Proton and cadmium adsorption by the archaeon Thermococcus zilligii: Generalising the contrast between thermophiles and mesophiles as sorbents

Adsorption by microorganisms can play a significant role in the fate and transport of metals in natural systems. Surface complexation models (SCMs) have been applied extensively to describe metal adsorption by mesophilic bacteria, and several recent studies have extended this framework to thermophilic bacteria. We conduct acid-base titrations and batch experiments to characterise proton and Cd adsorption onto the thermophilic archaeon Thermococcus zilligii. The experimental data and the derived SCMs indicate that the archaeon displays significantly lower overall sorption site density compared to previously studied thermophilic bacteria such Anoxybacillus flavithermus, Geobacillus stearothermophilus, G. thermocatenulatus, and Thermus thermophilus. The thermophilic bacteria and archaea display lower sorption site densities than the mesophilic microorganisms that have been studied to date, which points to a general pattern of total concentration of cell wall adsorption sites per unit biomass being inversely correlated to growth temperature

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

This is the published version. Copyright 2014 American Geophysical UnionThis paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models

Attenuated live infectious bronchitis virus QX vaccine disseminates slowly to target organs distant from the site of inoculation

Infectious bronchitis (IB) is a highly contagious respiratory disease of poultry, caused by the avian coronavirus infectious bronchitis virus (IBV). Currently, one of the most relevant genotypes circulating worldwide is IBV-QX (GI-19), for which vaccines have been developed by passaging virulent QX strains in embryonated chicken eggs. Here we explored the attenuated phenotype of a commercially available QX live vaccine, IB Primo QX, in specific pathogens free broilers. At hatch, birds were inoculated with QX vaccine or its virulent progenitor IBV-D388, and postmortem swabs and tissues were collected each day up to eight days post infection to assess viral replication and morphological changes. In the trachea, viral RNA replication and protein expression were comparable in both groups. Both viruses induced morphologically comparable lesions in the trachea, albeit with a short delay in the vaccinated birds. In contrast, in the kidney, QX vaccine viral RNA was nearly absent, which coincided with the lack of any morphological changes in this organ. This was in contrast to high viral RNA titers and abundant lesions in the kidney after IBV D388 infection. Furthermore, QX vaccine showed reduced ability to reach and replicate in conjunctivae and intestines including cloaca, resulting in significantly lower titers and delayed protein expression, respectively. Nephropathogenic IBVs might reach the kidney also via an ascending route from the cloaca, based on our observation that viral RNA was detected in the cloaca one day before detection in the kidney. In the kidney distal tubular segments, collecting ducts and ureter were positive for viral antigen. Taken together, the attenuated phenotype of QX vaccine seems to rely on slower dissemination and lower replication in target tissues other than the site of inoculation

Measuring Parton Densities in the Pomeron

We present a program to measure the parton densities in the pomeron using diffractive deep inelastic scattering and diffractive photoproduction, and to test the resulting parton densities by applying them to other processes such as the diffractive production of jets in hadron-hadron collisions. Since QCD factorization has been predicted NOT to apply to hard diffractive scattering, this program of fitting and using parton densities might be expected to fail. Its success or failure will provide useful information on the space-time structure of the pomeron.Comment: Contains revisions based on Phys. Rev. D referee comments. RevTeX version 3, epsf, 31 pages. Uuencoded compressed postscript figures appended. Uncompressed postscript files available at ftp://ftp.phys.psu.edu/pub/preprint/psuth136

Estimation of uncertainty in flood forecasts - a comparison of methods

The scientific literature has many methods for estimating uncertainty, however, there is a lack of information about the characteristics, merits and limitations of the individual methods, particularly for making decisions in practice. This paper provides an overview of the different uncertainty methods for flood forecasting that are reported in literature, concentrating on two established approaches defined as the ensemble and the statistical approach. Owing to the variety of flood forecasting and warning systems in operation, the question ‘which uncertainty method is most suitable for which application’ is difficult to answer readily. The paper aims to assist practitioners in understanding how to match an uncertainty quantification method to their particular application using two flood forecasting system case studies in Belgium and Canada. These two specific applications of uncertainty estimation from the literature are compared, illustrating statistical and ensemble methods, and indicating the information and output that these two types of methods offer. The advantages, disadvantages and application of the two different types of method are identified. Although there is no one ‘best’ uncertainty method to fit all forecasting systems, this review helps to explain the current commonly used methods from the available literature for the non-specialist

