RNA editing regulates insect gamma-aminobutyric acid receptor function and insecticide sensitivity

A-to-I pre-mRNA editing by adenosine deaminase enzymes has been reported to enhance protein diversity in the nervous system. In Drosophila, the resistance to dieldrin (RDL) gamma-aminobutyric acid (GABA) receptor subunit displays an editing site (R122) that is close to the putative GABA-binding site. We assessed the functional effects of editing at this site by expressing homomeric RDL receptors in Xenopus oocytes. After replacement of arginine 122 with a glycine, both agonist and fipronil potencies were shifted to the right in either fipronil-sensitive receptors or mutated resistant receptors (A301G/T350M). These data provide the first insight on the influence of RNA editing on GABA receptor function

Gene flow estimation with microsatellites in a Malagasy seed orchard of Eucalyptus grandis

International audienceEucalyptus grandis has a mixed-mating repro- ductive system. Malagasy Eucalyptus seed orchards were established 15 years ago with two aims both based on panmixia: open-pollinated seed production and genetic improvement. The panmixia hypothesis has never been confirmed in the seed orchard. From a seedling seed- orchard stand comprising 349 trees and using data obtained with six selected microsatellite markers, pater- nity analysis was performed for 724 offspring collected on 30 adult trees. Paternity assignment, based on exclu- sion procedures and likelihood-ratio method, was achieved with high accuracy; the exclusion probability value was 0.997. The outcrossing rate was very high (96.7%). More than 50% of potential male trees (199 out of 349) in the seed orchard contributed to pollination for 440 offspring of 30 progenies (8.6% of the basic population). The pollination rate from outside the seed orchard was high (39.2%), but might be due to the small size of this seed orchard. This study showed that "panmixia-like pollination" can be assume

Geochemical indices allow estimation of heavy metal background concentration in soils

Defining background concentrations for heavy metals in soils is essential for recognizing and managing soil pollution. However, background concentrations of metals in soils can vary naturally by several orders of magnitude. Moreover, many soils have also been subject to unquantifiable anthropogenic inputs of metals, in some cases, for centuries. Hence determination of heavy metal background concentrations in soils has to date been fraught with difficulty. Here we demonstrate that there are associations between the background heavy metal and Fe or Mn contents in soils which appear to be consistent for seven important heavy metals of environmental concern. The relationships are remarkably independent of both soil type and climatic setting. These observations provide the basis for a series of general equations from which it is proposed Southeast Asian including Australian, and possibly worldwide background concentrations for As, Cr, Co, Cu, Ni, Pb, and Zn in soils can be derived.R. E. Hamon, M. J. McLaughlin, R. J. Gilkes, A. W. Rate, B. Zarcinas, A. Robertson, G. Cozens, N. Radford and L. Bettena

Forced Abstinence from Cocaine Self-Administration is Associated with DNA Methylation Changes in Myelin Genes in the Corpus Callosum: a Preliminary Study

Background: Human cocaine abuse is associated with alterations in white matter integrity revealed upon brain imaging, an observation that is recapitulated in an animal model of continuous cocaine exposure. The mechanism through which cocaine may affect white matter is unknown and the present study tested the hypothesis that cocaine self-administration results in changes in DNA methylation that could result in altered expression of several myelin genes that could contribute to the effects of cocaine on white matter integrity. Methods: In the present study, we examined the impact of forced abstinence from cocaine self-administration on chromatin associated changes in white matter. To this end, rats were trained to self-administer cocaine (0.75 mg/kg/0.1 mL infusion) for 14 days followed by forced abstinence for 1 day (n = 6) or 30 days (n = 6) before sacrifice. Drug-free, sham surgery controls (n = 7) were paired with the experimental groups. Global DNA methylation and DNA methylation at specific CpG sites in the promoter regions ofmyelin basic protein (Mbp), proteolipid protein-1 (Plp1), and SRY-related HMG-box-10 (Sox10) genes were analyzed in DNA extracted from corpus callosum. Results: Significant differences in the overall methylation patterns of the Sox10 promoter region were observed in the corpus callosum of rats at 30 days of forced abstinence from cocaine self-administration relative to sham controls; the −189, −142, −93, and −62 CpG sites were significantly hypomethylated point-wise at this time point. After correction for multiple comparisons, no differences in global methylation or the methylation patterns of Mbp or Plp1 were found. Conclusion: Forced abstinence from cocaine self-administration was associated with differences in DNA methylation at specific CpG sites in the promoter region of the Sox10 gene in corpus callosum. These changes may be related to reductions in normal age related changes in DNA methylation and could be a factor in white matter alterations seen after withdrawal from repeated cocaine self-administration. Further research is warranted examining the effects of cocaine on DNA methylation in white matter

