Criteria for validation and selection of cognitive tests for investigating the effects of foods and nutrients.

This review is an output of the International Life Sciences Institute (ILSI) Europe Marker Initiative, which aims to identify evidence-based criteria for selecting adequate measures of nutrient effects on health through comprehensive literature review. Experts in cognitive and nutrition sciences examined the applicability of these proposed criteria to the field of cognition with respect to the various cognitive domains usually assessed to reflect brain or neurological function. This review covers cognitive domains important in the assessment of neuronal integrity and function, commonly used tests and their state of validation, and the application of the measures to studies of nutrition and nutritional intervention trials. The aim is to identify domain-specific cognitive tests that are sensitive to nutrient interventions and from which guidance can be provided to aid the application of selection criteria for choosing the most suitable tests for proposed nutritional intervention studies using cognitive outcomes. The material in this review serves as a background and guidance document for nutritionists, neuropsychologists, psychiatrists, and neurologists interested in assessing mental health in terms of cognitive test performance and for scientists intending to test the effects of food or food components on cognitive function.

Advanced feature selection methods in multinominal dementia classification from structural MRI data

Recent studies showed that features extracted from brain MRIs can well discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study provides an algorithm that sequentially applies advanced feature selection methods for findings the best subset of features in terms of binary classification accuracy. The classifiers that provided the highest accuracies, have been then used for solving a multi-class problem by the one-versus-one strategy. Although several approaches based on Regions of Interest (ROIs) extraction exist, the prediction power of features has not yet investigated by comparing filter and wrapper techniques. The findings of this work suggest that (i) the IntraCranial Volume (ICV) normalization can lead to overfitting and worst the accuracy prediction of test set and (ii) the combined use of a Random Forest-based filter with a Support Vector Machines-based wrapper, improves accuracy of binary classification.

Data-driven treatment selection for seamless phase II/III trials incorporating early-outcome data

Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow-up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods.

A niche-based framework to assess current monitoring of European forest birds and guide indicator species' selection

Concern that European forest biodiversity is depleted and declining has provoked widespread efforts to improve management practices. To gauge the success of these actions, appropriate monitoring of forest ecosystems is paramount. Multi-species indicators are frequently used to assess the state of biodiversity and its response to implemented management, but generally applicable and objective methodologies for species' selection are lacking. Here we use a niche-based approach, underpinned by coarse quantification of species' resource use, to objectively select species for inclusion in a pan-European forest bird indicator. We identify both the minimum number of species required to deliver full resource coverage and the most sensitive species' combination, and explore the trade-off between two key characteristics, sensitivity and redundancy, associated with indicators comprising different numbers of species. We compare our indicator to an existing forest bird indicator selected on the basis of expert opinion and show it is more representative of the wider community. We also present alternative indicators for regional and forest type specific monitoring and show that species' choice can have a significant impact on the indicator and consequent projections about the state of the biodiversity it represents. Furthermore, by comparing indicator sets drawn from currently monitored species and the full forest bird community, we identify gaps in the coverage of the current monitoring scheme. We believe that adopting this niche-based framework for species' selection supports the objective development of multi-species indicators and that it has good potential to be extended to a range of habitats and taxa.

The road not taken: observing a process of issue selection and model conceptualization

This article describes a case study involving information technology managers and their new programmer recruitment policy, but the primary interest is methodological. The processes of issue generation and selection and model conceptualization are described. Early use of “magnetic hexagons” allowed the generation of a range of issues, most of which would not have emerged if system dynamics elicitation techniques had been employed. With the selection of a specific issue, flow diagraming was used to conceptualize a model, computer implementation and scenario generation following naturally. Observations are made on the processes of system dynamics modeling, particularly on the need to employ general techniques of knowledge elicitation in the early stages of interventions. It is proposed that flexible approaches should be used to generate, select, and study the issues, since these reduce any biasing of the elicitation toward system dynamics problems and also allow the participants to take up the most appropriate problem- structuring approach.

