76 research outputs found

    Evolutionary relationships between Rhynchosporium lolii sp. nov. and other Rhynchosporium species on grass.

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    Copyright: 2013 King et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedThe fungal genus Rhynchosporium (causative agent of leaf blotch) contains several host-specialised species, including R. commune (colonising barley and brome-grass), R. agropyri (couch-grass), R. secalis (rye and triticale) and the more distantly related R. orthosporum (cocksfoot). This study used molecular fingerprinting, multilocus DNA sequence data, conidial morphology, host range tests and scanning electron microscopy to investigate the relationship between Rhynchosporium species on ryegrasses, both economically important forage grasses and common wild grasses in many cereal growing areas, and other plant species. Two different types of Rhynchosporium were found on ryegrasses in the UK. Firstly, there were isolates of R. commune that were pathogenic to both barley and Italian ryegrass. Secondly, there were isolates of a new species, here named R. lolii, that were pathogenic only to ryegrass species. R. lolii was most closely related to R. orthosporum, but exhibited clear molecular, morphological and host range differences. The species was estimated to have diverged from R. orthosporum ca. 5735 years before the present. The colonisation strategy of all of the different Rhynchosporium species involved extensive hyphal growth in the sub-cuticular regions of the leaves. Finally, new species-specific PCR diagnostic tests were developed that could distinguish between these five closely related Rhynchosporium species.Peer reviewedFinal Published versio

    Potential Savings of Harmonising Hospital and Community Formularies for Chronic Disease Medications Initiated in Hospital

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    Hospitals in Canada manage their formularies independently, yet many inpatients are discharged on medications which will be purchased through publicly-funded programs. We sought to determine how much public money could be saved on chronic medications if hospitals promoted the initiation of agents with the lowest outpatient formulary prices.We used administrative databases for the province of Ontario to identify patients initiated on a proton pump inhibitor (PPI), angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) following hospital admission from April 1(st) 2008-March 31(st) 2009. We assessed the cost to the Ontario Drug Benefit Program (ODB) over the year following initiation and determined the cost savings if prescriptions were substituted with the least expensive agent in each class.The cost for filling all PPI, ACE inhibitor and ARB prescriptions was 2.48million, 2.48 million, 968 thousand and 325thousandrespectively.Substitutingtheleastexpensiveagentcouldhavesaved325 thousand respectively. Substituting the least expensive agent could have saved 1.16 million (47%) for PPIs, 162thousand(17162 thousand (17%) for ACE inhibitors and 14 thousand (4%) for ARBs over the year following discharge.In a setting where outpatient prescriptions are publicly funded, harmonising outpatient formularies with inpatient therapeutic substitution resulted in modest cost savings and may be one way to control rising pharmaceutical costs

    Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

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    The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships

    On computational approaches for size-and-shape distributions from sedimentation velocity analytical ultracentrifugation

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    Sedimentation velocity analytical ultracentrifugation has become a very popular technique to study size distributions and interactions of macromolecules. Recently, a method termed two-dimensional spectrum analysis (2DSA) for the determination of size-and-shape distributions was described by Demeler and colleagues (Eur Biophys J 2009). It is based on novel ideas conceived for fitting the integral equations of the size-and-shape distribution to experimental data, illustrated with an example but provided without proof of the principle of the algorithm. In the present work, we examine the 2DSA algorithm by comparison with the mathematical reference frame and simple well-known numerical concepts for solving Fredholm integral equations, and test the key assumptions underlying the 2DSA method in an example application. While the 2DSA appears computationally excessively wasteful, key elements also appear to be in conflict with mathematical results. This raises doubts about the correctness of the results from 2DSA analysis

    Challenge clusters facing LCA in environmental decision-making—what we can learn from biofuels

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    Purpose Bioenergy is increasingly used to help meet greenhouse gas (GHG) and renewable energy targets. However, bioenergy’s sustainability has been questioned, resulting in increasing use of life cycle assessment (LCA). Bioenergy systems are global and complex, and market forces can result in significant changes, relevant to LCA and policy. The goal of this paper is to illustrate the complexities associated with LCA, with particular focus on bioenergy and associated policy development, so that its use can more effectively inform policymakers. Methods The review is based on the results from a series of workshops focused on bioenergy life cycle assessment. Expert submissions were compiled and categorized within the first two workshops. Over 100 issues emerged. Accounting for redundancies and close similarities in the list, this reduced to around 60 challenges, many of which are deeply interrelated. Some of these issues were then explored further at a policyfacing workshop in London, UK. The authors applied a rigorous approach to categorize the challenges identified to be at the intersection of biofuels/bioenergy LCA and policy. Results and discussion The credibility of LCA is core to its use in policy. Even LCAs that comply with ISO standards and policy and regulatory instruments leave a great deal of scope for interpretation and flexibility. Within the bioenergy sector, this has led to frustration and at times a lack of obvious direction. This paper identifies the main challenge clusters: overarching issues, application and practice and value and ethical judgments. Many of these are reflective of the transition from application of LCA to assess individual products or systems to the wider approach that is becoming more common. Uncertainty in impact assessment strongly influences planning and compliance due to challenges in assigning accountability, and communicating the inherent complexity and uncertainty within bioenergy is becoming of greater importance. Conclusions The emergence of LCA in bioenergy governance is particularly significant because other sectors are likely to transition to similar governance models. LCA is being stretched to accommodate complex and broad policy-relevant questions, seeking to incorporate externalities that have major implications for long-term sustainability. As policy increasingly relies on LCA, the strains placed on the methodology are becoming both clearer and impedimentary. The implications for energy policy, and in particular bioenergy, are large

    First molecular-cytogenetic characterization of Fanconi anemia fragile sites in primary lymphocytes of FA-D2 patients in different stages of the disease

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    Background: Fanconi anemia (FA) is a chromosomal instability syndrome characterized by increased frequency of chromosomal breakages, chromosomal radial figures and accelerated telomere shortening. In this work we performed detailed molecular-cytogenetic characterization of breakpoints in primary lymphocytes of FA-D2 patients in different stages of the disease using fluorescent in situ hybridization. Results: We found that chromosomal breakpoints co-localize on the molecular level with common fragile sites, whereas their distribution pattern depends on the severity of the disease. Telomere quantitative fluorescent in situ hybridization revealed that telomere fusions and radial figures, especially radials which involve telomere sequences are the consequence of critically shortened telomeres that increase with the disease progression and could be considered as a predictive parameter during the course of the disease. Sex chromosomes in FA cells are also involved in radial formation indicating that specific X chromosome regions share homology with autosomes and also could serve as repair templates in resolving DNA damage. Conclusions: FA-D2 chromosomal breakpoints co-localize with common fragile sites, but their distribution pattern depends on the disease stage. Telomere fusions and radials figures which involve telomere sequences are the consequence of shortened telomeres, increase with disease progression and could be of predictive value
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