Contribution of siderophore systems to growth and urinary tract colonization of asymptomatic bacteriuria Escherichia coli

The molecular mechanisms that define asymptomatic bacteriuria (ABU) Escherichia coli colonization of the human urinary tract remain to be properly elucidated. Here, we utilize ABU E. coli strain 83972 as a model to dissect the contribution of siderophores to iron acquisition, growth, fitness, and colonization of the urinary tract. We show that E. coli 83972 produces enterobactin, salmochelin, aerobactin, and yersiniabactin and examine the role of these systems using mutants defective in siderophore biosynthesis and uptake. Enterobactin and aerobactin contributed most to total siderophore activity and growth in defined iron-deficient medium. No siderophores were detected in an 83972 quadruple mutant deficient in all four siderophore biosynthesis pathways; this mutant did not grow in defined iron-deficient medium but grew in iron-limited pooled human urine due to iron uptake via the FecA ferric citrate receptor. In a mixed 1:1 growth assay with strain 83972, there was no fitness disadvantage of the 83972 quadruple biosynthetic mutant, demonstrating its capacity to act as a “cheater” and utilize siderophores produced by the wild-type strain for iron uptake. An 83972 enterobactin/salmochelin double receptor mutant was outcompeted by 83972 in human urine and the mouse urinary tract, indicating a role for catecholate receptors in urinary tract colonization.

Characterization of two homologous disulfide bond systems involved in virulence factor Biogenesis in Uropathogenic Escherichia coli CFT073

Disulfide bond (DSB) formation is catalyzed by disulfide bond proteins and is critical for the proper folding and functioning of secreted and membrane-associated bacterial proteins. Uropathogenic Escherichia coli (UPEC) strains possess two paralogous disulfide bond systems: the well-characterized DsbAB system and the recently described DsbLI system. In the DsbAB system, the highly oxidizing DsbA protein introduces disulfide bonds into unfolded polypeptides by donating its redox-active disulfide and is in turn reoxidized by DsbB. DsbA has broad substrate specificity and reacts readily with reduced unfolded proteins entering the periplasm. The DsbLI system also comprises a functional redox pair; however, DsbL catalyzes the specific oxidative folding of the large periplasmic enzyme arylsulfate sulfotransferase (ASST). In this study, we characterized the DsbLI system of the prototypic UPEC strain CFT073 and examined the contributions of the DsbAB and DsbLI systems to the production of functional flagella as well as type 1 and P fimbriae. The DsbLI system was able to catalyze disulfide bond formation in several well-defined DsbA targets when provided in trans on a multicopy plasmid. In a mouse urinary tract infection model, the isogenic dsbAB deletion mutant of CFT073 was severely attenuated, while deletion of dsbLI or assT did not affect colonization.

A cost-effectiveness analysis of a telephone-linked care intervention for individuals with Type 2 diabetes

AIM: To assess the cost-effectiveness of an automated telephone-linked care intervention, Australian TLC Diabetes, delivered over 6 months to patients with established Type 2 diabetes mellitus and high glycated haemoglobin level, compared to usual care. METHODS: A Markov model was designed to synthesize data from a randomized controlled trial of TLC Diabetes (n=120) and other published evidence. The 5-year model consisted of three health states related to glycaemic control: 'sub-optimal' HbA1c ≥58mmol/mol (7.5%); 'average' ≥48-57mmol/mol (6.5-7.4%) and 'optimal' <48mmol/mol (6.5%) and a fourth state 'all-cause death'. Key outcomes of the model include discounted health system costs and quality-adjusted life years (QALYS) using SF-6D utility weights. Univariate and probabilistic sensitivity analyses were undertaken. RESULTS: Annual medication costs for the intervention group were lower than usual care [Intervention: £1076 (95%CI: £947, £1206) versus usual care £1271 (95%CI: £1115, £1428) p=0.052]. The estimated mean cost for intervention group participants over five years, including the intervention cost, was £17,152 versus £17,835 for the usual care group. The corresponding mean QALYs were 3.381 (SD 0.40) for the intervention group and 3.377 (SD 0.41) for the usual care group. Results were sensitive to the model duration, utility values and medication costs. CONCLUSION: The Australian TLC Diabetes intervention was a low-cost investment for individuals with established diabetes and may result in medication cost-savings to the health system. Although QALYs were similar between groups, other benefits arising from the intervention should also be considered when determining the overall value of this strategy.

Reducing rear-end crashes with cooperative systems

This paper presents an evaluation of the effectiveness of a cooperative Intelligent Transport System (C-ITS) to reduce rear-end crashes. Two complementary simulation techniques are used to demonstrate the benefits of the C-ITS. A traffic (VEINS) and sensor (SiVIC) simulations use realistic data related to traffic/road in Brisbane’s Pacific Motorway, driver’s reaction time and injury severity to evaluate benefits. The results of our simulations show that C-ITS could reduce rear-end crash risk by providing several seconds of additional warning to drivers.

