The epitopes in wheat proteins for defining toxic units relevant to human health

Wheat-related disorders are well-studied health problems. Knowledge of the composition and amounts of epitopes present in a single wheat sample represents a significant gap, and the detailed wheat proteome datasets now available can provide the necessary information to carry out an estimation of allergen prediction for a single cultivar. The combined use of genome sequence and allergen databases, prediction methodology, and cereal chemistry results in better understanding of the level of toxicity present in the end-products produced from wheat flour. The workflow presented in this review provides information about the number and distribution of epitopes at single protein, or protein fraction, levels. In addition, epitopes present in the highest frequency and harmful proteins expressed in the highest amount can be identified. The “epitope toxicity” value obtained in this way is a significant research output from the analysis of large datasets that can be applied to the food industry.     

Understanding sample size: what determines the required number of microarrays for an experiment?

DNA microarray experiments have become a widely used tool for studying gene expression. An important, but difficult, part of these experiments is deciding on the appropriate number of biological replicates to use. Often, researchers will want a number of replicates that give sufficient power to recognize regulated genes while controlling the false discovery rate (FDR) at an acceptable level. Recent advances in statistical methodology can now help to resolve this issue. Before using such methods it is helpful to understand the reasoning behind them. In this Research Focus article we explain, in an intuitive way, the effect sample size has on the FDR and power, and then briefly survey some recently proposed methods in this field of research and provide an example of use.     

The Complex Emergency Database: A Global Repository of Small-Scale Surveys on Nutrition,Health and Mortality

Evidence has become central for humanitarian decision making, as it is now commonly agreed that aid must be provided solely in proportion to the needs and on the basis of needs assessments. Still, reliable epidemiological data from conflict-affected communities are difficult to acquire in time for effective decisions, as existing health information systems progressively lose functionality with the onset of conflicts. In the last decade, health and nutrition humanitarian agencies have made substantial progress in collecting quality data using small-scale surveys. In 2002, a group of academics, non-governmental organizations, and UN agencies launched the Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology. Since then, field agencies have conducted thousands of surveys. Although the contribution of each survey by itself is limited by its small sample and the impossibility to extrapolate results to national level, their aggregation can provide a more stable view of both trends and distributions in a larger region. The Complex Emergency Database (CEDAT) was set up in order to make best use of the collective force of these surveys. Functioning as a central repository, it can provide valuable information on trends and patterns of mortality and nutrition indicators from conflict-affected communities. Given their high spatial resolution and their high frequency, CEDAT data can complement official statistics in between nationwide surveys. They also provide information of the displacement status of the measured population, pointing out vulnerabilities. CEDAT is hosted at the Centre for Research on the Epidemiology of Disasters, University of Louvain. It runs on voluntary agreements between the survey implementer and the CEDAT team. To date, it contains 3309 surveys from 51 countries, and is a unique repository of such data.     

Garden of Eden or Desert Exile: The Mousterian of Hummal in context

Our view of MP cultural variability is blurred by site-specific problems as well as inadequate research concepts. The former are inherent in current fieldwork methodology and in the archaeological record itself. Excavation of Palaeolithic sites generally catches only parts of the entire archaeological record and thus leaves us with the sample size problem. Moreover, resolution of the archaeological record is often limited by the palimpsest problem which is especially given in spatially restricted sites (e.g. caves) coupled with a low sedimentation rate. Many research concepts not only neglect the resolution problem but also lack the consideration of scale when it comes to archaeological interpretation. Our aim is not to reinterpret the Levantine Middle Palaeolithic in the light of these challenges as this is outside the scope of this paper. Archaeological resolution and scale are nevertheless taken as guidelines for the integration of the Hummal Mousterian in a broader context. In doing so, we give a short review of current knowledge and show how a scale-sensitive approach can inform us about various aspects of the Levantine Middle Palaeolithic.     

