22 research outputs found

    Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus

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    <p>Abstract</p> <p>Background</p> <p>Hyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci.</p> <p>Methods</p> <p>Both Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]).</p> <p>Results</p> <p>Different patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations.</p> <p>Conclusion</p> <p>Combining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.</p

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    Modeling tropical montane forest biodiversity – The potential of multispectral remote sensing

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    In this thesis, the potential of multispectral remote sensing data to model taxonomic and functional aspects of biodiversity in a tropical mountain rainforest in southern Ecuador was analyzed. In particular, vegetation indices from multispectral reflectances and their textural information were used. For this purpose (i) different taxonomic groups and diversity measures (e.g. alpha/beta diversity) were investigated, (ii) a comparison to topographic metrics was made, and (iii) sensor data with high and moderate spatial resolution were considered. The three studies showed that the potential of multispectral remote sensing is closely related to the environmental filters of the respective biodiversity measures, which are responsible for spatial patterns of taxonomic and functional diversity. The taxon-specific resource requirements and their specific adaptation strategies to the environment are decisive for the importance of the predictors used here. In particular texture metrics, as proxies for habitat structure, explained a high proportion of diversity in addition to topographic metrics. However, their potential depended both on the spatial resolution of the multispectral sensor and on the complexity of the texture calculation. The robustness of multispectral image textures as an important driver of taxonomic and functional diversity should therefore be further investigated

    Modeling tropical montane forest biodiversity – The potential of multispectral remote sensing

    No full text
    In this thesis, the potential of multispectral remote sensing data to model taxonomic and functional aspects of biodiversity in a tropical mountain rainforest in southern Ecuador was analyzed. In particular, vegetation indices from multispectral reflectances and their textural information were used. For this purpose (i) different taxonomic groups and diversity measures (e.g. alpha/beta diversity) were investigated, (ii) a comparison to topographic metrics was made, and (iii) sensor data with high and moderate spatial resolution were considered. The three studies showed that the potential of multispectral remote sensing is closely related to the environmental filters of the respective biodiversity measures, which are responsible for spatial patterns of taxonomic and functional diversity. The taxon-specific resource requirements and their specific adaptation strategies to the environment are decisive for the importance of the predictors used here. In particular texture metrics, as proxies for habitat structure, explained a high proportion of diversity in addition to topographic metrics. However, their potential depended both on the spatial resolution of the multispectral sensor and on the complexity of the texture calculation. The robustness of multispectral image textures as an important driver of taxonomic and functional diversity should therefore be further investigated

    Mapping canopy traits over Québec using airborne and spaceborne imaging spectroscopy

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    Abstract The advent of new spaceborne imaging spectrometers offers new opportunities for ecologists to map vegetation traits at global scales. However, to date most imaging spectroscopy studies exploiting satellite spectrometers have been constrained to the landscape scale. In this paper we present a new method to map vegetation traits at the landscape scale and upscale trait maps to the continental level, using historical spaceborne imaging spectroscopy (Hyperion) to derive estimates of leaf mass per area, nitrogen, and carbon concentrations of forests in Québec, Canada. We compare estimates for each species with reference field values and obtain good agreement both at the landscape and continental scales, with patterns consistent with the leaf economic spectrum. By exploiting the Hyperion satellite archive to map these traits and successfully upscale the estimates to the continental scale, we demonstrate the great potential of recent and upcoming spaceborne spectrometers to benefit plant biodiversity monitoring and conservation efforts
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