MetaboLab - advanced NMR data processing and analysis for metabolomics

Background\ud Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.\ud \ud Results\ud Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.\ud \ud Conclusions\ud The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.\ud \u

Surface Waves for Anisotropic Material Characterization-A Computer Aided Evaluation System

Along with a wide application of nondestructive evaluation methods by ultrasonic techniques, Rayleigh surface waves are being studied for their applications in material characterization. Because surface waves can offer some sensitive measurement features of wave propagation, it is suggested that surface waves be conveniently used as an experimental technique for the solution of the inverse problem of determining elastic constants and/or other characteristics in materials [1–3]. The most common direct problem is to obtain wave propagation features by theoretical analysis, experimental measurement, or numerical calculation. A desired problem in material evaluation however, is to solve an inverse problem to find material characteristics from a set of field measurement data. In surface wave problems, the closed form solutions may not even exist for some direct problems. Moreover, often material constants collectively influence the ultrasonic wave propagation in anisotropic medium, and we can not decouple them and evaluate them individually by each single ultrasonic measurement. Therefore, a numerical computational procedure is proposed.</p

Facilitation or Competition? Tree Effects on Grass Biomass across a Precipitation Gradient

Savanna ecosystems are dominated by two distinct plant life forms, grasses and trees, but the interactions between them are poorly understood. Here, we quantified the effects of isolated savanna trees on grass biomass as a function of distance from the base of the tree and tree height, across a precipitation gradient in the Kruger National Park, South Africa. Our results suggest that mean annual precipitation (MAP) mediates the nature of tree-grass interactions in these ecosystems, with the impact of trees on grass biomass shifting qualitatively between 550 and 737 mm MAP. Tree effects on grass biomass were facilitative in drier sites (MAP≤550 mm), with higher grass biomass observed beneath tree canopies than outside. In contrast, at the wettest site (MAP = 737 mm), grass biomass did not differ significantly beneath and outside tree canopies. Within this overall precipitation-driven pattern, tree height had positive effect on sub-canopy grass biomass at some sites, but these effects were weak and not consistent across the rainfall gradient. For a more synthetic understanding of tree-grass interactions in savannas, future studies should focus on isolating the different mechanisms by which trees influence grass biomass, both positively and negatively, and elucidate how their relative strengths change over broad environmental gradients. © 2013 Moustakas et al

Dietary intakes of flavan-3-ols and cardiovascular health: a field synopsis using evidence mapping of randomized trials and prospective cohort studies

Background: There is considerable interest in the impact of increased flavan-3-ol intake on cardiovascular disease (CVD) and diabetes outcomes. Through evidence mapping, we determined the extent of the evidence base to initiate a future systematic review investigating the impact of flavan-3-ol intake on CVD and diabetes outcomes. Methods: We developed a research protocol, convened a technical expert panel (TEP) to refine the specific research questions, conducted a systematic search in multiple databases, double-screened abstracts and full-text articles, performed data extractions, and synthesized the data. We focused on randomized controlled trials (RCTs) and prospective cohort studies which assessed intakes of flavan-3-ol from foods, beverages, and supplement/extract sources on biomarkers and clinical outcomes of CVD and diabetes. Results: Of 257 eligible articles, 223 and 34 publications contributed to 226 RCTs and 39 prospective cohort studies, respectively. In RCTs, the most frequently studied interventions were cocoa-based products (23.2%); berries (16.1%); tea in the form of green tea (13.9%), black tea (7.2%), or unspecified tea (3.6%); and red wine (11.2%). Mean total flavan-3-ol intake was highest in the cocoa-based trials (618.7 mg/day) and lowest in the interventions feeding red wine (123.7 mg/day). The most frequently reported outcomes were intermediate biomarkers including serum lipid levels (63.4%), blood glucose (50.9%), blood pressure (50.8%), flow-mediated dilation (21.9%), and high-sensitivity C-reactive protein (21.9%). The included 34 prospective cohort studies predominantly examined exposures to flavan-3-ols (26%), cocoa-based products (23.2%), berries (16.1%), and green tea (13.9%) and CVD incidence and mortality. Conclusion: Through a systematic, evidence-based approach, evidence mapping on flavan-3-ol intake and CVD outcomes demonstrated sufficient data relating to flavan-3ol intake and biomarkers and clinical outcomes of CVD and diabetes. The current evidence base highlights the distribution of available data which both support the development of a future systematic review and identified the research need for future long-term RCTs

Regional adaptation defines sensitivity to future ocean acidification

Physiological responses to temperature are known to be a major determinant of species distributions and can dictate the sensitivity of populations to global warming. In contrast, little is known about how other major global change drivers, such as ocean acidification (OA), will shape species distributions in the future. Here, by integrating population genetics with experimental data for growth and mineralization, physiology and metabolomics, we demonstrate that the sensitivity of populations of the gastropod Littorina littorea to future OA is shaped by regional adaptation. Individuals from populations towards the edges of the natural latitudinal range in the Northeast Atlantic exhibit greater shell dissolution and the inability to upregulate their metabolism when exposed to low pH, thus appearing most sensitive to low seawater pH. Our results suggest that future levels of OA could mediate temperature-driven shifts in species distributions, thereby influencing future biogeography and the functioning of marine ecosystems

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Reassortment Patterns in Swine Influenza Viruses

Three human influenza pandemics occurred in the twentieth century, in 1918, 1957, and 1968. Influenza pandemic strains are the results of emerging viruses from non-human reservoirs to which humans have little or no immunity. At least two of these pandemic strains, in 1957 and in 1968, were the results of reassortments between human and avian viruses. Also, many cases of swine influenza viruses have reportedly infected humans, in particular, the recent H1N1 influenza virus of swine origin, isolated in Mexico and the United States. Pigs are documented to allow productive replication of human, avian, and swine influenza viruses. Thus it has been conjectured that pigs are the “mixing vessel” that create the avian-human reassortant strains, causing the human pandemics. Hence, studying the process and patterns of viral reassortment, especially in pigs, is a key to better understanding of human influenza pandemics. In the last few years, databases containing sequences of influenza A viruses, including swine viruses, collected since 1918 from diverse geographical locations, have been developed and made publicly available. In this paper, we study an ensemble of swine influenza viruses to analyze the reassortment phenomena through several statistical techniques. The reassortment patterns in swine viruses prove to be similar to the previous results found in human viruses, both in vitro and in vivo, that the surface glycoprotein coding segments reassort most often. Moreover, we find that one of the polymerase segments (PB1), reassorted in the strains responsible for the last two human pandemics, also reassorts frequently