316 resultados para animal-plant interactions


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A high-throughput method of isolating and cloning geminivirus genomes from dried plant material, by combining an Extract-n-Amp™-based DNA isolation technique with rolling circle amplification (RCA) of viral DNA, is presented. Using this method an attempt was made to isolate and clone full geminivirus genomes/genome components from 102 plant samples, including dried leaves stored at room temperature for between 6 months and 10 years, with an average hands-on-time to RCA-ready DNA of 15 min per 20 samples. While storage of dried leaves for up to 6 months did not appreciably decrease cloning success rates relative to those achieved with fresh samples, efficiency of the method decreased with increasing storage time. However, it was still possible to clone virus genomes from 47% of 10-year-old samples. To illustrate the utility of this simple method for high-throughput geminivirus diversity studies, six Maize streak virus genomes, an Abutilon mosaic virus DNA-B component and the DNA-A component of a previously unidentified New Word begomovirus species were fully sequenced. Genomic clones of the 69 other viruses were verified as such by end sequencing. This method should be extremely useful for the study of any circular DNA plant viruses with genome component lengths smaller than the maximum size amplifiable by RCA. © 2008 Elsevier B.V. All rights reserved.

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This relatively new biennial meeting - the first was in Prague in 2005 - was chaired by Julian Ma (Guy's Hospital, London, UK), with Mario Pezzotti (University of Verona, Italy) as local organizer, and attracted approximately 180 delegates from 25 countries. The theme was 'Plant Expression Systems for Recombinant Pharmacologics': there were 46 talks gathered into two plenaries, 12 themed sessions and 72 posters. Topics covered included publicly funded and commercial developments, innovation, regulation and commercialization, competition with conventional technology, manufacture and new products. © 2009 Expert Reviews Ltd.

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Background. A variety of interactions between up to three different movement proteins (MPs), the coat protein (CP) and genomic DNA mediate the inter- and intra-cellular movement of geminiviruses in the genus Begomovirus. Although movement of viruses in the genus Mastrevirus is less well characterized, direct interactions between a single MP and the CP of these viruses is also clearly involved in both intra- and intercellular trafficking of virus genomic DNA. However, it is currently unknown how specific these MP-CP interactions are, nor how disruption of these interactions might impact on virus viability. Results. Using chimaeric genomes of two strains of Maize streak virus (MSV) we adopted a genetic approach to investigate the gross biological effects of interfering with interactions between virus MP and CP homologues derived from genetically distinct MSV isolates. MP and CP genes were reciprocally exchanged, individually and in pairs, between maize (MSV-Kom)- and Setaria sp. (MSV-Set)-adapted isolates sharing 78% genome-wide sequence identity. All chimaeras were infectious in Zea mays c.v. Jubilee and were characterized in terms of symptomatology and infection efficiency. Compared with their parental viruses, all the chimaeras were attenuated in symptom severity, infection efficiency, and the rate at which symptoms appeared. The exchange of individual MP and CP genes resulted in lower infection efficiency and reduced symptom severity in comparison with exchanges of matched MP-CP pairs. Conclusion. Specific interactions between the mastrevirus MP and CP genes themselves and/or their expression products are important determinants of infection efficiency, rate of symptom development and symptom severity. © 2008 van der Walt et al; licensee BioMed Central Ltd.

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In the past few years, plant biotechnology has gone beyond traditional agricultural production of food, feed and fibre, and moved to address more complex contemporary health, social and industrial challenges. The new era involves production of novel pharmaceutical products, speciality and fine chemicals, phytoremediation and production of renewable energy resources to replace non-renewable fossil fuels. Plants have been shown to provide a genuine and low-cost alternative production system for high-value products. Currently, the principal plant-made products include antibodies, feed additives, vaccine antigens and hormones for human and animal health, and industrial proteins. Despite the unique advantages of scalability, cost and product safety, issues of politics, environmental impact, regulation and socioeconomics still limit the adoption of biopharmaceuticals, especially in the developing world. Plant-based production systems have further complicated biosafety, gene flow and environmental impact assessments with generally genetically modified plants, topics that are already partially understood. This article provides a background to biopharming, highlighting basic considerations for risk assessment and regulation in developing countries, with an emphasis on plant-based vaccine production in South Africa.