Future socio-political scenarios for aquatic resources in Europe: An operationalized framework for aquaculture projections

Climate-driven changes in aquatic environments have already started to affect the European aquaculture sector’s most commercially important finfish and shellfish species. In addition to changes in water quality and temperature that can directly influence fish production by altering health status, growth performance and/or feed conversion, the aquaculture sector also faces an uncertain future in terms of production costs and returns. For example, the availability of key ingredients for fish feeds (proteins, omega-3 fatty acids) will not only depend on future changes in climate, but also on social and political factors, thereby influencing feed costs. The future cost of energy, another main expenditure for fish farms, will also depend on various factors. Finally, marketing options and subsidies will have major impacts on future aquaculture profitability. Based on the framework of four socio-political scenarios developed in the EU H2020 project climate change and European aquatic resources (CERES), we defined how these key factors for the aquaculture sector could change in the future. We then apply these scenarios to make projections of how climate change and societal and economic trends influence the mid-century (2050) profitability of European aquaculture. We used an established benchmarking approach to contrast present-day and future economic performance of “typical farms” in selected European production regions under each of the scenarios termed “World Markets,” “National Enterprise,” “Global Sustainability” and “Local Stewardship.” These scenarios were based partly on the IPCC Special Report on Emissions Scenarios framework and their representative concentration pathways (RCPs) and the widely used shared socio-economic pathways (SSPs). Together, these scenarios contrast local versus international emphasis on decision making, more versus less severe environmental change, and different consequences for producers due to future commodity prices, cash returns, and costs. The mid-century profitability of the typical farms was most sensitive to the future development of feed costs, price trends of returns, and marketing options as opposed to the direct effect of climate-driven changes in the environment. These results can inform adaptation planning by the European aquaculture sector. Moreover, applying consistent scenarios including societal and economic dimensions, facilitates regional to global comparisons of adaptation advice both within and across Blue Growth sectors

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

BACKGROUND: Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. METHODS: A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. RESULTS: We apply our approach to five malaria interventions under development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements. CONCLUSIONS: Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. This study highlights the role of mathematical models to support intervention development. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions

Dihaploid Coffea arabica genome sequencing and assembly.

Coffea arabica which accounts for 70% of world coffee production is an allotetraploid with a genome size of approximately 1.3 Gb and is derived from the hybridization of C. canephora (710 Mb) and C. eugenioides (670 Mb). To elucidate the evolutionary history of C. arabica, and generate critical information for breeding programs, a sequencing project is underway to finalize a reference genome using a dihaploid line and a set of Menu Abstract: Dihaploid Coffea arabica Genome Sequencing and Assembly (Plant and Animal Genome XXIII Conference) https://pag.confex.com/pag/xxiii/webprogram/Paper16983.html [25/02/2015 15:00:12] 30 C. arabica accessions

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies

TCT-260 Which is the Ideal Revascularization Strategy in Patients Presenting with Acute Coronary Syndrome and Proximal LAD Stenosis? Results from the ACUITY Study

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Measurement of B(B-->X_s {\gamma}), the B-->X_s {\gamma} photon energy spectrum, and the direct CP asymmetry in B-->X_{s+d} {\gamma} decays

The photon spectrum in B --> X_s {\gamma} decay, where X_s is any strange hadronic state, is studied using a data sample of (382.8\pm 4.2) \times 10^6 e^+ e^- --> \Upsilon(4S) --> BBbar events collected by the BABAR experiment at the PEP-II collider. The spectrum is used to measure the branching fraction B(B --> X_s \gamma) = (3.21 \pm 0.15 \pm 0.29 \pm 0.08)\times 10^{-4} and the first, second, and third moments = 2.267 \pm 0.019 \pm 0.032 \pm 0.003 GeV,, )^2> = 0.0484 \pm 0.0053 \pm 0.0077 \pm 0.0005 GeV^2, and )^3> = -0.0048 \pm 0.0011 \pm 0.0011 \pm 0.0004 GeV^3, for the range E_\gamma > 1.8 GeV, where E_{\gamma} is the photon energy in the B-meson rest frame. Results are also presented for narrower E_{\gamma} ranges. In addition, the direct CP asymmetry A_{CP}(B --> X_{s+d} \gamma) is measured to be 0.057 \pm 0.063. The spectrum itself is also unfolded to the B-meson rest frame; that is the frame in which theoretical predictions for its shape are made.Comment: 37 pages, 19 postscript figures, submitted to Phys. Rev. D. No analysis or results have changed from previous version. Some changes to improve clarity based on interactions with Phys. Rev. D referees, including one new Figure (Fig. 13), and some minor wording/punctuation/spelling mistakes fixe