On the Recombination Rate Estimation in the Presence of Population Substructure

As recombination events are not uniformly distributed along the human genome, the estimation of fine-scale recombination maps, e.g. HapMap Project, has been one of the major research endeavors over the last couple of years. For simulation studies, these estimates provide realistic reference scenarios to design future study and to develop novel methodology. To achieve a feasible framework for the estimation of such recombination maps, existing methodology uses sample probabilities for a two-locus model with recombination, with recent advances allowing for computationally fast implementations. In this work, we extend the existing theoretical framework for the recombination rate estimation to the presence of population substructure. We show under which assumptions the existing methodology can still be applied. We illustrate our extension of the methodology by an extensive simulation study.     

The Next Direction for Primatology? A Commentary on Setchell (2013)

Primatologists were asked to submit their “ideas for the Big Questions that remain unanswered in Primatology” and, from this, Setchell (2013) grouped the 170 responses into 11 broad themes. This exercise created a valuable tool that can help primatologists identify both the “missing gaps” and current broad overarching themes within our field. In this commentary, we offer our perspective on the methodology and results of this survey. By considering the 11 themes more holistically, primatologists can more easily address a broader range of questions, methods, and outcomes for their research endeavors and conservation efforts. Ultimately, the results of this survey should enable researchers and policymakers to recognize gaps in our knowledge and plan how to proceed with new research initiatives and funding applications. The identified themes should also provide a reference point for new avenues of investigation, and we are hopeful that this list can encourage interdisciplinary research if primatologists consider the overlaps across the themes. However, as Setchell noted, as some key areas of research were omitted from the list, the 11 themes should be used as a tool for guidance in expanding our research horizons and not as a template for the minimum of what is required.     

Reproductive behaviour indicates specificity in resource use: phylogenetic examples from temperate and tropical insects

Specificity (= the degree of ecological specialisation) is one of the fundamental concepts of the science of ecology. Ambiguities on how to define and measure specificity have however complicated respective research efforts. Here we propose that, in insects, a behavioural trait – adult oviposition latency in captivity without a favourable host plant – correlates with a species’ specificity in larval host use. In the absence of a suitable host, monophagous insects are expected to wait for a long time before commencing oviposition, with the long waiting time corresponding to careful host location behaviour in nature. Polyphagous insects, in contrast, should be selected for an increased oviposition rate at the expense of the quality of oviposition substrate encountered and will on average have a short latency time. Using experimentally derived data on oviposition latency, we performed a phylogenetically informed analysis based on Bayesian inference to show that this variable correlates with host specificity (larval diet breadth) in a sample of north European species of geometrid moths. A closely related index – the probability to lay any eggs on an unfavourable substrate – shows an analogous pattern. To provide an example of how these indices can be applied, we compare our sample of geometrid moths from northern Europe with a sample from equatorial Africa. A comparative analysis based on an original phylogenetic reconstruction found no differences between the two study sites in parameters of oviposition behaviour. We conclude that behavioural tests can provide information about ecological interactions when the latter can not be directly recorded. Our example study also hints at the possibility that host specificity of herbivores is not necessarily higher in a tropical region compared to a temperate one.     

Explorations in statistics: standard deviations and standard errors

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This series in Advances in Physiology Education provides an opportunity to do just that: we will investigate basic concepts in statistics using the free software package R. Because this series uses R solely as a vehicle with which to explore basic concepts in statistics, I provide the requisite R commands. In this inaugural paper we explore the essential distinction between standard deviation and standard error: a standard deviation estimates the variability among sample observations whereas a standard error of the mean estimates the variability among theoretical sample means. If we fail to report the standard deviation, then we fail to fully report our data. Because it incorporates information about sample size, the standard error of the mean is a misguided estimate of variability among observations. Instead, the standard error of the mean provides an estimate of the uncertainty of the true value of the population mean.     

Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones

Background

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

Aim of review

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

Key scientific concepts of review

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze–thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

     

Between (Racial) Groups and a Hard Place: An Exploration of Social Science Approaches to Race and Genetics, 2000–2014

As the social sciences expand their involvement in genetic and genomic research, more information is needed to understand how theoretical concepts are applied to genetic data found in social surveys. Given the layers of complexity of studying race in relation to genetics and genomics, it is important to identify the varying approaches used to discuss and operationalize race and identity by social scientists. The present study explores how social scientists have used race, ethnicity, and ancestry in studies published in four social science journals from 2000 to 2014. We identify not only how race, ethnicity, and ancestry are classified and conceptualized in this growing area of research, but also how these concepts are incorporated into the methodology and presentation of results, all of which structure the discussion of race, identity, and inequality. This research indicates the slippage between concepts, classifications, and their use by social scientists in their genetics-related research. The current study can assist social scientists with clarifying their use and interpretations of race and ethnicity with the incorporation of genetic data, while limiting possible misinterpretations of the complexities of the connection between genetics and the social world.     

Mapping from heterogeneous biodiversity monitoring data sources

Field monitoring can vary from simple volunteer opportunistic observations to professional standardised monitoring surveys, leading to a trade-off between data quality and data collection costs. Such variability in data quality may result in biased predictions obtained from species distribution models (SDMs). We aimed to identify the limitations of different monitoring data sources for developing species distribution maps and to evaluate their potential for spatial data integration in a conservation context. Using Maxent, SDMs were generated from three different bird data sources in Catalonia, which differ in the degree of standardisation and available sample size. In addition, an alternative approach for modelling species distributions was applied, which combined the three data sources at a large spatial scale, but then downscaling to the required resolution. Finally, SDM predictions were used to identify species richness and high quality areas (hotspots) from different treatments. Models were evaluated by using high quality Atlas information. We show that both sample size and survey methodology used to collect the data are important in delivering robust information on species distributions. Models based on standardized monitoring provided higher accuracy with a lower sample size, especially when modelling common species. Accuracy of models from opportunistic observations substantially increased when modelling uncommon species, giving similar accuracy to a more standardized survey. Although downscaling data through a SDM approach appears to be a useful tool in cases of data shortage or low data quality and heterogeneity, it will tend to overestimate species distributions. In order to identify distributions of species, data with different quality may be appropriate. However, to identify biodiversity hotspots high quality information is needed.     

Methodology for developing gate-to-gate Life cycle inventory information

Life Cycle Assessment (LCA) methodology evaluates holistically the environmental consequences of a product system or activity, by quantifying the energy and materials used, the wastes released to the environment, and assessing the environmental impacts of those energy, materials and wastes. Despite the international focus on environmental impact and LCA, the quality of the underlying life cycle inventory data is at least as, if not more, important than the more qualitative LCA process. This work presents an option to generate gate-to-gate life cycle information of chemical substances, based on a transparent methodology of chemical engineering process design (an ab initio approach). In the broader concept of a Life Cycle Inventory (LCI), the information of each gate-to-gate module can be linked accordingly in a production chain, including the extraction of raw materials, transportation, disposal, reuse, etc. to provide a full cradle to gate evaluation. The goal of this article is to explain the methodology rather than to provide a tutorial on the techniques used. This methodology aims to help the LCA practitioner to obtain a fair and transparent estimate of LCI data when the information is not readily available from industry or literature. Results of gate-to-gate life cycle information generated using the cited methodology are presented as a case study. It has been our experience that both LCI and LCA information provide valuable means of understanding the net environmental consequence of any technology. The LCI information from this methodology can be used more directly in exploring engineering and chemistry changes to improve manufacturing processes. The LCA information can be used to set broader policy and to look at more macro improvements for the environment.     