Circulating fragments of N-Terminal Pro-B-Type Natriuretic Peptides in plasma of heart failure patients

BACKGROUND: The use of nonstandardized N-terminal pro-B-type natriuretic peptide (NT-proBNP) assays can contribute to the misdiagnosis of heart failure (HF). Moreover, there is yet to be established a common consensus regarding the circulating forms of NT-proBNP being used in current assays. We aimed to characterize and quantify the various forms of NT-proBNP in the circulation of HF patients. METHODS: Plasma samples were collected from HF patients (n = 20) at rest and stored at -80 degrees C. NT-proBNP was enriched from HF patient plasma by use of immunoprecipitation followed by mass spectrometric analysis. Customized homogeneous sandwich AlphaLISA (R) immunoassays were developed and validated to quantify 6 fragments of NT-proBNP. RESULTS: Mass spectrometry identified the presence of several N- and C-terminally processed forms of circulating NT-proBNP, with physiological proteolysis between Pro2-Leu3, Leu3-Gly4, Pro6-Gly7, and Pro75-Arg76. Consistent with this result, AlphaLISA immunoassays demonstrated that antibodies targeting the extreme N or C termini measured a low apparent concentration of circulating NT-proBNP. The apparent circulating NT-proBNP concentration was increased with antibodies targeting nonglycosylated and nonterminal epitopes (P < 0.05). CONCLUSIONS: In plasma collected from HF patients, immunoreactive NT-proBNP was present as multiple N- and C-terminally truncated fragments of the full length NT-proBNP molecule. Immunodetection of NT-proBNP was significantly improved with the use of antibodies that did not target these terminal regions. These findings support the development of a next generation NT-proBNP assay targeting nonterminal epitopes as well as avoiding the central glycosylated region of this molecule. (c) 2013 American Association for Clinical Chemistry

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Amplitude of accommodation in type 1 diabetes

Purpose People with diabetes have accelerated age-related biometric ocular changes compared with people without diabetes. We determined the effect of Type 1 diabetes on amplitude of accommodation. Method There were 43 participants (33 ± 8 years) with type 1 diabetes and 32 (34 ± 8 years) age-balanced participants without diabetes. There was no significant difference in the mean equivalent refractive error and visual acuity between the two groups. Amplitude of accommodation was measured using two techniques: objective — by determining the accommodative response to a stimulus in a COAS-HD wavefront aberrometer (Wavefront Sciences), and subjective — with a Badal hand optometer (Rodenstock). The influences of age and diabetes duration (in years) on amplitude of accommodation were analyzed using multiple regression analysis. Results Across both groups, objective amplitude was less than subjective amplitude by 1.4 ± 1.2 D. People with diabetes had lower objective (2.7 ± 1.6 D) and subjective (4.0 ± 1.7 D) amplitudes than people without diabetes (objective 4.1 ± 2.1 D, subjective 5.6 ± 2.1 D). For objective amplitude and the whole group, the duration of diabetes contributed 57% of the variation as did age. For the objective amplitude and only the diabetes group this was 78%. For subjective amplitude, the corresponding proportions were 68% and 103%. Conclusions Both objective and subjective techniques showed lowered amplitude of accommodation in participants with type 1 diabetes when compared with age-matched controls. The loss correlated strongly with duration of diabetes. The results suggest that individuals with diabetes will experience presbyopia earlier in life than people without diabetes, possibly due to metabolic changes in the lens.

Rethinking the value of simulation methods in the information systems research field : a call for reconstructing contribution for a broader audience

The impact of simulation methods for social research in the Information Systems (IS) research field remains low. A concern is our field is inadequately leveraging the unique strengths of simulation methods. Although this low impact is frequently attributed to methodological complexity, we offer an alternative explanation – the poor construction of research value. We argue a more intuitive value construction, better connected to the knowledge base, will facilitate increased value and broader appreciation. Meta-analysis of studies published in IS journals over the last decade evidences the low impact. To facilitate value construction, we synthesize four common types of simulation research contribution: Analyzer, Tester, Descriptor, and Theorizer. To illustrate, we employ the proposed typology to describe how each type of value is structured in simulation research and connect each type to instances from IS literature, thereby making these value types and their construction visible and readily accessible to the general IS community.

Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

Design, modelling and measurement of a hybrid powerplant for unmanned aerial systems

Hybrid powerplants combining internal combustion engines and electric motor prime movers have been extensively developed for land- and marine-based transport systems. The use of such powerplants in airborne applications has been historically impractical due to energy and power density constraints. Improvements in battery and electric motor technology make aircraft hybrid powerplants feasible. This paper presents a technique for determining the feasibility and mechanical effectiveness of powerplant hybridisation. In this work, a prototype aircraft hybrid powerplant was designed, constructed and tested. It is shown that an additional 35% power can be supplied from the hybrid system with an overall weight penalty of 5%, for a given unmanned aerial system. A flight dynamic model was developed using the AeroSim Blockset in MATLAB Simulink. The results have shown that climb rates can be improved by 56% and endurance increased by 13% when using the hybrid powerplant concept.