The type II secretion system and its ubiquitous lipoprotein substrate, SsIE are required for biofilm formation and virulence of enteropathogenic escherichia coli

Enteropathogenic Escherichia coli (EPEC) is a major cause of diarrhea in infants in developing countries. We have identified a functional type II secretion system (T2SS) in EPEC that is homologous to the pathway responsible for the secretion of heat-labile enterotoxin by enterotoxigenic E. coli. The wild-type EPEC T2SS was able to secrete a heat-labile enterotoxin reporter, but an isogenic T2SS mutant could not. We showed that the major substrate of the T2SS in EPEC is SslE, an outer membrane lipoprotein (formerly known as YghJ), and that a functional T2SS is essential for biofilm formation by EPEC. T2SS and SslE mutants were arrested at the microcolony stage of biofilm formation, suggesting that the T2SS is involved in the development of mature biofilms and that SslE is a dominant effector of biofilm development. Moreover, the T2SS was required for virulence, as infection of rabbits with a rabbit-specific EPEC strain carrying a mutation in either the T2SS or SslE resulted in significantly reduced intestinal colonization and milder disease.

Transcriptional regulation of the yghJ-pppA-yghG-gspCDEFGHIJKLM cluster, encoding the type II secretion pathway in Enterotoxigenic Escherichia coli

The gene cluster gspCDEFGHIJKLM codes for various structural components of the type II secretion pathway which is responsible for the secretion of heat-labile enterotoxin by enterotoxigenic Escherichia coli (ETEC). In this work, we used a variety of molecular approaches to elucidate the transcriptional organization of the ETEC type II secretion system and to unravel the mechanisms by which the expression of these genes is controlled. We showed that the gspCDEFGHIJKLM cluster and three other upstream genes, yghJ, pppA, and yghG, are cotranscribed and that a promoter located in the upstream region of yghJ plays a major role in the expression of this 14-gene transcriptional unit. Transcription of the yghJ promoter was repressed 168-fold upon a temperature downshift from 37°C to 22°C. This temperature-induced repression was mediated by the global regulatory proteins H-NS and StpA. Deletion mutagenesis showed that the promoter region encompassing positions −321 to +301 relative to the start site of transcription of yghJ was required for full repression. The yghJ promoter region is predicted to be highly curved and bound H-NS or StpA directly. The binding of H-NS or StpA blocked transcription initiation by inhibiting promoter open complex formation. Unraveling the mechanisms of regulation of type II secretion by ETEC enhances our understanding of the pathogenesis of ETEC and other pathogenic varieties of E. coli.

Neural network and interval type-2 fuzzy system for stock price forecasting

Stock price forecast has long been received special attention of investors and financial institutions. As stock prices are changeable over time and increasingly uncertain in modern financial markets, their forecasting becomes more important than ever before. A hybrid approach consisting of two components, a neural network and a fuzzy logic system, is proposed in this paper for stock price prediction. The first component of the hybrid, i.e. a feedforward neural network (FFNN), is used to select inputs that are highly relevant to the dependent variables. An interval type-2 fuzzy logic system (IT2 FLS) is employed as the second component of the hybrid forecasting method. The IT2 FLS’s parameters are initialized through deployment of the k-means clustering method and they are adjusted by the genetic algorithm. Experimental results demonstrate the efficiency of the FFNN input selection approach as it reduces the complexity and increase the accuracy of the forecasting models. In addition, IT2 FLS outperforms the widely used type-1 FLS and FFNN models in stock price forecasting. The combination of the FFNN and the IT2 FLS produces dominant forecasting accuracy compared to employing only the IT2 FLSs without the FFNN input selection.

Mass spectrometry-based proteomic data for cancer diagnosis using interval type-2 fuzzy system

An interval type-2 fuzzy logic system is introduced for cancer diagnosis using mass spectrometry-based proteomic data. The fuzzy system is incorporated with a feature extraction procedure that combines wavelet transform and Wilcoxon ranking test. The proposed feature extraction generates feature sets that serve as inputs to the type-2 fuzzy classifier. Uncertainty, noise and outliers that are common in the proteomic data motivate the use of type-2 fuzzy system. Tabu search is applied for structure learning of the fuzzy classifier. Experiments are performed using two benchmark proteomic datasets for the prediction of ovarian and pancreatic cancer. The dominance of the suggested feature extraction as well as type-2 fuzzy classifier against their competing methods is showcased through experimental results. The proposed approach therefore is helpful to clinicians and practitioners as it can be implemented as a medical decision support system in practice.