Blood Collection Procedure of Laboratory Primates: A Neglected Variable in Biomedical Research

A survey of 75 biomedical articles dealing with stress-dependent blood parameters in caged primates revealed that the conditions under which blood collection occurred were in most cases described either not at all or so haphazardly that it would be impossible to determine if humane handling procedures were used and basic principles of scientific methodology applied. These findings were unexpected because there is ample scientific evidence not only that stress-sensitive research data are influenced by traditional blood sampling procedures, but also that those data-biasing effects can be avoided. If dependent variables of the blood collection procedure are not controlled, data variability will increase, automatically increasing the number of animals needed for statistical analysis. For ethical and scientific reasons, it was recommended that editors of biomedical journals require authors to provide sufficient information of the blood collection--and, when applicable, the sedative injection--procedure to ensure that the experiment was done with the smallest number of animals possible to achieve statistical significance and that the investigation can be replicated reliably in another laboratory and the research data interpreted with reasonable accuracy.     

Where Next? Group Coordination and Collective Decision Making by Primates

Primate groups need to remain coordinated in their activities and collectively decide when and where to travel if they are to accrue the benefits and minimize the costs of sociality. The achievement of coordinated activity and group decision making therefore has important implications for individual survival and reproduction. The aim of this special issue is to bring together a collection of empirical, theoretical, and commentary articles by primatologists studying this rapidly expanding topic. In this article, we introduce the contributions within the special issue and provide a background to the topic. We begin by focusing on decisions that involve a collective transition between a resting and a moving state, a transition we term making the move. We examine whether specific predeparture behaviors seen during transitions represent intentional processes or more simple response facilitation. Next we classify decisions according to the contribution of individual group members, and describe how, and why, certain individuals can have a disproportionate influence over group-mates?? behavior. We then review how primate groups make decisions on the move. In particular, we focus on how variability in group size and spatial organization helps or hinders information transmission and coordination. We end with a discussion of new tools and methodology that will allow future investigators to address some outstanding questions in primate coordination and decision-making research. We conclude that a better integration of concepts and terminology, along with a focus on how individuals integrate environmental and social information, will be critical to developing a satisfactory understanding of collective patterns of behavior in primate systems.     

当地生态知识在海洋哺乳动物研究中的应用与展望

当地生态知识(local ecological knowledge,LEK)是指人们在长期的生活体验和生产实践中,获得的有关周边环境、生物资源及其相互关系的经验和知识。近几十年来,LEK在海洋哺乳动物研究中得到了广泛的应用和发展,尤其是在基础相对薄弱的发展中国家或地区,LEK作为一种低成本、短周期且适合大范围调查的手段,日益成为研究人员获取目标物种生态信息的重要渠道。LEK与野外实地调查等获得的数据可以互补,从而为评估海洋哺乳动物的生存状况和环境变化提供多维度的信息来源;该方法还往往是了解目标物种生存状况历史变动的有效手段,回答传统方法很难甚至无法回答的科学问题,如目标物种在较长时间尺度上的生态信息历史变化趋势等。本文介绍了LEK的定义及特征、海洋哺乳动物及其传统生态调查方法、LEK在海洋哺乳动物中的研究进展、应用LEK开展海洋哺乳动物研究的步骤,还讨论了LEK在我国海洋哺乳动物研究中的应用前景和推广价值,旨在为今后相关研究提供参考资料。     

Complete allocation sampling: an efficient and easily implemented adaptive sampling design

Adaptive sampling designs are becoming increasingly popular in environmental science, particularly for surveying rare and aggregated populations. An adaptive sample is one in which the survey design is modified, or adapted, in some way on the basis of information gained during the survey. There are many different adaptive survey designs that can be used to estimate animal and plant abundance. In adaptive cluster sampling, additional sample effort is allocated during the survey to the immediate neighborhood in which the species is found. In adaptive stratified sampling, additional sample effort is allocated during the survey to strata of high abundance. The appealing feature of these adaptive designs is that the field biologist gets to do what innately seems sensible when working with rare and aggregated populations—field effort is targeted around where the species is observed in the first wave of the survey. However, there are logistical challenges of applying this principle of targeted field effort while remaining in the framework of probability-based sampling. We propose a simplified adaptive survey design that incorporates both targeting field effort and being logistically feasible. We show with a case study population of rockfish that complete allocation stratified sampling is a very efficient design.     

