Spectroscopic and magnetic studies of wild-type and mutant forms of the Fe(II)- and 2-oxoglutarate-dependent decarboxylase ALKBH4

The Fe(II)/2OG (2-oxoglutarate)-dependent dioxygenase superfamily comprises proteins that couple substrate oxidation to decarboxylation of 2OG to succinate. A member of this class of mononuclear non-haem Fe proteins is the Escherichia coli DNA/RNA repair enzyme AlkB. In the present work, we describe the magnetic and optical properties of the yet uncharacterized human ALKBH4 (AlkB homologue). Through EPR and UV–visible spectroscopy studies, we address the Fe-binding environment of the proposed catalytic centre of wild-type ALKBH4 and an Fe(II)-binding mutant. We could observe a novel unusual Fe(III) high-spin EPR-active species in the presence of sulfide with a gmax of 8.2. The Fe(II) site was probed with NO. An intact histidine-carboxylate site is necessary for productive Fe binding. We also report the presence of a unique cysteine-rich motif conserved in the N-terminus of ALKBH4 orthologues, and investigate its possible Fe-binding ability. Furthermore, we show that recombinant ALKBH4 mediates decarboxylation of 2OG in absence of primary substrate. This activity is dependent on Fe as well as on residues predicted to be involved in Fe(II) co-ordination. The present results demonstrate that ALKBH4 represents an active Fe(II)/2OG-dependent decarboxylase and suggest that the cysteine cluster is involved in processes other than Fe co-ordination

Supercritical solvothermal synthesis under reducing conditions to increase stability and durability of Mo/ZSM-5 catalysts in methane dehydroaromatization

Natural gas is currently envisioned as a potential energy and hydrocarbon feedstock in the forthcoming years. To overcome the detrimental flaring of this natural gas and the partial release of its major component, methane, novel and more effective strategies are required. These include the development of new, efficient and seemingly stable catalysts able to rapidly convert methane into valuable feedstocks. We show a novel synthesis method of Mo/ZSM-5 based on a solvothermal synthesis under supercritical conditions and reducing atmosphere (SC-STSE) to improve metal dispersion and enhance catalyst stability and durability during the methane dehydroaromatization (MDA) reaction. In contrast to the conventional impregnation method, SC-STS-E provides a superhigh atom-like metal dispersion at the zeolite pores resulting in the most stable Mo/ZSM-5 catalyst for MDA with the highest long-term hydrocarbon yield (xCH4=11.6% and yC2+ = 8.9%, after 15 h on stream) among the catalysts reported in literature for this reaction

Comprehensive Analysis of Market Conditions in the Foreign Exchange Market: Fluctuation Scaling and Variance-Covariance Matrix

We investigate quotation and transaction activities in the foreign exchange market for every week during the period of June 2007 to December 2010. A scaling relationship between the mean values of number of quotations (or number of transactions) for various currency pairs and the corresponding standard deviations holds for a majority of the weeks. However, the scaling breaks in some time intervals, which is related to the emergence of market shocks. There is a monotonous relationship between values of scaling indices and global averages of currency pair cross-correlations when both quantities are observed for various window lengths $\Delta t$.Comment: 13 pages, 10 figure

Fetal loss and maternal serum levels of 2,2',4,4',5,5'-hexachlorbiphenyl (CB-153) and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (p,p'-DDE) exposure: a cohort study in Greenland and two European populations

<p>Abstract</p> <p>Background</p> <p>In the present study, the aim is to examine the risk of fetal loss related to environmental 2,2',4,4',5,5'-hexachlorobiphenyl (CB-153) or 1,1-dichloro-2,2-bis(<it>p</it>-chlorophenyl)ethylene (p,p'-DDE) exposure.</p> <p>Methods</p> <p>We related LC/MS/MS measurements of CB-153 and p,p'-DDE in serum samples to interview-data on previous fetal loss in populations of pregnant women from Poland, Ukraine and Greenland.</p> <p>Results</p> <p>In total, 1710 women were interviewed, and 678 of these had at least one previous pregnancy. The risk of ever experiencing a fetal loss increased at higher levels of CB-153 and p,p'-DDE exposure, with an adjusted odds ratio (OR) of 2.4; confidence interval (CI) (1.1-5.5) for CB-153>200 ng/g lipid compared to 0-25 ng CB-153/g lipid and OR of 2.5 CI (0.9-6.6) for p,p'-DDE>1500 ng/g lipid compared to 0-250 ng DDE/g lipid. However, no clear dose response associations were observed. The results further suggest that high level of organochlorine serum concentrations may be related to repeated loss.</p> <p>Conclusions</p> <p>The risk of fetal loss may increase at higher levels of CB-153 and p,p'-DDE exposure, although lack of dose response and inconsistencies between countries did not allow for firm conclusions.</p