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In this paper, we present TiltZoom, a collection of tilt-based interaction techniques designed for easy one-handed zooming on mobile devices. TiltZoom represents novel gestural interaction techniques, implemented using rate-of-rotation readings from a gyroscope, a sensor commonly embedded on current generation smart phones. We designed and experimented three variants of TiltZoom - Tilt Level, Tilt and Hold and Flip Gesture. The design decisions for all three variants are discussed in this paper and their performance, as well as subjective user experience are evaluated and compared against conventional touch-based zooming techniques. TiltZoom appears to be a worthy addition to current established collection of gesture-based mobile interaction techniques for zooming controls, especially when user has only one hand available when moving about.

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Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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The concept of the cellular glycoprotein vitronectin acts as a biological ‘glue’ and key controller of mammalian tissue repair and remodelling activity is emerging from nearly 50 years of experimental in vitro and in vivo data. Unexpectedly, the vitronectin-knock-out mouse was found to be viable and to have largely normal phenotype. However, diligent observation revealed that the VN-KO animal exhibits delayed coagulation and poor wound healing. This is interpreted to indicate that vitronectin occupies a role in the earliest events of thrombogenesis and tissue repair. That role is as a foundation upon which the thrombus grows in an organised structure. In addition to closing the wound, the thrombus also serves to protect the underlying tissue from oxidation, is a reservoir of mitogens and tissue repair mediators and provides a provisional scaffold for the repairing tissue. In the absence of vitronectin (e.g. VN-KO animal) this cascade is disrupted before it begins. Our data demonstrates that a wide variety of biologically active species associate with VN. While initial studies were focused on mitogens, other classes of bioactives (e.g. glycosaminoglycans, metalloproteinases) are now also known to specifically interact with VN. Many of these interactions are long-lived, often resulting in multi-protein complexes, while others are stable for prolonged periods. Multiprotein complexes provide several advantages: prolonging molecular interaction; sustaining local concentrations, facilitating co-stimulation of cell surface receptors and thereby enhancing cellular / biological responses. We contend that these, or equivalent, multi-protein complexes mediate vitronectin functionality in vivo. It is also likely that many of the species demonstrated to associate with vitronectin in vitro, also associate with vitronectin in vivo in similar multi-protein complexes. Thus the predominant biological function of vitronectin is that of a master controller of the extracellular environment; informing, and possibly instructing cells ‘where’ to behave, ‘when’ to behave, and ‘how’ to behave (i.e. appropriately for the current circumstance).

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This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

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New substation technology, such as non-conventional instrument transformers,and a need to reduce design and construction costs, are driving the adoption of Ethernet based digital process bus networks for high voltage substations. Protection and control applications can share a process bus, making more efficient use of the network infrastructure. This paper classifies and defines performance requirements for the protocols used in a process bus on the basis of application. These include GOOSE, SNMP and IEC 61850-9-2 sampled values. A method, based on the Multiple Spanning Tree Protocol (MSTP) and virtual local area networks, is presented that separates management and monitoring traffic from the rest of the process bus. A quantitative investigation of the interaction between various protocols used in a process bus is described. These tests also validate the effectiveness of the MSTP based traffic segregation method. While this paper focusses on a substation automation network, the results are applicable to other real-time industrial networks that implement multiple protocols. High volume sampled value data and time-critical circuit breaker tripping commands do not interact on a full duplex switched Ethernet network, even under very high network load conditions. This enables an efficient digital network to replace a large number of conventional analog connections between control rooms and high voltage switchyards.

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Purpose: Service research typically relates switching costs to customer loyalty, and portrays them as effective switching deterrents that engender harmful word-of-mouth (WOM). Rather than to customer loyalty, this paper aims to relate switching costs to consumer inertia, and show that while switching costs may result in customer retention, they can engender positive and negative WOM. This depends on whether the inertia stems from satisfaction or indifference. Design/methodology/approach: A mall-intercept survey investigated 518 customers' perceptions of their mobile phone service providers. Structural equation modelling fitted the data to the conceptual model. Findings: Switching costs deterred switching and engendered negative WOM, but only with low-inertia customers. With high-inertia customers, retention and WOM behaviours depended on whether the inertia stemmed from satisfaction or indifference. Satisfied customers with high switching costs tended to stay, gave more positive and less negative WOM. With indifferent customers, switching costs were unrelated to retention or WOM behaviours. Research limitations/implications: While they may be perceived negatively, switching costs can engender PWOM. Hence, research should not consider switching costs alone without considering the context that produces them. Practical implications: Service providers should segment their customers into low-inertia, high-inertia/satisfied and high-inertia/indifferent, and target each segment differently. By converting customers into the high-inertia/satisfied segment, service providers can make the best use of switching costs – not only in the traditional sense as a barrier to defection, but also as a way of generating positive WOM. Originality/value: This study is the first to consider the role of inertia with switching costs, positive WOM, and negative WOM. The findings suggest that past studies portraying switching costs as negative impediments that evoke only negative WOM might be misleading.

