Habitat structure: a fundamental concept and framework for urban soil ecology

Habitat structure is defined as the composition and arrangement of physical matter at a location. Although habitat structure is the physical template underlying ecological patterns and processes, the concept is relatively unappreciated and underdeveloped in ecology. However, it provides a fundamental concept for urban ecology because human activities in urban ecosystems are often targeted toward management of habitat structure. In addition, the concept emphasizes the fine-scale, on-the-ground perspective needed in the study of urban soil ecology. To illustrate this, urban soil ecology research is summarized from the perspective of habitat structure effects. Among the key conclusions emerging from the literature review are: (1) habitat structure provides a unifying theme for multivariate research about urban soil ecology; (2) heterogeneous urban habitat structures influence soil ecological variables in different ways; (3) more research is needed to understand relationships among sociological variables, habitat structure patterns and urban soil ecology. To stimulate urban soil ecology research, a conceptual framework is presented to show the direct and indirect relationships among habitat structure and ecological variables. Because habitat structure serves as a physical link between sociocultural and ecological systems, it can be used as a focus for interdisciplinary and applied research (e.g., pest management) about the multiple, interactive effects of urbanization on the ecology of soils

Variable DNA methylation in neonates mediates the association between prenatal smoking and birth weight

There is great interest in the role epigenetic variation induced by non-genetic exposures may play in the context of health and disease. In particular, DNA methylation has previously been shown to be highly dynamic during the earliest stages of development and is influenced by in utero exposures such as maternal smoking and medication. In this study we sought to identify the specific DNA methylation differences in blood associated with prenatal and birth factors, including birth weight, gestational age and maternal smoking. We quantified neonatal methylomic variation in 1263 infants using DNA isolated from a unique collection of archived blood spots taken shortly after birth (mean = 6.08 days; s.d. = 3.24 days). An epigenome-wide association study (EWAS) of gestational age and birth weight identified 4299 and 18 differentially methylated positions (DMPs) respectively, at an experiment-wide significance threshold of p < 1 × 10-7. Our EWAS of maternal smoking during pregnancy identified 110 DMPs in neonatal blood, replicating previously reported genomic loci, including AHRR. Finally, we tested the hypothesis that DNA methylation mediates the relationship between maternal smoking and lower birth weight, finding evidence that methylomic variation at three DMPs may link exposure to outcome. These findings complement an expanding literature on the epigenomic consequences of prenatal exposures and obstetric factors, confirming a link between the maternal environment and gene regulation in neonates. This article is part of the theme issue 'Developing differences: early-life effects and evolutionary medicine'.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This study was supported by grant no. HD073978 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Environmental Health Sciences, and National Institute of Neurological Disorders and Stroke; and by the Beatrice and Samuel A. Seaver Foundation. The iPSYCH (The Lundbeck Foundation Initiative for Integrative Psychiatric Research) team acknowledges funding from The Lundbeck Foundation (grant no. R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, the European Research Council (project no: 294838), the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center. This research has been conducted using the Danish National Biobank resource, supported by the Novo Nordisk Foundation. J.M. and E.H. are supported by funding from the UK Medical Research Council (K013807).published version, accepted version, submitted versio

Elevated polygenic burden for autism is associated with differential DNA methylation at birth

This is the final version of the article. Available from BioMed Central via the DOI in this record.Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth.This study was supported by grant HD073978 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Environmental Health Sciences, and National Institute of Neurological Disorders and Stroke; and by the Beatrice and Samuel A. Seaver Foundation. We acknowledge iPSYCH and The Lundbeck Foundation for providing samples and funding. The iPSYCH (The Lundbeck Foundation Initiative for Integrative Psychiatric Research) team acknowledges funding from The Lundbeck Foundation (grant numbers R102-A9118 and R155–2014-1724), the Stanley Medical Research Institute, the European Research Council (project number 294838), the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center. This research has been conducted using the Danish National Biobank resource, supported by the Novo Nordisk Foundation. JM is supported by funding from the UK Medical Research Council (MR/K013807/1) and a Distinguished Investigator Award from the Brain & Behavior Research Foundation. The SEED study was supported by Centers for Disease Control and Prevention (CDC) Cooperative Agreements announced under the RFAs 01086, 02199, DD11–002, DD06–003, DD04–001, and DD09–002 and the SEED DNA methylation measurements were supported by Autism Speaks Award #7659 to MDF. SA was supported by the Burroughs-Wellcome Trust training grant: Maryland, Genetics, Epidemiology and Medicine (MD-GEM). The SSC was supported by Simons Foundation (SFARI) award and NIH grant MH089606, both awarded to STW

