Oceans and Human Health: A Rising Tide of Challenges and Opportunities for Europe

The European Marine Board recently published a position paper on linking oceans and human health as a strategic research priority for Europe. With this position paper as a reference, the March 2014 Cornwall Oceans and Human Health Workshop brought together key scientists, policy makers, funders, business, and non governmental organisations from Europe and the US to review the recent interdisciplinary and cutting edge research in oceans and human health specifically the growing evidence of the impacts of oceans and seas on human health and wellbeing (and the effects of humans on the oceans). These impacts are a complex mixture of negative influences (e.g. from climate change and extreme weather to harmful algal blooms and chemical pollution) and beneficial factors (e.g. from natural products including seafood to marine renewable energy and wellbeing from interactions with coastal environments). Integrated approaches across disciplines, institutions, and nations in science and policy are needed to protect both the oceans and human health and wellbeing now and in the future

ProRepeat: an integrated repository for studying amino acid tandem repeats in proteins

ProRepeat (http://prorepeat.bioinformatics.nl/) is an integrated curated repository and analysis platform for in-depth research on the biological characteristics of amino acid tandem repeats. ProRepeat collects repeats from all proteins included in the UniProt knowledgebase, together with 85 completely sequenced eukaryotic proteomes contained within the RefSeq collection. It contains non-redundant perfect tandem repeats, approximate tandem repeats and simple, low-complexity sequences, covering the majority of the amino acid tandem repeat patterns found in proteins. The ProRepeat web interface allows querying the repeat database using repeat characteristics like repeat unit and length, number of repetitions of the repeat unit and position of the repeat in the protein. Users can also search for repeats by the characteristics of repeat containing proteins, such as entry ID, protein description, sequence length, gene name and taxon. ProRepeat offers powerful analysis tools for finding biological interesting properties of repeats, such as the strong position bias of leucine repeats in the N-terminus of eukaryotic protein sequences, the differences of repeat abundance among proteomes, the functional classification of repeat containing proteins and GC content constrains of repeats’ corresponding codons

Non-state actors in hybrid global climate governance: justice, legitimacy, and effectiveness in a post-Paris era

In this article, we outline the multifaceted roles played by non-state actors within the United Nations Framework Convention on Climate Change and place this within the wider landscape of global climate governance. In doing so, we look at both the formation and aftermath of the 2015 Paris Agreement. We argue that the Paris Agreement cements an architecture of hybrid multilateralism that enables and constrains non-state actor participation in global climate governance. We flesh out the constitutive features of hybrid multilateralism, enumerate the multiple positions non-state actors may employ under these conditions, and contend that non-state actors will play an increasingly important role in the post-Paris era. To substantiate these claims, we assess these shifts and ask how non-state actors may affect the legitimacy, justice, and effectiveness of the Paris Agreement

Comparative Expression Profiling of Leishmania: Modulation in Gene Expression between Species and in Different Host Genetic Backgrounds

The single-celled parasite Leishmania, transmitted by sand flies in more than 88 tropical and sub-tropical countries globally, infects man and other mammals, causing a spectrum of diseases called the leishmaniases. Over 12 million people are currently infected worldwide with 2 million new cases reported each year. The type of leishmaniasis that develops in the mammalian host is dependent on the species of infecting parasite and the immune response to infection (that can be influenced by host genetic variation). Our research is focused on identifying parasite factors that contribute to pathogenicity in the host and understanding how these might differ between parasite species that give rise to the different clinical forms of leishmaniasis. Molecules of this type might lead to new therapeutic tools in the longer term. In this paper, we report a comparative analysis of gene expression profiles in three Leishmania species that give rise to different types of disease, focusing on the intracellular stages that reside in mammalian macrophages. Our results show that there are only a small number of differences between these parasite species, with host genetics playing only a minor role in influencing the parasites' response to their intracellular habitat. These small changes may be significant, however, in determining the clinical outcome of infection

An analysis of single amino acid repeats as use case for application specific background models

Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and feasible in a challenging sequence analysis situation

Coxsackie-adenovirus receptor expression is enhanced in pancreas from patients with type 1 diabetes

Objectives: One of the theories connecting enterovirus (EV) infection of human islets with type 1 diabetes (T1D) is the development of a fertile field in the islets. This implies induction of appropriate proteins for the viral replication such as the coxsackie–adenovirus receptor (CAR). The aim of this study was to investigate to what extent CAR is expressed in human islets of Langerhans, and what conditions that would change the expression. Design: Immunohistochemistry for CAR was performed on paraffin-embedded pancreatic tissue from patients with T1D (n=9 recent onset T1D, n=4 long-standing T1D), islet autoantibody-positive individuals (n=14) and non-diabetic controls (n=24) individuals. The expression of CAR was also examined by reverse transcription PCR on microdissected islets (n=5), exocrine tissue (n=5) and on explanted islets infected with EV or exposed to chemokines produced by EV-infected islet cells. Results: An increased frequency of patients with T1D and autoantibody-positive individuals expressed CAR in the pancreas (p<0.039). CAR staining was detected more frequently in pancreatic islets from patients with T1D and autoantibody-positive subjects (15/27) compared with (6/24) non-diabetic controls (p<0.033). Also in explanted islets cultured in UV-treated culture medium from coxsackievirus B (CBV)-1-infected islets, the expression of the CAR gene was increased compared with controls. Laser microdissection of pancreatic tissue revealed that CAR expression was 10-fold higher in endocrine compared with exocrine cells of the pancreas. CAR was also expressed in explanted islets and the expression level decreased with time in culture. CBV-1 infection of explanted islets clearly decreased the expression of CAR (p<0.05). In contrast, infection with echovirus 6 did not affect the expression of CAR. Conclusions: CAR is expressed in pancreatic islets of patients with T1D and the expression level of CAR is increased in explanted islets exposed to proinflammatory cytokines/chemokines produced by infected islets. T1D is associated with increased levels of certain chemokines/cytokines in the islets and this might be the mechanism behind the increased expression of CAR in TID islets