Anionic metabolic profiling of urine from antibiotic-treated rats by capillary electrophoresis–mass spectrometry

A recently developed capillary electrophoresis (CE)-negative-ionisation mass spectrometry (MS) method was used to profile anionic metabolites in a microbial-host co-metabolism study. Urine samples from rats receiving antibiotics (penicillin G and streptomycin sulfate) for 0, 4, or 8 days were analysed. A quality control sample was measured repeatedly to monitor the performance of the applied CE-MS method. After peak alignment, relative standard deviations (RSDs) for migration time of five representative compounds were below 0.4 %, whereas RSDs for peak area were 7.9–13.5 %. Using univariate and principal component analysis of obtained urinary metabolic profiles, groups of rats receiving different antibiotic treatment could be distinguished based on 17 discriminatory compounds, of which 15 were downregulated and 2 were upregulated upon treatment. Eleven compounds remained down- or upregulated after discontinuation of the antibiotics administration, whereas a recovery effect was observed for others. Based on accurate mass, nine compounds were putatively identified; these included the microbial-mammalian co-metabolites hippuric acid and indoxyl sulfate. Some discriminatory compounds were also observed by other analytical techniques, but CE-MS uniquely revealed ten metabolites modulated by antibiotic exposure, including aconitic acid and an oxocholic acid. This clearly demonstrates the added value of CE-MS for nontargeted profiling of small anionic metabolites in biological samples.

International financial reporting standards (IFRS) as a change agent in Ukraine

This paper aims to examine the perception of key actors regarding the costs and benefits that result from adopting International Financial Reporting Standards (IFRS) in Ukraine. Authors showed that IFRS implementation impacts on internal reporting quality, the relationship with customers, creditors and shareholders, the access to international markets and external financing. They also indicated that financial managers have serious concerns about implementation costs related to the introduction of IFRS. These costs relate to training, instruction on IFRS adoption and translation of current IFRS, changes in software systems, double purpose accounting and deadlines for IFRS adoption and consulting services.

Messages about antibiotic resistance in different newspaper genres

Poorer people are more likely to use antibiotics; inappropriate antibiotic use causes resistance, and health campaigns attempt to change behaviour through education. However, fuelled by the media, the public think antibiotic resistance is outside their control. Differences in the attribution of blame for antibiotic resistance in two genres of UK newspapers, targeting distinct socioeconomic groups, were examined using a mixed methods approach. Firstly, depiction of blame was categorised as either external to the lay public (outside their control) or internal (lay person accountable) and subjected to a chi-square test. Secondly, using critical discourse analysis, we examined the portrayal of the main agents through newspaper language. Data from 597 articles (307 broadsheets) analysed revealed a significant association between newspaper genre and attribution of blame for antibiotic resistance. While both newspaper types blamed antibiotic resistance predominantly on factors external to the lay public, broadsheets were more likely to acknowledge internal factors than tabloids. Tabloids provided a more skewed representation, exposing readers to inaccurate explanations about antibiotic resistance. They highlighted ineptitude in health professionals, victimising patients and blaming others, while broadsheets used less emotive language. Pharmacists should take special care to communicate the importance of appropriate antibiotic use against this backdrop of distortion.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

An analysis of UK policies for domestic energy reduction using an agent based tool

This paper introduces a new agent-based model, which incorporates the actions of individual homeowners in a long-term domestic stock model, and details how it was applied in energy policy analysis. The results indicate that current policies are likely to fall significantly short of the 80% target and suggest that current subsidy levels need re-examining. In the model, current subsidy levels appear to offer too much support to some technologies, which in turn leads to the suppression of other technologies that have a greater energy saving potential. The model can be used by policy makers to develop further scenarios to find alternative, more effective, sets of policy measures. The model is currently limited to the owner-occupied stock in England, although it can be expanded, subject to the availability of data.