The non-random walk of stock prices: The long-term correlation between signs and sizes

We investigate the random walk of prices by developing a simple model relating the properties of the signs and absolute values of individual price changes to the diffusion rate (volatility) of prices at longer time scales. We show that this benchmark model is unable to reproduce the diffusion properties of real prices. Specifically, we find that for one hour intervals this model consistently over-predicts the volatility of real price series by about 70%, and that this effect becomes stronger as the length of the intervals increases. By selectively shuffling some components of the data while preserving others we are able to show that this discrepancy is caused by a subtle but long-range non-contemporaneous correlation between the signs and sizes of individual returns. We conjecture that this is related to the long-memory of transaction signs and the need to enforce market efficiency.Comment: 9 pages, 5 figures, StatPhys2

Self-reported sleep relates to hippocampal atrophy across the adult lifespan: results from the Lifebrain consortium.

OBJECTIVES: Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan. METHODS: Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21,390 participants from the UK Biobank. RESULTS: No cross-sectional sleep-hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses. CONCLUSIONS: Worse self-reported sleep is associated with higher rates of hippocampal volume decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation

Microsatellite based genetic diversity and population structure of the endangered Spanish Guadarrama goat breed

<p>Abstract</p> <p>Background</p> <p>Assessing genetic biodiversity and population structure of minor breeds through the information provided by neutral molecular markers, allows determination of their extinction risk and to design strategies for their management and conservation. Analysis of microsatellite loci is known to be highly informative in the reconstruction of the historical processes underlying the evolution and differentiation of animal populations. Guadarrama goat is a threatened Spanish breed which actual census (2008) consists of 3057 females and 203 males distributed in 22 populations more or less isolated. The aim of this work is to study the genetic status of this breed through the analysis of molecular data from 10 microsatellites typed in historic and actual live animals.</p> <p>Results</p> <p>The mean expected heterozygosity across loci within populations ranged from 0.62 to 0.77. Genetic differentiation measures were moderate, with a mean F_STof 0.074, G_STof 0.081 and R_STof 0.085. Percentages of variation among and within populations were 7.5 and 92.5, respectively. Bayesian clustering analyses pointed out a population subdivision in 16 clusters, however, no correlation between geographical distances and genetic differences was found. Management factors such as the limited exchange of animals between farmers (estimated gene flow Nm = 3.08) mostly due to sanitary and social constraints could be the major causes affecting Guadarrama goat population subdivision.</p> <p>Conclusion</p> <p>Genetic diversity measures revealed a good status of biodiversity in the Guadarrama goat breed. Since diseases are the first cause affecting the census in this breed, population subdivision would be an advantage for its conservation. However, to maintain private alleles present at low frequencies in such small populations minimizing the inbreeding rate, it would necessitate some mating designs of animals carrying such alleles among populations. The systematic use of molecular markers will facilitate the comprehensive management of these populations, which in combination with the actual breeding program to increase milk yield, will constitute a good strategy to preserve the breed.</p

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution

Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.The NEXT Collaboration acknowledges support from the following agencies and institutions: the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the European Union's Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Grant Agreements No. 674896, 690575 and 740055; the Ministerio de Economia y Competitividad and the Ministerio de Ciencia, Innovacion y Universidades of Spain under grants FIS2014-53371-C04, RTI2018-095979, the Severo Ochoa Program grants SEV-2014-0398 and CEX2018-000867-S, and the Maria de Maeztu Program MDM-2016-0692; the Generalitat Valenciana under grants PROMETEO/2016/120 and SEJI/2017/011; the Portuguese FCT under project PTDC/FIS-NUC/2525/2014 and under projects UID/04559/2020 to fund the activities of LIBPhys-UC; the U.S. Department of Energy under contracts No. DE-AC02-06CH11357 (Argonne National Laboratory), DE-AC02-07CH11359 (Fermi National Accelerator Laboratory), DE-FG02-13ER42020 (Texas A&M) and DE-SC0019223/DE-SC0019054 (University of Texas at Arlington); the University of Texas at Arlington (U.S.A.); and the Pazy Foundation (Israel) under grants 877040 and 877041. DGD acknowledges Ramon y Cajal program (Spain) under contract number RYC-2015-18820. JM-A acknowledges support from Fundacion Bancaria "la Caixa" (ID 100010434), grant code LCF/BQ/PI19/11690012. AS acknowledges support from the Kreitman School of Advanced Graduate Studies at Ben-Gurion University. Documen