12 research outputs found

    Detection of a Fourth Orbivirus Non-Structural Protein

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    The genus Orbivirus includes both insect and tick-borne viruses. The orbivirus genome, composed of 10 segments of dsRNA, encodes 7 structural proteins (VP1–VP7) and 3 non-structural proteins (NS1–NS3). An open reading frame (ORF) that spans almost the entire length of genome segment-9 (Seg-9) encodes VP6 (the viral helicase). However, bioinformatic analysis recently identified an overlapping ORF (ORFX) in Seg-9. We show that ORFX encodes a new non-structural protein, identified here as NS4. Western blotting and confocal fluorescence microscopy, using antibodies raised against recombinant NS4 from Bluetongue virus (BTV, which is insect-borne), or Great Island virus (GIV, which is tick-borne), demonstrate that these proteins are synthesised in BTV or GIV infected mammalian cells, respectively. BTV NS4 is also expressed in Culicoides insect cells. NS4 forms aggregates throughout the cytoplasm as well as in the nucleus, consistent with identification of nuclear localisation signals within the NS4 sequence. Bioinformatic analyses indicate that NS4 contains coiled-coils, is related to proteins that bind nucleic acids, or are associated with membranes and shows similarities to nucleolar protein UTP20 (a processome subunit). Recombinant NS4 of GIV protects dsRNA from degradation by endoribonucleases of the RNAse III family, indicating that it interacts with dsRNA. However, BTV NS4, which is only half the putative size of the GIV NS4, did not protect dsRNA from RNAse III cleavage. NS4 of both GIV and BTV protect DNA from degradation by DNAse. NS4 was found to associate with lipid droplets in cells infected with BTV or GIV or transfected with a plasmid expressing NS4

    An ecological future for weed science to sustain crop production and the environment. A review

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    Sustainable strategies for managing weeds are critical to meeting agriculture's potential to feed the world's population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weedsat the agroecosystem levelthat, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management

    Simulation of Load Cycles in Pressurized SOFC Systems and Economic Evaluation

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    As known from literature [1], the pressurization of SOFC systems may lead to increased efficiencies and higher power output. These benefits will have to be utilized in future power generation in order to meet the requirements of higher electrical power demand as well as the goals of lower emissions. Operating a hybrid power plant at full load only is not always an option. Small power plants have to be able to run in load-following mode in order to keep the load of the grid low. By alternating the power of the gas turbine, a hybrid power plant would only be capable of following load in a band of 100 to 80%. Therefore, load alternation of the SOFC system is crucial for the operation of a hybrid power plant. The model of an SOFC system in a hybrid power plant has been presented before [2]. In this presentation we focus on the load-following capability of the modelled SOFC system. A series of step responses in load demand was applied to the system model, giving a close insight into the systems dynamic capabilities. These step responses will be discussed in detail and rules for dynamic system operation will be developed from these simulations. These rules have to be applied in order to keep the system within safe operation boundaries. Further complete load cycle simulations will be presented based on typical household load demands showing the dynamic capability of the pressurized fuel cell system. The prospects of pressurized SOFC systems in stationary power generation will be discussed on the basis of economical considerations. The operation of the SOFC at full load operation as well as at dynamic load conditions will be considered. 1. Virkar, The effect of pressure on solid oxide fuel cell performance. 1997, Westinghouse Electric Corporation, University of Utah, Department of Material's Science and Engineering. 2. F. Leucht and K. A. Friedrich, "SOFC System Modelling in the Hybrid Power Plant Project," in Proceedings of the 6th Symposium on Fuel Cell Modelling and Experimental Validation, Bad Herrenalb (Germany) (2009)

    δ13C Measurements as Indicators of Carbon Flow in Marine and Freshwater Ecosystems

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