Host defense at the ocular surface

Microbial infections of the cornea frequently cause painful, blinding and debilitating disease that is often difficult to treat and may require corneal transplantation. In addition, sterile corneal infiltrates that are associated with contact lens wear cause pain, visual impairment and photophobia. In this article, we review the role of Toll-Like Receptors (TLR) in bacterial keratitis and sterile corneal infiltrates, and describe the role of MD-2 regulation in LPS responsiveness by corneal epithelial cells. We conclude that both live bacteria and bacterial products activate Toll-Like Receptors in the cornea, which leads to chemokine production and neutrophil recruitment to the corneal stroma. While neutrophils are essential for bacterial killing, they also cause tissue damage that results in loss of corneal clarity. These disparate outcomes, therefore, represent a spectrum of disease severity based on this pathway, and further indicate that targeting the TLR pathway is a feasible approach to treating inflammation caused by live bacteria and microbial products. Further, as the P. aeruginosa type III secretion system (T3SS) also plays a critical role in disease pathogenesis by inducing neutrophil apoptosis and facilitating bacterial growth in the cornea, T3SS exotoxins are additional targets for therapy for P. aeruginosa keratitis.

Multi-output interval type-2 fuzzy logic system for protein secondary structure prediction

A new multi-output interval type-2 fuzzy logic system (MOIT2FLS) is introduced for protein secondary structure prediction in this paper. Three outputs of the MOIT2FLS correspond to three structure classes including helix, strand (sheet) and coil. Quantitative properties of amino acids are employed to characterize twenty amino acids rather than the widely used computationally expensive binary encoding scheme. Three clustering tasks are performed using the adaptive vector quantization method to construct an equal number of initial rules for each type of secondary structure. Genetic algorithm is applied to optimally adjust parameters of the MOIT2FLS. The genetic fitness function is designed based on the Q3 measure. Experimental results demonstrate the dominance of the proposed approach against the traditional methods that are Chou-Fasman method, Garnier-Osguthorpe-Robson method, and artificial neural network models.

An intelligent forex monitoring system

The need for intelligent monitoring systems has become a necessity to keep track of the complex forex market. The vast currency market is a foreign concept to the average individual. However, once it is broken down into simple terms, the average individual can begin to understand the foreign exchange market and use it as a financial instrument for future investing. We attempt to compare the performance of a Takagi-Sugeno, type neuro-fuzzy system and a feedforward neural network trained using the scaled conjugate gradient algorithm to predict the average monthly forex rates. We considered the exchange values of Australian dollar with respect to US dollar, Singapore dollar, New Zealand dollar, Japanese yen and United Kingdom pounds. The connectionist models were trained using 70% of the data and remaining was used for testing and validation purposes. It is observed that the proposed connectionist models were able to predict the average forex rates one month ahead accurately. Experiment results also reveal that the neuro-fuzzy technique performed better than the neural network

Hydrological modelling with a dynamic neural fuzzy inference system

Dynamic Evolving Neural-Fuzzy Inference System (DENFIS) is a Takagi-Sugeno-type fuzzy inference system for online learning which can be applied for dynamic time series prediction. Data from Heshui catchment (2,275 km2) which is rural catchment in China, comprising daily time series of rainfall and discharge from January 1, 1990 to January 21, 2006 were analyzed. Rainfall and discharge antecedents were the inputs used for the DENFIS and ANFIS models and the output was discharge at the present time. DENFIS model results were compared with the results obtained from the physically-based University Regina Hydrologic Model (URHM) and an Adaptive Network-based Fuzzy Inference System (ANFIS) which employs offline learning. Our analysis shows that DENFIS results are better or at least comparable to URHM, but almost identical to ANFIS.

Dynamic evolving neural-fuzzy inference system for rainfall-runoff (R-R) modelling

Dynamic Evolving Neural-Fuzzy Inference System (DENFIS) is a Takagi-Sugeno-type fuzzy inference system for online learning which can be applied for dynamic time series prediction. To the best of our knowledge, this is the first time that DENFIS has been used for rainfall-runoff (R-R) modeling. DENFIS model results were compared to the results obtained from the physically-based Storm Water Management Model (SWMM) and an Adaptive Network-based Fuzzy Inference System (ANFIS) which employs offline learning. Data from a small (5.6 km2) catchment in Singapore, comprising 11 separated storm events were analyzed. Rainfall was the only input used for the DENFIS and ANFIS models and the output was discharge at the present time. It is concluded that DENFIS results are better or at least comparable to SWMM, but similar to ANFIS. These results indicate a strong potential for DENFIS to be used in R-R modeling.

Securing institutional legitimacy or organizational effectiveness?

Purpose: The purpose of this paper is to consider the impact of a major initiative (the National Competition Policy) and pieces of legislation (the Local Government Act and the Local Government Finance Standards) on the internal practices of a large Australian local authority.

Design/methodology/approach: A theoretical framework is developed using new public management (NPM) and neo-institutional theory literatures to explain the findings. A case study approach was applied to collect the data for the research.

