68 research outputs found

    BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

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    Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

    Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

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    Background: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches

    Indigenous biosecurity: Māori responses to kauri dieback and myrtle rust in Aotearoa New Zealand

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    It is widely acknowledged that Indigenous peoples have traditional knowledge relevant to modern environmental management. By asserting roles within associated science and policy networks, such Indigenous Knowledge (IK) can be seen as part of the resistance to colonisation that includes protest, treaty making, political and economic empowerment, legislation, cultural renaissance and regulatory influence. In New Zealand, these achievements inform attempts by Māori (the Indigenous people of New Zealand) to manage forest ecosystems and cultural keystone species. This chapter presents two case studies of how indigenous participation in modern biosecurity through the example of Māori asserting and contributing to forest management. While progress is often frustratingly slow for indigenous participants, significant gains in acceptance of Māori cultural frameworks have been achieved

    Climatic risks and impacts in South Asia: extremes of water scarcity and excess

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    This paper reviews the current knowledge of climatic risks and impacts in South Asia associated with anthropogenic warming levels of 1.5°C to 4°C above pre-industrial values in the 21st century. It is based on the World Bank Report “Turn Down the Heat, Climate Extremes, Regional Impacts and the Case for Resilience” (2013). Many of the climate change impacts in the region, which appear quite severe even with relatively modest warming of 1.5–2°C, pose significant hazards to development. For example, increased monsoon variability and loss or glacial meltwater will likely confront populations with ongoing and multiple challenges. The result is a significant risk to stable and reliable water resources for the region, with increases in peak flows potentially causing floods and dry season flow reductions threatening agriculture. Irrespective of the anticipated economic development and growth, climate projections indicate that large parts of South Asia’s growing population and especially the poor are likely to remain highly vulnerable to climate change

    A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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    ICAR: endoscopic skull‐base surgery

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    Toward conservational anthropology: addressing anthropocentric bias in anthropology

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    Anthropological literature addressing conservation and development often blames 'conservationists' as being neo-imperialist in their attempts to institute limits to commercial activities by imposing their post-materialist eco-ideology. The author argues that this view of conservationists is ironic in light of the fact that the very notion of 'development' is arguably an imposition of the (Western) elites. The anthropocentric bias in anthropology also permeates constructivist ethnographies of human-animal 'interactions,' which tend to emphasize the socio-cultural complexity and interconnectivity rather than the unequal and often extractive nature of this 'interaction.' Anthropocentrism is argued to be counteractive to reconciling conservationists' efforts at environmental protection with the traditional ontologies of the interdependency of human-nature relationship

    Structured model for batch culture growth of Lactobacillus bulgaricus

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    Batch fermentation kinetics of Lactobacillus bulgaricus were examined in detail using the methodology of cybernetic modelling. The effect of pH and lactate ion on the activity of the enzyme B-galactosidase was simulated. Cybernetic modelling is mainly used for simulation of growth on multiple substrates. Here, it has been incorporated in a model which simulates pH effects on single-substrate batch growth. The expression of active enymze is crucial for substrate and growth. It was seen that the effect of lactate ion on the activity of the enzyme was dependant on the system pH. A semi-empirical expression was obtained for the relative amount of active enzyme present in the organism and used to model the enzyme, biomass, substrate and lactic acid concentrations for the batch fermentation. The rate of biomass formation and product formation depended on the amount of enzyme synthesised, which in turn was dependant on the pH value of the system. The model developed simulates the effect of pH and lactate concentration on the expression and degradation of the enzyme
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