Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape

Novel prokaryotic expression of thioredoxin-fused insulinoma associated protein tyrosine phosphatase 2 (IA-2), its characterization and immunodiagnostic application

Background The insulinoma associated protein tyrosine phosphatase 2 (IA-2) is one of the immunodominant autoantigens involved in the autoimmune attack to the beta-cell in Type 1 Diabetes Mellitus. In this work we have developed a complete and original process for the production and recovery of the properly folded intracellular domain of IA-2 fused to thioredoxin (TrxIA-2ic) in Escherichia coli GI698 and GI724 strains. We have also carried out the biochemical and immunochemical characterization of TrxIA-2icand design variants of non-radiometric immunoassays for the efficient detection of IA-2 autoantibodies (IA-2A). Results The main findings can be summarized in the following statements: i) TrxIA-2ic expression after 3 h of induction on GI724 strain yielded ≈ 10 mg of highly pure TrxIA-2ic/L of culture medium by a single step purification by affinity chromatography, ii) the molecular weight of TrxIA-2ic (55,358 Da) could be estimated by SDS-PAGE, size exclusion chromatography and mass spectrometry, iii) TrxIA-2ic was properly identified by western blot and mass spectrometric analysis of proteolytic digestions (63.25 % total coverage), iv) excellent immunochemical behavior of properly folded full TrxIA-2ic was legitimized by inhibition or displacement of [35S]IA-2 binding from IA-2A present in Argentinian Type 1 Diabetic patients, v) great stability over time was found under proper storage conditions and vi) low cost and environmentally harmless ELISA methods for IA-2A assessment were developed, with colorimetric or chemiluminescent detection. Conclusions E. coli GI724 strain emerged as a handy source of recombinant IA-2ic, achieving high levels of expression as a thioredoxin fusion protein, adequately validated and applicable to the development of innovative and cost-effective immunoassays for IA-2A detection in most laboratories.Fil: Guerra, Luciano Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Faccinetti, Natalia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Trabucchi, Aldana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Rovitto, Bruno David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Sabljic, Adriana Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Poskus, Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Iacono, Ruben Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Valdez, Silvina Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; Argentin

Influence of Different Plant Species on Methane Emissions from Soil in a Restored Swiss Wetland

Plants are a major factor influencing methane emissions from wetlands, along with environmental parameters such as water table, temperature, pH, nutrients and soil carbon substrate. We conducted a field experiment to study how different plant species influence methane emissions from a wetland in Switzerland. The top 0.5 m of soil at this site had been removed five years earlier, leaving a substrate with very low methanogenic activity. We found a sixfold difference among plant species in their effect on methane emission rates: Molinia caerulea and Lysimachia vulgaris caused low emission rates, whereas Senecio paludosus, Carex flava, Juncus effusus and Typha latifolia caused relatively high rates. Centaurea jacea, Iris sibirica, and Carex davalliana caused intermediate rates. However, we found no effect of either plant biomass or plant functional groups – based on life form or productivity of the habitat – upon methane emission. Emissions were much lower than those usually reported in temperate wetlands, which we attribute to reduced concentrations of labile carbon following topsoil removal. Thus, unlike most wetland sites, methane production in this site was probably fuelled chiefly by root exudation from living plants and from root decay. We conclude that in most wetlands, where concentrations of labile carbon are much higher, these sources account for only a small proportion of the methane emitted. Our study confirms that plant species composition does influence methane emission from wetlands, and should be considered when developing measures to mitigate the greenhouse gas emissions

HLA Genes, Islet Autoantibodies and Residual C-Peptide at the Clinical Onset of Type 1 Diabetes Mellitus and the Risk of Retinopathy 15 Years Later

HLA genes, islet autoantibodies and residual C-peptide were studied to determine the independent association of each exposure with diabetic retinopathy (DR), 15 years after the clinical onset of type 1 diabetes in 15-34 year old individuals.The cohort was identified in 1992 and 1993 by the Diabetes Incidence Study in Sweden (DISS), which investigates incident cases of diabetes for patients between 15 and 34 years of age. Blood samples at diagnosis were analyzed to determine HLA genotype, islet autoantibodies and serum C-peptide. In 2009, fundus photographs were obtained from patient records. Study measures were supplemented with data from the Swedish National Diabetes Registry.The prevalence of DR was 60.2% (148/246). Autoantibodies against the 65 kD isoform of glutamate decarboxylase (GADA) at the onset of clinical diabetes increased the risk of DR 15 years later, relative risk 1.12 for each 100 WHO units/ml, [95% CI 1.02 to 1.23]. This equates to risk estimates of 1.27, [95% CI 1.04 to 1.62] and 1.43, [95% CI 1.06 to 1.94] for participants in the highest 25(th) (GADA>233 WHO units/ml) and 5(th) percentile (GADA>319 WHO units/ml) of GADA, respectively. These were adjusted for duration of diabetes, HbA(1c), treated hypertension, sex, age at diagnosis, HLA and C-peptide. Islet cell autoantibodies, insulinoma-antigen 2 autoantibodies, residual C-peptide and the type 1 diabetes associated haplotypes DQ2, DQ8 and DQ6 were not associated with DR.Increased levels of GADA at the onset of type 1 diabetes were associated with DR 15 years later. These results, if confirmed, could provide additional insights into the pathogenesis of the most common microvascular complication of diabetes and lead to better risk stratification for both patient screenings and DR treatment trials