Findings: The findings reveal that the National Competition Policy 1993, the Local Government Act 1993 and the Local Government Finance Standards 1994 mainly have brought about significant changes to the organisation's internal management control processes, such as financial reporting, budgeting and performance appraisal. The changes brought in appeared to be coincidentally similar to NPM ideals. Furthermore, senior managers (such as the chief executive and divisional heads) played a major role in implementing new accounting technologies (activity-based costing and the balanced scorecard type performance measurement system).

Research limitations/implications: Future research on public sector financial management from the outset of organisational contexts could considerably further the stock of knowledge in this area, especially given the rapid changes occurring within the public sector throughout the world. Future research may wish to extend this study by assessing how external legitimating functions become internal reality, the perceptions of reality of the organisational members, and how these perceptions change over time.

Practical implications: The findings reported provide evidence to further our understanding of how the introduction of private sector styles of organisational practices into large areas of the public sector brought about significant changes in the demand for “new” financial management practices.

Originality/value: The findings reported on in this paper will open a new path of research that may increase our understanding about the factors that play a role in the design of management and accounting systems in a public sector context. Further, they will help policy makers and public sector managers in their day-to-day decision-making.

A review of employment relations theories and their application

New developments in the industrial relations and human resource management have moved management and employee bargaining down to the level of the firm. In doing so they have generated a growing level of interest in the conduct of employment relations, not just at the level of specialist managers, who have traditionally had the responsibility for dealing with issues in this area, but across management as a whole. There is thus a growing need for managers to place more emphasis on achieving a greater symmetry between commercial objectives and employment practices. This paper looks at the predicates of managerial authority and its legitimacy, and how personal assumptions and value systems (i.e., ‘frames of reference’) held by managers can predispose them to view the nature of work and workplace relations in particular ways. The paper also presents
and aligns a range of contemporary theories within the province of such systems, with the aim being to show how judgements made about the worth or otherwise of a given range of theories are inevitably shaped by the type of value system and set of assumptions one holds towards the
world of work. The paper concludes by offering a practical guide to managers on how to evaluate their own assumptions and value systems when applying the noted theories and concepts to real world circumstances. In doing so, the paper provides a tool kit of theories and concepts that should allow managers to avoid engaging in workforce management practices that are either illconceived or based on intuitive premises.

Exploring distributive justice in health care

The allocation of resources to providers and the way in which the resources are then prioritised to specific service areas and patients remain the critical ethical decisions which determine the type of health system a community receives. Heath care providers will never be given enough resources to satisfy all the demands placed upon them by a community that is becoming increasingly informed and demanding. This paper discusses the matter of justice as it relates to the distribution of health resources. It translates the theoretical constructs of distribution into a practical situation that arose at The Geelong Hospital. It is important to emphasise that the aim of giving the example is not necessarily to provide the right answer but rather to assist in determining what ought to be the questions.

Australian forex market anaylsis using connectionist models

The need for intelligent monitoring systems has become a necessity to keep track of the complex forex market. The forex market is difficult to understand by an average individual. However, once the market is broken down into simple terms, the average individual can begin to understand the foreign exchange market and use it as a financial instrument for future investing. This paper is an attempt to compare the performance of a Takagi-Sugeno type neuro-fuzzy system and a feed forward neural network trained using the scaled conjugate gradient algorithm to predict the average monthly forex rates. The exchange values of Australian dollar are considered with respect to US dollar, Singapore dollar, New Zealand dollar, Japanese yen and United Kingdom pound. The connectionist models were trained using 70% of the data and remaining was used for testing and validation purposes. It is observed that the proposed connectionist models were able to predict the average forex rates one month ahead accurately. Experiment results also reveal that neuro-fuzzy technique performed better than the neural network.

Plasmodium falciparum possesses two GRASP proteins that are differentially targeted to the Golgi complex via a higher- and lower-eukaryote-like mechanism

Plasmodium falciparum, the causative agent of malaria, relies on a complex protein-secretion system for protein targeting into numerous subcellular destinations. Recently, a homologue of the Golgi re-assembly stacking protein (GRASP) was identified and used to characterise the Golgi organisation in this parasite. Here, we report on the presence of a splice variant that leads to the expression of a GRASP isoform. Although the first GRASP protein (GRASP1) relies on a well-conserved myristoylation motif, the variant (GRASP2) displays a different N-terminus, similar to GRASPs found in fungi. Phylogenetic analyses between GRASP proteins of numerous taxa point to an independent evolution of the unusual N-terminus that could reflect unique requirements for Golgi-dependent protein sorting and organelle biogenesis in P. falciparum. Golgi association of GRASP2 depends on the hydrophobic N-terminus that resembles a signal anchor, leading to a unique mode of Golgi targeting and membrane attachment.