基于GIS的外来入侵植物调查规划与外业实施

前期规划对外来入侵植物野外调查工作的顺利开展至关重要。本文将基于GIS的野外调查规划方法和入侵植物调查技术规范相结合, 利用地图资源丰富、分析功能强大的LocaSpace Viewer和奥维互动地图, 形成有针对性的野外调查规划方案。具体操作流程包括: (1)借助LocaSpace Viewer软件集成的高分辨率遥感数据和地理标注数据选取调查区域; (2)根据调查规范, 通过该软件的空间分析和地理要素编辑功能, 规划调查地理网格、调查点、样地、标准地和样方, 运用KML空间数据格式存储和分享调查规划信息; (3)在外业实施中使用移动版奥维互动地图软件的数据管理和导航功能实现调查规划信息的导入、定位和导航。通过在福建、广西和云南三省开展技术方法的实地应用与对比实验发现, 运用该方案的外业实施能够达到日平均调查6个样点, 采集调查数据80多条, 直线调查距离180 km, 调查点导航精度大于15 m。对比实验表明基于规划调查比未规划调查在时间利用效率上提高1倍, 工作效率得到显著提升。该方案为外来入侵植物的发生和危害等基础性调查工作提供了高效的技术支撑, 为生物多样性野外调查规划提供了参考方案。     

Multiscale Molecular Visualization

We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basics and describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the general structure of the following survey. First, we discuss methods that support the visual analysis of molecular dynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the second part, we survey multiscale approaches that support the design, analysis, and manipulation of DNA nanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, and navigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches that support interactive exploration within large structural biology assemblies up to the size of bacterial cells. We describe fundamental rendering techniques as well as approaches for element instantiation, visibility management, visual guidance, camera control, and support of depth perception. We close the survey with a brief listing of important tools that implement many of the discussed approaches and a conclusion that provides some research challenges in the field.     

Multidimensional Mapping Method Using an Arrayed Sensing System for Cross-Reactivity Screening

When measuring chemical information in biological fluids, challenges of cross-reactivity arise, especially in sensing applications where no biological recognition elements exist. An understanding of the cross-reactions involved in these complex matrices is necessary to guide the design of appropriate sensing systems. This work presents a methodology for investigating cross-reactions in complex fluids. First, a systematic screening of matrix components is demonstrated in buffer-based solutions. Second, to account for the effect of the simultaneous presence of these species in complex samples, the responses of buffer-based simulated mixtures of these species were characterized using an arrayed sensing system. We demonstrate that the sensor array, consisting of electrochemical sensors with varying input parameters, generated differential responses that provide synergistic information of sample. By mapping the sensing array response onto multidimensional heat maps, characteristic signatures were compared across sensors in the array and across different matrices. Lastly, the arrayed sensing system was applied to complex biological samples to discern and match characteristic signatures between the simulated mixtures and the complex sample responses. As an example, this methodology was applied to screen interfering species relevant to the application of schizophrenia management. Specifically, blood serum measurement of antipsychotic clozapine and antioxidant species can provide useful information regarding therapeutic efficacy and psychiatric symptoms. This work proposes an investigational tool that can guide multi-analyte sensor design, chemometric modeling and biomarker discovery.     

Personality research with non-human primates: theoretical formulation and methods

Since the earliest periods of primatology study, researchers have been aware of animals’ consistent individual differences in behavior or personality. Many papers have been published on this subject, but they lacked a common theoretical and methodological background. The present work is an attempt to provide such theoretical and methodological foundations to this field of biological science. In the theoretical formulation section, “biological study of personality” is first derived as an extension of the ethology paradigm, and non-human primate personality research is subsequently characterized as its strategic component. In the methodology section, brief reviews and discussions are presented on subjective and objective personality assessment methods with non-human primates with a reference to the reliability and validity concepts in human psychometrics. The work provides a theoretical framework and methodological suggestions for non-human primate personality research.