Trust in Nanotechnology? On Trust as Analytical Tool in Social Research on Emerging Technologies

Trust has become an important aspect of evaluating the relationship between lay public and technology implementation. Experiences have shown that a focus on trust provides a richer understanding of reasons for backlashes of technology in society than a mere focus of public understanding of risks and science communication. Therefore, trust is also widely used as a key concept for understanding and predicting trust or distrust in emerging technologies. But whereas trust broadens the scope for understanding established technologies with well-defined questions and controversies, it easily fails to do so with emerging technologies, where there are no shared questions, a lack of public familiarity with the technology in question, and a restricted understanding amongst social researchers as to where distrust is likely to arise and how and under which form the technology will actually be implemented. Rather contrary, ‘trust’ might sometimes even direct social research into fixed structures that makes it even more difficult for social research to provide socially robust knowledge. This article therefore suggests that if trust is to maintain its important role in evaluating emerging technologies, the approach has to be widened and initially focus not on people’s motivations for trust, but rather the object of trust it self, as to predicting how and where distrust might appear, how the object is established as an object of trust, and how it is established in relation with the public

Biodiversity Loss and the Taxonomic Bottleneck: Emerging Biodiversity Science

Human domination of the Earth has resulted in dramatic changes to global and local patterns of biodiversity. Biodiversity is critical to human sustainability because it drives the ecosystem services that provide the core of our life-support system. As we, the human species, are the primary factor leading to the decline in biodiversity, we need detailed information about the biodiversity and species composition of specific locations in order to understand how different species contribute to ecosystem services and how humans can sustainably conserve and manage biodiversity. Taxonomy and ecology, two fundamental sciences that generate the knowledge about biodiversity, are associated with a number of limitations that prevent them from providing the information needed to fully understand the relevance of biodiversity in its entirety for human sustainability: (1) biodiversity conservation strategies that tend to be overly focused on research and policy on a global scale with little impact on local biodiversity; (2) the small knowledge base of extant global biodiversity; (3) a lack of much-needed site-specific data on the species composition of communities in human-dominated landscapes, which hinders ecosystem management and biodiversity conservation; (4) biodiversity studies with a lack of taxonomic precision; (5) a lack of taxonomic expertise and trained taxonomists; (6) a taxonomic bottleneck in biodiversity inventory and assessment; and (7) neglect of taxonomic resources and a lack of taxonomic service infrastructure for biodiversity science. These limitations are directly related to contemporary trends in research, conservation strategies, environmental stewardship, environmental education, sustainable development, and local site-specific conservation. Today’s biological knowledge is built on the known global biodiversity, which represents barely 20% of what is currently extant (commonly accepted estimate of 10 million species) on planet Earth. Much remains unexplored and unknown, particularly in hotspots regions of Africa, South Eastern Asia, and South and Central America, including many developing or underdeveloped countries, where localized biodiversity is scarcely studied or described. ‘‘Backyard biodiversity’’, defined as local biodiversity near human habitation, refers to the natural resources and capital for ecosystem services at the grassroots level, which urgently needs to be explored, documented, and conserved as it is the backbone of sustainable economic development in these countries. Beginning with early identification and documentation of local flora and fauna, taxonomy has documented global biodiversity and natural history based on the collection of ‘‘backyard biodiversity’’ specimens worldwide. However, this branch of science suffered a continuous decline in the latter half of the twentieth century, and has now reached a point of potential demise. At present there are very few professional taxonomists and trained local parataxonomists worldwide, while the need for, and demands on, taxonomic services by conservation and resource management communities are rapidly increasing. Systematic collections, the material basis of biodiversity information, have been neglected and abandoned, particularly at institutions of higher learning. Considering the rapid increase in the human population and urbanization, human sustainability requires new conceptual and practical approaches to refocusing and energizing the study of the biodiversity that is the core of natural resources for sustainable development and biotic capital for sustaining our life-support system. In this paper we aim to document and extrapolate the essence of biodiversity, discuss the state and nature of taxonomic demise, the trends of recent biodiversity studies, and suggest reasonable approaches to a biodiversity science to facilitate the expansion of global biodiversity knowledge and to create useful data on backyard biodiversity worldwide towards human sustainability

