins [A (42%) and E (6%)] and glucose (42%) over 24 h. Significant increases in circuit concentrations (p < 0.05) were observed over time for many amino acids, zinc and vitamin C. There were no significant reductions in total proteins, triglycerides, total cholesterol, selenium, copper, manganese and vitamin D concentrations within the ECMO circuit over a 24-h period. No clear correlation could be established between physicochemical properties and circuit behaviour of tested nutrients. Conclusions Significant alterations in macro- and micronutrient concentrations were observed in this single-dose ex vivo circuit study. Most significantly, there is potential for circuit loss of essential amino acid isoleucine and lipid soluble vitamins (A and E) in the ECMO circuit, and the mechanisms for this need further exploration. While the reductions in glucose concentrations and an increase in other macro- and micronutrient concentrations probably reflect cellular metabolism and breakdown, the decrement in arginine and glutamine concentrations may be attributed to their enzymatic conversion to ornithine and glutamate, respectively. While the results are generally reassuring from a macronutrient perspective, prospective studies in clinical subjects are indicated to further evaluate the influence of ECMO circuit on micronutrient concentrations and clinical outcomes.

A framework for model integration and holistic modelling of socio-technical systems

This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

A semi-alternating direction method for a 2-D fractional FitzHugh–Nagumo monodomain model on an approximate irregular domain

A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.

Computational micromodel for epigenetic mechanisms

Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of histone modifications and DNA methylation. These dynamic elements interact to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing imbalance that can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in gene expression and investigate their intrinsic interdependency. In this paper, we explore the relation between DNA methylation and transcription and characterize in detail the histone modifications for specific DNA methylation levels using a stochastic approach.

Impact of mobility constraints on epidemic broadcast mechanisms in delay-tolerant networks

In this paper, we investigate the effect of mobility constraints on epidemic broadcast mechanisms in DTNs (Delay-Tolerant Networks). Major factors affecting epidemic broadcast performances are its forwarding algorithm and node mobility. The impact of forwarding algorithm and node mobility on epidemic broadcast mechanisms has been actively studied in the literature, but those studies generally use unconstrained mobility models. The objective of this paper is therefore to quantitatively investigate the effect of mobility constraints on epidemic broadcast mechanisms. We evaluate the performances of three classes of epidemic broadcast mechanisms - P-BCAST (PUSH-based BroadCast), SA-BCAST (Self-Adaptive BroadCast), and HP-BCAST (History-based P-BCAST) - with a random waypoint mobility model with mobility constraints. Our finding includes that the existence of mobility constraints significantly improves the reach ability and dissemination speed of epidemic broadcast mechanisms while degrading their efficiency.

A novel population balance model for the dilute acid hydrolysis of hemicellulose

Acid hydrolysis is a popular pretreatment for removing hemicellulose from lignocelluloses in order to produce a digestible substrate for enzymatic saccharification. In this work, a novel model for the dilute acid hydrolysis of hemicellulose within sugarcane bagasse is presented and calibrated against experimental oligomer profiles. The efficacy of mathematical models as hydrolysis yield predictors and as vehicles for investigating the mechanisms of acid hydrolysis is also examined. Experimental xylose, oligomer (degree of polymerisation 2 to 6) and furfural yield profiles were obtained for bagasse under dilute acid hydrolysis conditions at temperatures ranging from 110C to 170C. Population balance kinetics, diffusion and porosity evolution were incorporated into a mathematical model of the acid hydrolysis of sugarcane bagasse. This model was able to produce a good fit to experimental xylose yield data with only three unknown kinetic parameters ka, kb and kd. However, fitting this same model to an expanded data set of oligomeric and furfural yield profiles did not successfully reproduce the experimental results. It was found that a ``hard-to-hydrolyse'' parameter, $\alpha$, was required in the model to ensure reproducibility of the experimental oligomer profiles at 110C, 125C and 140C. The parameters obtained through the fitting exercises at lower temperatures were able to be used to predict the oligomer profiles at 155C and 170C with promising results. The interpretation of kinetic parameters obtained by fitting a model to only a single set of data may be ambiguous. Although these parameters may correctly reproduce the data, they may not be indicative of the actual rate parameters, unless some care has been taken to ensure that the model describes the true mechanisms of acid hydrolysis. It is possible to challenge the robustness of the model by expanding the experimental data set and hence limiting the parameter space for the fitting parameters. The novel combination of ``hard-to-hydrolyse'' and population balance dynamics in the model presented here appears to stand up to such rigorous fitting constraints.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

Collaborative learning model of infrastructure construction: A capability perspective

Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Model’s empirical value will be tested in future research.