20 resultados para data integration


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Bioenergy is a key component of the European Union long term energy strategy across all sectors, with a target contribution of up to 14% of the energy mix by 2020. It is estimated that there is the potential for 1TWh of primary energy from biogas per million persons in Europe, derived from agricultural by-products and waste. With an agricultural sector that accounts for 75% of land area and a large number of advanced engineering firms, Northern Ireland is a region with considerable potential for an integrated biogas industry. Northern Ireland is also heavily reliant on imported fossil fuels. Despite this, the industry is underdeveloped and there is a need for a collaborative approach from research, business and policy-makers across all sectors to optimise Northern Ireland’s abundant natural resources. ‘Developing Opportunities in Bio-Energy’ (i.e. Do Bioenergy) is a recently completed project that involved both academic and specialist industrial partners. The aim was to develop a biogas research action plan for 2020 to define priorities for intersectoral regional development, co-operation and knowledge transfer in the field of production and use of biogas. Consultations were held with regional stakeholders and working groups were established to compile supporting data, decide key objectives and implementation activities. Within the context of this study it was found that biogas from feedstocks including grass, agricultural slurry, household and industrial waste have the potential to contribute from 2.5% to 11% of Northern Ireland’s total energy consumption. The economics of on-farm production were assessed, along with potential markets and alternative uses for biogas in sectors such as transport, heat and electricity. Arising from this baseline data, a Do Bioenergy was developed. The plan sets out a strategic research agenda, and details priorities and targets for 2020. The challenge for Northern Ireland is how best to utilise the biogas – as electricity, heat or vehicle fuel and in what proportions. The research areas identified were: development of small scale solutions for biogas production and use; solutions for improved nutrient management; knowledge supporting and developing the integration of biogas into the rural economy; and future crops and bio-based products. The human resources and costs for the implementation were estimated as 80 person-years and £25 million respectively. It is also clear that the development of a robust bio-gas sector requires some reform of the regulatory regime, including a planning policy framework and a need to address social acceptance issues. The Action Plan was developed from a regional perspective but the results may be applicable to other regions in Europe and elsewhere. This paper presents the methodology, results and analysis, and discussion and key findings of the Do Bioenergy report for Northern Ireland.

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BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

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We consider the problem of regulating the rate of harvesting a natural resource, taking account of the wider system represented by a set of ecological and economic indicators, given differing stakeholder priorities. This requires objective and transparent decision making to show how indicators impinge on the resulting regulation decision. We offer a new scheme for combining indicators, derived from assessing the suitability of lowering versus not lowering the harvest rate based on indicator values relative to their predefined reference levels. Using the practical example of fisheries management under an “ecosystem approach,” we demonstrate how different stakeholder views can be quantitatively represented by weighting sets applied to these comparisons. Using the scheme in an analysis of historical data from the Celtic Sea fisheries, we find great scope for negotiating agreement among disparate stakeholders.

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BACKGROUND: Healthcare integration is a priority in many countries, yet there remains little direction on how to systematically evaluate this construct to inform further development. The examination of community-based palliative care networks provides an ideal opportunity for the advancement of integration measures, in consideration of how fundamental provider cohesion is to effective care at end of life.

AIM: This article presents a variable-oriented analysis from a theory-based case study of a palliative care network to help bridge the knowledge gap in integration measurement.

DESIGN: Data from a mixed-methods case study were mapped to a conceptual framework for evaluating integrated palliative care and a visual array depicting the extent of key factors in the represented palliative care network was formulated.

SETTING/PARTICIPANTS: The study included data from 21 palliative care network administrators, 86 healthcare professionals, and 111 family caregivers, all from an established palliative care network in Ontario, Canada.

RESULTS: The framework used to guide this research proved useful in assessing qualities of integration and functioning in the palliative care network. The resulting visual array of elements illustrates that while this network performed relatively well at the multiple levels considered, room for improvement exists, particularly in terms of interventions that could facilitate the sharing of information.

CONCLUSION: This study, along with the other evaluative examples mentioned, represents important initial attempts at empirically and comprehensively examining network-integrated palliative care and healthcare integration in general.

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Multiple myeloma is characterized by genomic alterations frequently involving gains and losses of chromosomes. Single nucleotide polymorphism (SNP)-based mapping arrays allow the identification of copy number changes at the sub-megabase level and the identification of loss of heterozygosity (LOH) due to monosomy and uniparental disomy (UPD). We have found that SNP-based mapping array data and fluorescence in situ hybridization (FISH) copy number data correlated well, making the technique robust as a tool to investigate myeloma genomics. The most frequently identified alterations are located at 1p, 1q, 6q, 8p, 13, and 16q. LOH is found in these large regions and also in smaller regions throughout the genome with a median size of 1 Mb. We have identified that UPD is prevalent in myeloma and occurs through a number of mechanisms including mitotic nondisjunction and mitotic recombination. For the first time in myeloma, integration of mapping and expression data has allowed us to reduce the complexity of standard gene expression data and identify candidate genes important in both the transition from normal to monoclonal gammopathy of unknown significance (MGUS) to myeloma and in different subgroups within myeloma. We have documented these genes, providing a focus for further studies to identify and characterize those that are key in the pathogenesis of myeloma.