Budesonide/formoterol and formoterol provide similar rapid relief in patients with acute asthma showing refractoriness to salbutamol

BACKGROUND: To compare the efficacy and safety of budesonide/formoterol (Symbicort(®)) with formoterol (Oxis(®)) in the treatment of patients with acute asthma who showed evidence of refractoriness to short-acting β(2)-agonist therapy. METHODS: In a 3 hour, randomized, double-blind study, a total of 115 patients with acute asthma (mean FEV(1 )40% of predicted normal) and a refractory response to salbutamol (mean reversibility 2% of predicted normal after inhalation of 400 μg), were randomized to receive either budesonide/formoterol (320/9 μg, 2 inhalations at t = -5 minutes and 2 inhalations at 0 minutes [total dose 1280/36 μg]) or formoterol (9 μg, 2 inhalations at t = -5 minutes and 2 inhalations at 0 minutes [total dose 36 μg]). The primary efficacy variable was the average FEV(1 )from the first intake of study medication to the measurement at 90 minutes. Secondary endpoints included changes in FEV(1 )at other timepoints and change in respiratory rate at 180 minutes. Treatment success, treatment failure and patient assessment of the effectiveness of the study medication were also measured. RESULTS: FEV(1 )increased after administration of the study medication in both treatment groups. No statistically significant difference between the treatment groups was apparent for the primary outcome variable, or for any of the other efficacy endpoints. There were no statistically significant between-group differences for treatment success, treatment failure or patient assessment of medication effectiveness. Both treatments were well tolerated. CONCLUSION: Budesonide/formoterol and formoterol provided similarly rapid relief of acute bronchoconstriction in patients with asthma who showed evidence of refractoriness to a short-acting β(2)-agonist

Farmers' attitudes and landscape change: evidence from the abandonment of terraced cultivations on Lesvos, Greece

Agricultural landscapes are the product of the interaction of the natural environment of an area and the practices of its farmers. In this paper, farmers' practices are examined in order to describe and understand processes of landscape change in terraced fields on the island of Lesvos, Greece. We examine the changes of the terraced fields of each farmer and the reasons for these changes, practices concerning the maintenance of terraces and how farmers view this landscape change. The concept of farming systems is used to link farmers' practices at the farm level with changes at the landscape level. Data come from research via questionnaires to farmers in order to record their practices, to explore changes in land use and the landscape elements and the reasons behind these changes, and finally to record their opinions on the landscape change that result. Findings indicate that although farm households in the case study areas depend on farming incomes by very different degrees, they employ similar cultivation and landscape management practices. At the same time, "hobby" farm households may be more prone to abandonment of fields and negligence of landscape elements (here terraces)

A polygenic resilience score moderates the genetic risk for schizophrenia.

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531–538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known “polygenic resilience score” that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder

Application of Permutation Genetic Algorithm for Sequential Model Building–Model Validation Design of Experiments

YesThe work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient Design of Experiment (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to support an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of Model Building–Model Validation (MB-MV) sequences, by generating optimal infill sets of test points as OLH DoEs, that preserve good space filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB-MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back (SHCB) function, as well as the Gasoline Direct Injection (GDI) engine steady state engine mapping problem that motivated this research. The case studies show that the algorithm is effective at delivering quasi-orthogonal space-filling DoEs with good properties even after several MB-MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, also is that significant reduction in the effort and cost of testing can be achieved.The research work presented in this paper was funded by the UK Technology Strategy Board (TSB) through the Carbon Reduction through Engine Optimization (CREO) project

Selecting Forecasting Methods

I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods