Clinical trial: the effects of a trans-galactooligosaccharide prebiotic on faecal microbiota and symptoms in irritable bowel syndrome

Gut microflora-mucosal interactions may be involved in the pathogenesis of irritable bowel syndrome (IBS). To investigate the efficacy of a novel prebiotic trans-galactooligosaccharide in changing the colonic microflora and improve the symptoms in IBS sufferers. In all, 44 patients with Rome II positive IBS completed a 12-week single centre parallel crossover controlled clinical trial. Patients were randomized to receive either 3.5 g/d prebiotic, 7 g/d prebiotic or 7 g/d placebo. IBS symptoms were monitored weekly and scored according to a 7-point Likert scale. Changes in faecal microflora, stool frequency and form (Bristol stool scale) subjective global assessment (SGA), anxiety and depression and QOL scores were also monitored. The prebiotic significantly enhanced faecal bifidobacteria (3.5 g/d P < 0.005; 7 g/d P < 0.001). Placebo was without effect on the clinical parameters monitored, while the prebiotic at 3.5 g/d significantly changed stool consistency (P < 0.05), improved flatulence (P < 0.05) bloating (P < 0.05), composite score of symptoms (P < 0.05) and SGA (P < 0.05). The prebiotic at 7 g/d significantly improved SGA (P < 0.05) and anxiety scores (P < 0.05). The galactooligosaccharide acted as a prebiotic in specifically stimulating gut bifidobacteria in IBS patients and is effective in alleviating symptoms. These findings suggest that the prebiotic has potential as a therapeutic agent in IBS.

A buffering layer to support derived types and proprietary networks for Java HPC

MPJ Express is our implementation of MPI-like bindings for Java. In this paper we discuss our intermediate buffering layer that makes use of the so-called direct byte buffers introduced in the Java New I/O package. The purpose of this layer is to support the implementation of derived datatypes. MPJ Express is the first Java messaging library that implements this feature using pure Java. In addition, this buffering layer allows efficient implementation of communication devices based on proprietary networks such as Myrinet. In this paper we evaluate the performance of our buffering layer and demonstrate the usefulness of direct byte buffers. Also, we evaluate the performance of MPJ Express against other messaging systems using Myrinet and show that our buffering layer has made it possible to avoid the overheads suffered by other Java systems such as mpiJava that relies on the Java Native Interface.

Equitability revisited: why the “equitable threat score” is not equitable

In the forecasting of binary events, verification measures that are “equitable” were defined by Gandin and Murphy to satisfy two requirements: 1) they award all random forecasting systems, including those that always issue the same forecast, the same expected score (typically zero), and 2) they are expressible as the linear weighted sum of the elements of the contingency table, where the weights are independent of the entries in the table, apart from the base rate. The authors demonstrate that the widely used “equitable threat score” (ETS), as well as numerous others, satisfies neither of these requirements and only satisfies the first requirement in the limit of an infinite sample size. Such measures are referred to as “asymptotically equitable.” In the case of ETS, the expected score of a random forecasting system is always positive and only falls below 0.01 when the number of samples is greater than around 30. Two other asymptotically equitable measures are the odds ratio skill score and the symmetric extreme dependency score, which are more strongly inequitable than ETS, particularly for rare events; for example, when the base rate is 2% and the sample size is 1000, random but unbiased forecasting systems yield an expected score of around −0.5, reducing in magnitude to −0.01 or smaller only for sample sizes exceeding 25 000. This presents a problem since these nonlinear measures have other desirable properties, in particular being reliable indicators of skill for rare events (provided that the sample size is large enough). A potential way to reconcile these properties with equitability is to recognize that Gandin and Murphy’s two requirements are independent, and the second can be safely discarded without losing the key advantages of equitability that are embodied in the first. This enables inequitable and asymptotically equitable measures to be scaled to make them equitable, while retaining their nonlinearity and other properties such as being reliable indicators of skill for rare events. It also opens up the possibility of designing new equitable verification measures.

Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

The restoration of phytophagous beetles in species-rich chalk grasslands

This study focuses on the restoration of chalk grasslands over a 6-year period and tests the efficacy of two management practices, hay spreading and soil disturbance, in promoting this process for phytophagous beetles. Restoration success for the beetles, measured as similarity to target species-rich chalk grassland, was not found to be influenced by either management practice. In contrast, restoration success for the plants did increase in response to hay spreading management. Although the presence of suitable host plants was considered to dictate the earliest point at which phytophagous beetles could successfully colonized, few beetle species colonized as soon as their host plants became established. Morphological characteristics and feeding habits of 27 phytophagous beetle species were therefore tested to identify factors that limited their colonization and persistence. The lag time between host plant establishment and colonization was greatest for flightless beetles. Beetles with foliage-feeding larvae both colonized at slower rates than seed-, stem-, or root-feeding species and persisted within the swards for shorter periods. Although the use of hay spreading may benefit plant communities during chalk grassland restoration, it did not directly benefit phytophagous beetles. Without techniques for overcoming colonization limitation for invertebrate taxa, short-term success of restoration may be limited to the plants only.

Challenges in elevated CO2 experiments on forests

Current forest Free Air CO2 Enrichment (FACE) experiments are reaching completion. Therefore, it is time to define the scientific goals and priorities of future experimental facilities. In this opinion article, we discuss the following three overarching issues (i) What are the most urgent scientific questions and how can they be addressed? (ii) What forest ecosystems should be investigated? (iii) Which other climate change factors should be coupled with elevated CO2 concentrations in future experiments to better predict the effects of climate change? Plantations and natural forests can have conflicting purposes for high productivity and environmental protection. However, in both cases the assessment of carbon balance and how this will be affected by elevated CO2 concentrations and the interacting climate change factors is the most pressing priority for future experiments.

A simple, coherent framework for partitioning uncertainty in climate predictions

A simple and coherent framework for partitioning uncertainty in multi-model climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model-scenario interaction - the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the 21st century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multi-model ensembles. For example, three models are shown diverging pattern over the 21st century, while another model exhibits an unusually large variation among its scenario-dependent deviations.

Environmental evaluation of agri-environment schemes using participatory approaches: experiences of testing the Agri-Environmental Footprint Index

The Agri-Environment Footprint Index (AFI) has been developed as a generic methodology to assess changes in the overall environmental impacts from agriculture at the farm level and to assist in the evaluation of European agri-environmental schemes (AES). The methodology is based on multicriteria analysis (MCA) and involves stakeholder participation to provide a locally customised evaluation based on weighted environmental indicators. The methodology was subjected to a feasibility assessment in a series of case studies across the EU. The AFI approach was able to measure significant differences in environmental status between farms that participated in an AES and nonparticipants. Wider environmental concerns, beyond the scheme objectives, were also considered in some case studies and the benefits for identification of unintentional (and often beneficial) impacts of AESs are presented. The participatory approach to AES valuation proved efficient in different environments and administrative contexts. The approach proved to be appropriate for environmental evaluation of complex agri-environment systems and can complement any evaluation conducted under the Common Monitoring and Evaluation Framework. The applicability of the AFI in routine monitoring of AES impacts and in providing feedback to improve policy design is discussed.

Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method

The IntFOLD-TS method was developed according to the guiding principle that the model quality assessment would be the most critical stage for our template based modelling pipeline. Thus, the IntFOLD-TS method firstly generates numerous alternative models, using in-house versions of several different sequence-structure alignment methods, which are then ranked in terms of global quality using our top performing quality assessment method – ModFOLDclust2. In addition to the predicted global quality scores, the predictions of local errors are also provided in the resulting coordinate files, using scores that represent the predicted deviation of each residue in the model from the equivalent residue in the native structure. The IntFOLD-TS method was found to generate high quality 3D models for many of the CASP9 targets, whilst also providing highly accurate predictions of their per-residue errors. This important information may help to make the 3D models that are produced by the IntFOLD-TS method more useful for guiding future experimental work