2,643 research outputs found

    Adsorption and desorption dynamics of citric acid anions in soil

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    The functional role of organic acid anions (e.g. citrate, oxalate, malonate, etc) in soil has been intensively investigated with special focus either on (i) microbial respiration and soil carbon dynamics, (ii) nutrient solubilization, or (iii) metal detoxification. Considering the potential impact of sorption processes on the functional significance of these effects, comparatively little is known about the adsorption and desorption dynamics of organic acid anions in soils. The aim of this study therefore was to experimentally characterize the adsorption and desorption dynamics of organic acid anions in different soils using citrate as a model carboxylate. Results showed that both adsorption and desorption processes were fast, reaching a steady state equilibrium solution concentration within approximately 1 hour. However, for a given total soil citrate concentration(ctot) the steady state value obtained was critically dependent on the starting conditions of the experiment (i.e. whether most of the citrate was initially present in solution (cl) or held on the solid phase (cs)). Specifically, desorption-led processes resulted in significantly lower equilibrium solution concentrations than adsorption led processes indicating time-dependent sorption hysteresis. As it is not possible to experimentally distinguish between different sorption pools in soil (i.e. fast, slow, irreversible adsorption/desorption), a new dynamic hysteresis model was developed that relies only on measured soil solution concentrations. The model satisfactorily explained experimental data and was able to predict dynamic adsorption and desorption behaviour. To demonstrate its use we applied the model to two relevant scenarios (exudation and microbial degradation), where the dynamic sorption behaviour of citrate occurs. Overall, this study highlights the complex nature of citrate sorption in soil and concludes that existing models need to incorporate both a temporal and sorption hysteresis component to realistically describe the role and fate of organic acids in soil processes

    Combined use of empirical data and mathematical modelling to better estimate the microbial turnover of isotopically labelled carbon substrates in soil

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    The flow of carbon (C) through soil is inherently complex due to the many thousands of different chemical transformations occurring simultaneously within the soil microbial community. The accurate modelling of this C flow therefore represents a major challenge. In response to this, isotopic tracers (e.g. 13C, 14C) are commonly used to experimentally parameterise models describing the fate and residence time of individual C compounds within soil. In this study, we critically evaluated the combined use of experimental 14C labelling and mathematical modelling to estimate C turnover times in soil. We applied 14C-labelled alanine and glucose to an agricultural soil and simultaneously measured their loss from soil solution alongside the rate of microbial C immobilization and mineralization. Our results revealed that chloroform fumigation-extraction (CFE) cannot be used to reliably quantify the amount of isotopically labelled 13C/14C immobilised by the microbial biomass. This is due to uncertainty in the extraction efficiency values (kec) within the CFE methodology which are both substrate and incubation time dependent. Further, the traditional mineralization approach (i.e. measuring 14/13CO2 evolution) provided a poor estimate of substrate loss from soil solution and mainly reflected rates of internal microbial C metabolism after substrate uptake from the soil. Therefore, while isotope addition provides a simple mechanism for labelling the microbial biomass it provides limited information on the behaviour of the substrate itself. We used our experimental data to construct a new empirical model to describe the simultaneous flow of substrate-C between key C pools in soil. This model provided a superior estimate of microbial substrate use and microbial respiration flux in comparison to traditional first order kinetic modelling approaches. We also identify a range of fundamental problems associated with the modelling of isotopic-C in soil, including issues with variation in C partitioning within the community, model pool connectivity and variation in isotopic pool dilution, which make interpretation of any C isotopic flux data difficult. We conclude that while convenient, the use of isotopic data (13C, 14C, 15N) has many potential pitfalls necessitating a critical evaluation of both past and future studies

    Provisioning of data locality for HEP analysis workflows

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    The heavily increasing amount of data produced by current experiments in high energy particle physics challenge both end users and providers of computing resources. The boosted data rates and the complexity of analyses require huge datasets being processed in short turnaround cycles. Usually, data storages and computing farms are deployed by different providers, which leads to data delocalization and a strong influence of the interconnection transfer rates. The CMS collaboration at KIT has developed a prototype enabling data locality for HEP analysis processing via two concepts. A coordinated and distributed caching approach that reduce the limiting factor of data transfers by joining local high performance devices with large background storages were tested. Thereby, a throughput optimization was reached by selecting and allocating critical data within user work-flows. A highly performant setup using these caching solutions enables fast processing of throughput dependent analysis workflows

    Inhibition of protein crystallization by evolutionary negative design

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    In this perspective we address the question: why are proteins seemingly so hard to crystallize? We suggest that this is because of evolutionary negative design, i.e. proteins have evolved not to crystallize, because crystallization, as with any type of protein aggregation, compromises the viability of the cell. There is much evidence in the literature that supports this hypothesis, including the effect of mutations on the crystallizability of a protein, the correlations found in the properties of crystal contacts in bioinformatics databases, and the positive use of protein crystallization by bacteria and viruses.Comment: 5 page
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