Selection experiments reveal trade-offs between swimming and twitching motilities in pseudomonas aeruginosa

Bacteria possess a range of mechanisms to move in different environments, and these mechanisms have important direct and correlated impacts on the virulence of opportunistic pathogens. Bacteria use two surface organelles to facilitate motility: a single polar flagellum, and type IV pili, enabling swimming in aqueous habitats and twitching along hard surfaces, respectively. Here, we address whether there are trade-offs between these motility mechanisms, and hence whether different environments could select for altered motility. We experimentally evolved initially isogenic Pseudomonas aeruginosa under conditions that favored the different types of motility, and found evidence for a trade-off mediated by antagonistic pleiotropy between swimming and twitching. Moreover, changes in motility resulted in correlated changes in other behaviors, including biofilm formation and growth within an insect host. This suggests environmental origins of a particular motile opportunistic pathogen could predictably influence motility and virulence

Bifidobacteria in milk products: An overview of physiological and biochemical properties, exopolysaccharide production, selection criteria of milk products and health benefits

Research and commercial interest in the genus Bifidobacterium have increased in the last decade due to their potential health benefits in probiotic functional foods, especially in dairy products. However, cultivation of bifidobacteria in milk is a difficult task compared with that of conventional starters because milk is not a good medium for growth of these nutritionally fastidious microorganisms. Therefore, suitable strains of Bifidobacterium for dairy products should be selected based on their safety and technological and functional properties. There are a number of milk products containing bifidobacteria in the world market and the demand for new products is increasing with the awareness of the potential health benefits of the consumption of products blended with bifidobacteria. Some strains of Bifidobacterium, which produce exopolysaccharide, have been isolated and characterised. This review will discuss the general characteristics of bifidobacteria, exopolysaccharide production, the selection criteria of bacterial strains for milk products, current applications of bifidobacteria in milk products, and their nutritional and beneficial health properties.

A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints

In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short- and long-term endpoints.

Systematic selection of analogue redesign method for forward-type digital power converters

This article proposes a systematic approach to determine the most suitable analogue redesign method to be used for forward-type converters under digital voltage mode control. The focus of the method is to achieve the highest phase margin at the particular switching and crossover frequencies chosen by the designer. It is shown that at high crossover frequencies with respect to switching frequency, controllers designed using backward integration have the largest phase margin; whereas at low crossover frequencies with respect to switching frequency, controllers designed using bilinear integration with pre-warping have the largest phase margins. An algorithm has been developed to determine the frequency of the crossing point where the recommended discretisation method changes. An accurate model of the power stage is used for simulation and experimental results from a Buck converter are collected. The performance of the digital controllers is compared to that of the equivalent analogue controller both in simulation and experiment. Excellent closeness between the simulation and experimental results is presented. This work provides a concrete example to allow academics and engineers to systematically choose a discretisation method.

The influence of anxiety on the initial selection of emotional faces presented in binocular rivalry

Neurocognitive theories of anxiety predict that threat-related information can be evaluated before attentional selection, and can influence behaviour differentially in high anxious compared to low anxious individuals. We investigate this further by presenting emotional and neutral faces in an adapted binocular rivalry paradigm. We show that the initial selection of emotional faces presented in binocular rivalry is highly influenced by self-reported state and trait anxiety-level. Heightened anxiety was correlated with increased perception of angry and fearful faces, and decreased perception of happy expressions. These results are consistent with recent evidence of involuntary selection of threat in anxiety.

Effects of organic and conventional fertilizer treatments on host selection by the aphid parasitoid Diaeretiella rapae