The C:N:P:S stoichiometry of soil organic matter

The formation and turnover of soil organic matter (SOM) includes the biogeochemical processing of the macronutrient elements nitrogen (N), phosphorus (P) and sulphur (S), which alters their stoichiometric relationships to carbon (C) and to each other. We sought patterns among soil organic C, N, P and S in data for c. 2000 globally distributed soil samples, covering all soil horizons. For non-peat soils, strong negative correlations (p < 0.001) were found between N:C, P:C and S:C ratios and % organic carbon (OC), showing that SOM of soils with low OC concentrations (high in mineral matter) is rich in N, P and S. The results can be described approximately with a simple mixing model in which nutrient-poor SOM (NPSOM) has N:C, P:C and S:C ratios of 0.039, 0.0011 and 0.0054, while nutrient-rich SOM (NRSOM) has corresponding ratios of 0.12, 0.016 and 0.016, so that P is especially enriched in NRSOM compared to NPSOM. The trends hold across a range of ecosystems, for topsoils, including O horizons, and subsoils, and across different soil classes. The major exception is that tropical soils tend to have low P:C ratios especially at low N:C. We suggest that NRSOM comprises compounds selected by their strong adsorption to mineral matter. The stoichiometric patterns established here offer a new quantitative framework for SOM classification and characterisation, and provide important constraints to dynamic soil and ecosystem models of carbon turnover and nutrient dynamics

Vegetation Type Dominates the Spatial Variability in CH<inf>4</inf> Emissions Across Multiple Arctic Tundra Landscapes

Methane (CH4) emissions from Arctic tundra are an important feedback to global climate. Currently, modelling and predicting CH4 fluxes at broader scales are limited by the challenge of upscaling plot-scale measurements in spatially heterogeneous landscapes, and by uncertainties regarding key controls of CH4 emissions. In this study, CH4 and CO2 fluxes were measured together with a range of environmental variables and detailed vegetation analysis at four sites spanning 300 km latitude from Barrow to Ivotuk (Alaska). We used multiple regression modelling to identify drivers of CH4 flux, and to examine relationships between gross primary productivity (GPP), dissolved organic carbon (DOC) and CH4 fluxes. We found that a highly simplified vegetation classification consisting of just three vegetation types (wet sedge, tussock sedge and other) explained 54% of the variation in CH4 fluxes across the entire transect, performing almost as well as a more complex model including water table, sedge height and soil moisture (explaining 58% of the variation in CH4 fluxes). Substantial CH4 emissions were recorded from tussock sedges in locations even when the water table was lower than 40 cm below the surface, demonstrating the importance of plant-mediated transport. We also found no relationship between instantaneous GPP and CH4 fluxes, suggesting that models should be cautious in assuming a direct relationship between primary production and CH4 emissions. Our findings demonstrate the importance of vegetation as an integrator of processes controlling CH4 emissions in Arctic ecosystems, and provide a simplified framework for upscaling plot scale CH4 flux measurements from Arctic ecosystems

Environmental and vegetation controls on the spatial variability of CH4 emission from wet-sedge and tussock tundra ecosystems in the Arctic

Aims Despite multiple studies investigating the environmental controls on CH4 fluxes from arctic tundra ecosystems, the high spatial variability of CH4 emissions is not fully understood. This makes the upscaling of CH4 fluxes from plot to regional scale, particularly challenging. The goal of this study is to refine our knowledge of the spatial variability and controls on CH4 emission from tundra ecosystems. Methods CH4 fluxes were measured in four sites across a variety of wet-sedge and tussock tundra ecosystems in Alaska using chambers and a Los Gatos CO2 and CH4 gas analyser. Results All sites were found to be sources of CH4, with northern sites (in Barrow) showing similar CH4 emission rates to the southernmost site (ca. 300 km south, Ivotuk). Gross primary productivity (GPP), water level and soil temperature were the most important environmental controls on CH4 emission. Greater vascular plant cover was linked with higher CH4 emission, but this increased emission with increased vascular plant cover was much higher (86 %) in the drier sites, than the wettest sites (30 %), suggesting that transport and/or substrate availability were crucial limiting factors for CH4 emission in these tundra ecosystems. Conclusions Overall, this study provides an increased understanding of the fine scale spatial controls on CH4 flux, in particular the key role that plant cover and GPP play in enhancing CH4 emissions from tundra soils

Functional analysis by 64-slice CT scanning: prediction of left ventricular dysfunction together with reduction in radiation exposure?

Cardiac Dysfunction and Arrhythmia

320-row CT: does beat-to-beat motion of the coronary arteries affect image quality?

Vascular Biology and Interventio