Hydrophilic interaction chromatography–mass spectrometry for anionic metabolic profiling of urine from antibiotic-treated rats

Hydrophilic interaction chromatography–mass spectrometry (HILIC–MS) was used for anionic metabolic profiling of urine from antibiotic-treated rats to study microbial–host co-metabolism. Rats were treated with the antibiotics penicillin G and streptomycin sulfate for four or eight days and compared to a control group. Urine samples were collected at day zero, four and eight, and analyzed by HILIC–MS. Multivariate data analysis was applied to the urinary metabolic profiles to identify biochemical variation between the treatment groups. Principal component analysis found a clear distinction between those animals receiving antibiotics and the control animals, with twenty-nine discriminatory compounds of which twenty were down-regulated and nine up-regulated upon treatment. In the treatment group receiving antibiotics for four days, a recovery effect was observed for seven compounds after cessation of antibiotic administration. Thirteen discriminatory compounds could be putatively identified based on their accurate mass, including aconitic acid, benzenediol sulfate, ferulic acid sulfate, hippuric acid, indoxyl sulfate, penicillin G, phenol and vanillin 4-sulfate. The rat urine samples had previously been analyzed by capillary electrophoresis (CE) with MS detection and proton nuclear magnetic resonance (1H NMR) spectroscopy. Using CE–MS and 1H NMR spectroscopy seventeen and twenty-five discriminatory compounds were found, respectively. Both hippuric acid and indoxyl sulfate were detected across all three platforms. Additionally, eight compounds were observed with both HILIC–MS and CE–MS. Overall, HILIC–MS appears to be highly complementary to CE–MS and 1H NMR spectroscopy, identifying additional compounds that discriminate the urine samples from antibiotic-treated and control rats.

Array based detection of antibiotic resistance genes in Gram negative bacteria isolated from retail poultry meat in the UK and Ireland

The use of antibiotics in birds and animals intended for human consumption within the European Union (EU) and elsewhere has been subject to regulation prohibiting the use of antimicrobials as growth promoters and the use of last resort antibiotics in an attempt to reduce the spread of multi-resistant Gram negative bacteria. Given the inexorable spread of antibiotic resistance there is an increasing need for improved monitoring of our food. Using selective media, Gram negative bacteria were isolated from retail chicken of UK-Intensively reared (n = 27), Irish-Intensively reared (n = 19) and UK-Free range (n = 30) origin and subjected to an oligonucleotide based array system for the detection of 47 clinically relevant antibiotic resistance genes (ARGs) and two integrase genes. High incidences of β-lactamase genes were noted in all sample types, acc (67%), cmy (80%), fox (55%) and tem (40%) while chloramphenicol resistant determinants were detected in bacteria from the UK poultry portions and were absent in bacteria from the Irish samples. Denaturing Gradient Gel Electrophoresis (DGGE) was used to qualitatively analyse the Gram negative population in the samples and showed the expected diversity based on band stabbing and DNA sequencing. The array system proved to be a quick method for the detection of antibiotic resistance gene (ARG) burden within a mixed Gram negative bacterial population.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Biology as an agent of chemical and mineralogical change in soil

Earthworms have a significant impact on the functioning of soils and the processes that occur within them. Here we review our work on the impact of earthworms on soil mineralogy and chemistry, in particular focusing on the contribution of earthworms to mineral weathering and calcium carbonate in soils and the impact that earthworms have on metal mobility at contaminated sites.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

nor-Mevaldic acid surrogates as selective antifungal agent leads against Botrytis cinerea. Enantioselective preparation of 4-hydroxy-6-(1-phenylethoxy)tetrahydro-2H-pyran-2-one

Solvent-free desymmetrisation of meso-dialdehyde 1 with chiral 1-phenylethan-1-ol, led to preparation of 4-silyloxy-6-alkyloxytetrahydro-2H-pyran-2-one (+)-3a with a 96:4 d.r. Deprotected lactone (+)-19a and the related racemic lactones 16a-18a present a lactone moiety resembling the natural substrate of HMG-CoA reductase and their antifungal properties have been evaluated against the phytopathogenic fungi Botrytis cinerea and Colletotrichum gloeosporioides. These compounds were selectively active against B. cinerea, while inactive against C. gloeosporioides.