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The L-glutamate transporter GLT-1 is an abundant CNS membrane protein of the excitatory amino acid transporter (EAAT) family which controls extracellular L-glutamate levels and is important in limiting excitotoxic neuronal death. Using RT-PCR, we have determined that four mRNAs encoding GLT-1 exist in mouse brain, with the potential to encode four GLT-1 isoforms that differ in their N- and C-termini. We expressed all four isoforms (termed MAST-KREK, MPK-KREK, MAST-DIETCI and MPK-DIETCI according to amino acid sequence) in a range of cell lines and primary astrocytes and show that each isoform can reach the cell surface. In transfected HEK-293 or COS-7 cells, all four isoforms support high-affinity sodium-dependent L-glutamate uptake with identical pharmacological and kinetic properties. Inserting a viral epitope (V5, HA or FLAG) into the second extracellular domain of each isoform allowed co-immunoprecipitation and tr-FRET studies using transfected HEK-293 cells. Here we show for the first time that each of the four isoforms are able to combine to form homomeric and heteromeric assemblies, each of which are expressed at the cell surface of primary astrocytes. After activation of protein kinase C by phorbol ester, V5-tagged GLT-1 is rapidly removed from the cell surface of HEK-293 cells and degraded. This study provides direct biochemical evidence for oligomeric assembly of GLT-1 and reports the development of novel tools to provide insight into the trafficking of GLT-1.

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The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.

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The Olsen method is an indicator of plant-available phosphorus (P). The effect of time and temperature on residual phosphate in soils was measured using the Olsen method in a pot experiment. Four soils were investigated: two from Pakistan and one each from England (calcareous) and Colombia (acidic). Two levels of residual phosphate were developed in each soil after addition of phosphate by incubation at either 10degreesC or 45degreesC. The amount of phosphate added was based on the P maximum of each soil, calculated using the Langmuir equation. Rvegrass was used as the test crop. The pooled data for the four soils incubated at 10degreesC showed good correlation between Olsen P and dry matter yield or P uptake (r(2) = 0.85 and 0.77, respectively), whereas at 45 degreesC, each soil had its own relationship and pooled data did not show correlation of Olsen P with dry matter yield or P uptake. When the data at both temperatures were pooled, Olsen P was a good indicator of yield and uptake for the English soil. For the Pakistani soils, Olsen P after 45 degreesC treatment was an underestimate relative to the 10 degreesC data and for the Colombian soil it was an overestimate. The reasons for these differences need to be explored further before high temperature incubation can be used to simulate long-term changes in the field.

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Nonylphenol polyethoxylates (NPEOs) are surfactants found ubiquitously in the environment due to widespread industrial and domestic use. Biodegradation of NPEOs produces nonylphenol (NP), an endocrine disruptor. Sewage sludge application introduces NPEOs and NP into soils, potentially leading to accumulation in soils and crops. We examined degradation of NP and nonyl phenol-12-ethoxylate (NP12EO) in four soils. NP12EO degraded rapidly (initial half time 0.3-5 days). Concentrations became undetectable within 70-90 days, with a small increase in NP concentrations after 30 days. NP initially degraded quickly (mean half time 11.5 days), but in three soils a recalcitrant fraction of 26-35% remained: the non-degrading fraction may consist of branched isomers, resistant to biodegradation. Uptake of NP by bean plants was also examined. Mean bioconcentration factors for shoots and seeds were 0.71 and 0.58, respectively. Removal of NP from the soil by plant uptake was negligible (0.01-0.02% of initial NP). Root concentrations were substantially higher than shoot and seed concentrations. (C) 2008 Elsevier Ltd. All rights reserved.

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Critical loads are the basis for policies controlling emissions of acidic substances in Europe and elsewhere. They are assessed by several elaborate and ingenious models, each of which requires many parameters, and have to be applied on a spatially-distributed basis. Often the values of the input parameters are poorly known, calling into question the validity of the calculated critical loads. This paper attempts to quantify the uncertainty in the critical loads due to this "parameter uncertainty", using examples from the UK. Models used for calculating critical loads for deposition of acidity and nitrogen in forest and heathland ecosystems were tested at four contrasting sites. Uncertainty was assessed by Monte Carlo methods. Each input parameter or variable was assigned a value, range and distribution in an objective a fashion as possible. Each model was run 5000 times at each site using parameters sampled from these input distributions. Output distributions of various critical load parameters were calculated. The results were surprising. Confidence limits of the calculated critical loads were typically considerably narrower than those of most of the input parameters. This may be due to a "compensation of errors" mechanism. The range of possible critical load values at a given site is however rather wide, and the tails of the distributions are typically long. The deposition reductions required for a high level of confidence that the critical load is not exceeded are thus likely to be large. The implication for pollutant regulation is that requiring a high probability of non-exceedance is likely to carry high costs. The relative contribution of the input variables to critical load uncertainty varied from site to site: any input variable could be important, and thus it was not possible to identify variables as likely targets for research into narrowing uncertainties. Sites where a number of good measurements of input parameters were available had lower uncertainties, so use of in situ measurement could be a valuable way of reducing critical load uncertainty at particularly valuable or disputed sites. From a restricted number of samples, uncertainties in heathland critical loads appear comparable to those of coniferous forest, and nutrient nitrogen critical loads to those of acidity. It was important to include correlations between input variables in the Monte Carlo analysis, but choice of statistical distribution type was of lesser importance. Overall, the analysis provided objective support for the continued use of critical loads in policy development. (c) 2007 Elsevier B.V. All rights reserved.

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This Note outlines the further development of a system of models for the estimation of the costs of livestock diseases first presented by Bennett (2003). The models have been developed to provide updated and improved estimates of the costs associated with 34 endemic diseases of livestock in Great Britain, using border prices and including assessments of the impact of diseases on human health and animal welfare. Results show that, of the diseases studied, mastitis has the highest costs for cattle diseases, enzootic abortion for sheep diseases, swine influenza for pig diseases and salmonellosis for poultry diseases.

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Objectives: To conduct it detailed evaluation, with meta-analyses, of the published evidence on milk and dairy consumption and the incidence of vascular diseases and diabetes. Also to summarise the evidence on milk and dairy consumption and cancer reported by the World Cancer Research Fund and then to consider the relevance of milk and dairy consumption to survival in the UK, a typical Western community. Finally, published evidence on relationships with whole milk and fat-reduced milks was examined. Methods: Prospective cohort studies of vascular disease and diabetes with baseline data on milk or dairy consumption and a relevant disease outcome were identified by searching MEDLINE, and reference lists in the relevant published reports. Meta-analyses of relationships in these reports were conducted. The likely effect of milk and dairy consumption on survival was then considered, taking into account the results of published overviews of relationships of these foods with cancer. Results: From meta-analysis of 15 studies the relative risk of stroke and/or heart disease in subjects with high milk or dairy consumption was 0.84 (95% CI 0.76, 0,93) and 0.79 (0.75, 0.82) respectively, relative to the risk in those with low consumption. Four studies reported incident diabetes as an outcome, and the relative risk in the Subjects with the highest intake of milk or diary foods was 0.92 (0.86, 0.97). Conclusions: Set against the proportion of total deaths attributable to the life-threatening diseases in the UK, vascular disease, diabetes and cancer, the results of meta-analyses provide evidence of an overall survival advantage from the consumption of milk and dairy foods.