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Despite efforts to motivate students to engage in Science, technology, engineering and mathematics (STEM) education, women are still underrepresented in these areas in the workforce and higher education. Targeting females at high school or earlier may be a key towards engaging them in STEM. In this paper we report on the research question: How do middle school females interact for learning about engineering education? This ethnographic study, part of a three-year longitudinal research project, investigated Year 8 female students’ learning about engineering concepts associated with designing, constructing, testing, and evaluating a catapult. Through a series of lead-up lessons and the four lesson catapult challenge (total of 18 x 45-minute lessons over 9 weeks), data from two girls within a focus group showed that the students needed to: (1) receive clarification on engineering terms to facilitate more fluent discourse, (2) question and debate conceptual understandings without peers being judgemental, and (3) have multiple opportunities for engaging with materials towards designing, constructing and explaining key concepts learnt. Implications for teachers undertaking STEM education are evident, including outlining expectations for clarifying STEM terms, outlining to students about interacting non-judgementally, and providing multiple opportunities for interacting within engineering education.

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The three-component reaction-diffusion system introduced in [C. P. Schenk et al., Phys. Rev. Lett., 78 (1997), pp. 3781–3784] has become a paradigm model in pattern formation. It exhibits a rich variety of dynamics of fronts, pulses, and spots. The front and pulse interactions range in type from weak, in which the localized structures interact only through their exponentially small tails, to strong interactions, in which they annihilate or collide and in which all components are far from equilibrium in the domains between the localized structures. Intermediate to these two extremes sits the semistrong interaction regime, in which the activator component of the front is near equilibrium in the intervals between adjacent fronts but both inhibitor components are far from equilibrium there, and hence their concentration profiles drive the front evolution. In this paper, we focus on dynamically evolving N-front solutions in the semistrong regime. The primary result is use of a renormalization group method to rigorously derive the system of N coupled ODEs that governs the positions of the fronts. The operators associated with the linearization about the N-front solutions have N small eigenvalues, and the N-front solutions may be decomposed into a component in the space spanned by the associated eigenfunctions and a component projected onto the complement of this space. This decomposition is carried out iteratively at a sequence of times. The former projections yield the ODEs for the front positions, while the latter projections are associated with remainders that we show stay small in a suitable norm during each iteration of the renormalization group method. Our results also help extend the application of the renormalization group method from the weak interaction regime for which it was initially developed to the semistrong interaction regime. The second set of results that we present is a detailed analysis of this system of ODEs, providing a classification of the possible front interactions in the cases of $N=1,2,3,4$, as well as how front solutions interact with the stationary pulse solutions studied earlier in [A. Doelman, P. van Heijster, and T. J. Kaper, J. Dynam. Differential Equations, 21 (2009), pp. 73–115; P. van Heijster, A. Doelman, and T. J. Kaper, Phys. D, 237 (2008), pp. 3335–3368]. Moreover, we present some results on the general case of N-front interactions.

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Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

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In 2007, the Queensland University of Technology (QUT) received funding from the Australian Government through the NCRIS program and from the then Queensland Government Department of State Development to construct a pilot research and development facility for the production of bioethanol and other renewable biocommodities from biomass including sugar cane bagasse. This facility is being constructed adjacent to the Racecourse Sugar Mill in Mackay and is known as the Mackay Renewable Biocommodities Pilot Plant (MRBPP). The MRBPP will be capable of processing biomass through a pressurised pretreatment reactor and includes equipment for enzymatic saccharification, fermentation and distillation to produce ethanol. Lignin and fermentation co-products will also be produced at a pilot scale for product development and testing.