The type and quantity of fertilizer supplied to a crop will differ between organic and conventional farming practices. Altering the type of fertilizer a plant is provided with can influence a plant’s foliar nitrogen levels, as well as the composition and concentration of defence compounds, such as glucosinolates. Many natural enemies of insect herbivores can respond to headspace volatiles emitted by the herbivores’ host plant in response to herbivory. We propose that manipulating fertilizer type may also influence the headspace volatile profiles of plants, and as a result, the tritrophic interactions that occur between plants, their insect pests and those pests’ natural enemies. Here, we investigate a tritrophic system consisting of cabbage plants, Brassica oleracea, a parasitoid, Diaeretiella rapae, and one of its hosts, the specialist cabbage aphid Brevicoryne brassicae. Brassica oleracea plants were provided with either no additional fertilization or one of three types of fertilizer: Nitram (ammonium nitrate), John Innes base or organic chicken manure. We investigated whether these changes would alter the rate of parasitism of aphids on those plants and whether any differences in parasitism could be explained by differences in attractivity of the plants to D. rapae or attack rate of aphids by D. rapae. In free-choice experiments, there were significant differences in the percentage of B. brassicae parasitized by D. rapae between B. oleracea plants grown in different fertilizer treatments. In a series of dual-choice Y-tube olfactometry experiments, D. rapae females discriminated between B. brassicae-infested and undamaged plants, but parasitoids did not discriminate between similarly infested plants grown in different fertilizer treatments. Correspondingly, in attack rate experiments, there were no differences in the rate that D. rapae attacked B. brassicae on B. oleracea plants grown in different fertilizer treatments. These findings are of direct relevance to sustainable and conventional farming practices.

Olfactory selection of Plantago lanceolata by snails declines with seedling age

Background and Aims Despite recent recognition that (1) plant–herbivore interactions during the establishment phase, (2) ontogenetic shifts in resource allocation and (3) herbivore response to plant volatile release are each pivotal to a comprehensive understanding of plant defence, no study has examined how herbivore olfactory response varies during seedling ontogeny. Methods Using a Y-tube olfactometer we examined snail (Helix aspersa) olfactory response to pellets derived from macerated Plantago lanceolata plants harvested at 1, 2, 3, 4, 5, 6 and 8 weeks of age to test the hypothesis that olfactory selection of plants by a generalist herbivore varies with plant age. Plant volatiles were collected for 10 min using solid-phase microextraction technique on 1- and 8-week-old P. lanceolata pellets and analysed by gas chromatography coupled with a mass spectrometer. Key Results Selection of P. lanceolata was strongly negatively correlated with increasing age; pellets derived from 1-week-old seedlings were three times more likely to be selected as those from 8-week-old plants. Comparison of plant selection experiments with plant volatile profiles from GC/MS suggests that patterns of olfactory selection may be linked to ontogenetic shifts in concentrations of green leaf volatiles and ethanol (and its hydrolysis derivatives). Conclusions Although confirmatory of predictions made by contemporary plant defence theory, this is the first study to elucidate a link between seedling age and olfactory selection by herbivores. As a consequence, this study provides a new perspective on the ontogenetic expression of seedling defence, and the role of seedling herbivores, particularly terrestrial molluscs, as selective agents in temperate plant communities.

The IT outsourcing market-place: vendors and their selection

This paper focuses on outsourcing vendors, their characteristics and the vendor selection process. It draws on current research and two research studies, one specifi- cally examining outsourcing vendors and the other examining vendor-client issues. We first outline the development of the market for the outsourcing of information technology/information systems services and activities, then detail the characteristics of different types of vendor companies and their competitive positions, before providing a client perspective to the issue of vendor selection.

Estimation after subpopulation selection in adaptive seamless trials

During the development of new therapies, it is not uncommon to test whether a new treatment works better than the existing treatment for all patients who suffer from a condition (full population) or for a subset of the full population (subpopulation). One approach that may be used for this objective is to have two separate trials, where in the first trial, data are collected to determine if the new treatment benefits the full population or the subpopulation. The second trial is a confirmatory trial to test the new treatment in the population selected in the first trial. In this paper, we consider the more efficient two-stage adaptive seamless designs (ASDs), where in stage 1, data are collected to select the population to test in stage 2. In stage 2, additional data are collected to perform confirmatory analysis for the selected population. Unlike the approach that uses two separate trials, for ASDs, stage 1 data are also used in the confirmatory analysis. Although ASDs are efficient, using stage 1 data both for selection and confirmatory analysis introduces selection bias and consequently statistical challenges in making inference. We will focus on point estimation for such trials. In this paper, we describe the extent of bias for estimators that ignore multiple hypotheses and selecting the population that is most likely to give positive trial results based on observed stage 1 data. We then derive conditionally unbiased estimators and examine their mean squared errors for different scenarios.