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction

Integrated fecal microbiome–metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome

To gain insight into the complex microbiome-gut-brain axis in irritable bowel syndrome (IBS) several modalities of biological and clinical data must be combined. We aimed to identify profiles of faecal microbiota and metabolites associated with IBS and to delineate specific phenotypes of IBS that represent potential pathophysiological mechanisms. Faecal metabolites were measured using proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy and gut microbiome using Shotgun Metagenomic Sequencing (MGS) in a combined dataset of 142 IBS patients and 120 healthy controls (HC) with extensive clinical, biological and phenotype information. Data were analysed using support vector classification and regression and kernel t-SNE. Microbiome and metabolome profiles could distinguish IBS and HC with an area-under-the-receiver-operator-curve (AUC) of 77.3% and 79.5%, respectively, but this could be improved by combining microbiota and metabolites to 83.6%. No significant differences in predictive ability of the microbiome-metabolome data were observed between the three classical, stool pattern-based, IBS subtypes. However, unsupervised clustering showed distinct subsets of IBS patients based on faecal microbiome-metabolome data. These clusters could be related plasma levels of serotonin and its metabolite 5-hydroxyindoleacetate, effects of psychological stress on gastrointestinal symptoms, onset of IBS after stressful events, medical history of previous abdominal surgery, dietary caloric intake and IBS symptom duration. Furthermore, pathways in metabolic reaction networks were integrated with microbiota data, that reflect the host-microbiome interactions in IBS. The identified microbiome-metabolome signatures for IBS, associated with altered serotonin metabolism and unfavourable stress-response related to gastrointestinal symptoms, support the microbiota-gut-brain link in the pathogenesis of IBS

Global QCD Analysis and the CTEQ Parton Distributions

The CTEQ program for the determination of parton distributions through a global QCD analysis of data for various hard scattering processes is fully described. A new set of distributions, CTEQ3, incorporating several new types of data is reported and compared to the two previous sets of CTEQ distributions. Comparison with current data is discussed in some detail. The remaining uncertainties in the parton distributions and methods to further reduce them are assessed. Comparisons with the results of other global analyses are also presented.Comment: (Change in Latex style only: 2up style removed since many don't have it.) 35 pages, 23 figures separately submitted as uuencoded compressed ps-file; Michigan State Report # MSU-HEP/41024 and CTEQ 40

Measurement of Semileptonic Branching Fractions of B Mesons to Narrow D** States

Using the data accumulated in 2002-2004 with the DO detector in proton-antiproton collisions at the Fermilab Tevatron collider with centre-of-mass energy 1.96 TeV, the branching fractions of the decays B -> \bar{D}_1^0(2420) \mu^+ \nu_\mu X and B -> \bar{D}_2^{*0}(2460) \mu^+ \nu_\mu X and their ratio have been measured: BR(\bar{b}->B) \cdot BR(B-> \bar{D}_1^0 \mu^+ \nu_\mu X) \cdot BR(\bar{D}_1^0 -> D*- pi+) = (0.087+-0.007(stat)+-0.014(syst))%; BR(\bar{b}->B)\cdot BR(B->D_2^{*0} \mu^+ \nu_\mu X) \cdot BR(\bar{D}_2^{*0} -> D*- \pi^+) = (0.035+-0.007(stat)+-0.008(syst))%; and (BR(B -> \bar{D}_2^{*0} \mu^+ \nu_\mu X)BR(D2*0->D*- pi+)) / (BR(B -> \bar{D}_1^{0} \mu^+ \nu_\mu X)\cdot BR(\bar{D}_1^{0}->D*- \pi^+)) = 0.39+-0.09(stat)+-0.12(syst), where the charge conjugated states are always implied.Comment: submitted to Phys. Rev. Let