A Cellular Automata Model for Citrus Variagated Chlorosis

A cellular automata model is proposed to analyze the progress of Citrus Variegated Chlorosis epidemics in S\~ao Paulo oranges plantation. In this model epidemiological and environmental features, such as motility of sharpshooter vectors which perform L\'evy flights, hydric and nutritional level of plant stress and seasonal climatic effects, are included. The observed epidemics data were quantitatively reproduced by the proposed model varying the parameters controlling vectors motility, plant stress and initial population of diseased plants.Comment: 10 pages, 10 figures, Scheduled tentatively for the issue of: 01Nov0

Finding and evaluating community structure in networks

We propose and study a set of algorithms for discovering community structure in networks -- natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.Comment: 16 pages, 13 figure

Virus Infection Suppresses Nicotiana benthamiana Adaptive Phenotypic Plasticity

Competition and parasitism are two important selective forces that shape life-histories, migration rates and population dynamics. Recently, it has been shown in various pathosystems that parasites can modify intraspecific competition, thus generating an indirect cost of parasitism. Here, we investigated if this phenomenon was present in a plant-potyvirus system using two viruses of different virulence (Tobacco etch virus and Turnip mosaic virus). Moreover, we asked if parasitism interacted with the shade avoidance syndrome, the plant-specific phenotypic plasticity in response to intraspecific competition. Our results indicate that the modification of intraspecific competition by parasitism is not present in the Nicotiana benthamiana – potyvirus system and suggests that this phenomenon is not universal but depends on the peculiarities of each pathosystem. However, whereas the healthy N. benthamiana presented a clear shade avoidance syndrome, this phenotypic plasticity totally disappeared when the plants were infected with TEV and TuMV, very likely resulting in a fitness loss and being another form of indirect cost of parasitism. This result suggests that the suppression or the alteration of adaptive phenotypic plasticity might be a component of virulence that is often overlooked

Monitoring the spread of water hyacinth (Pontederia crassipes): challenges and future developments

Water hyacinth (Pontederia crassipes, also referred to as Eicchornia crassipes) is one of the most invasive weed species in the world, causing significant adverse economic and ecological impacts, particularly in tropical and sub-tropical regions. Large scale real-time monitoring of areas of chronic infestation is critical to formulate effective control strategies for this fast spreading weed species. Assessment of revenue generation potential of the harvested water hyacinth biomass also requires enhanced understanding to estimate the biomass yield potential for a given water body. Modern remote sensing technologies can greatly enhance our capacity to understand, monitor and estimate water hyacinth infestation within inland as well as coastal freshwater bodies. Readily available satellite imagery with high spectral, temporal and spatial resolution, along with conventional and modern machine learning techniques for automated image analysis, can enable discrimination of water hyacinth infestation from other floating or submerged vegetation. Remote sensing can potentially be complemented with an array of other technology-based methods, including aerial surveys, ground-level sensors, and citizen science, to provide comprehensive, timely and accurate monitoring. This review discusses the latest developments in the use of remote sensing and other technologies to monitor water hyacinth infestation, and proposes a novel, multi-modal approach that combines the strengths of the different methods

A Rice Plastidial Nucleotide Sugar Epimerase Is Involved in Galactolipid Biosynthesis and Improves Photosynthetic Efficiency

Photosynthesis is the final determinator for crop yield. To gain insight into genes controlling photosynthetic capacity, we selected from our large T-DNA mutant population a rice stunted growth mutant with decreased carbon assimilate and yield production named photoassimilate defective1 (phd1). Molecular and biochemical analyses revealed that PHD1 encodes a novel chloroplast-localized UDP-glucose epimerase (UGE), which is conserved in the plant kingdom. The chloroplast localization of PHD1 was confirmed by immunoblots, immunocytochemistry, and UGE activity in isolated chloroplasts, which was approximately 50% lower in the phd1-1 mutant than in the wild type. In addition, the amounts of UDP-glucose and UDP-galactose substrates in chloroplasts were significantly higher and lower, respectively, indicating that PHD1 was responsible for a major part of UGE activity in plastids. The relative amount of monogalactosyldiacylglycerol (MGDG), a major chloroplast membrane galactolipid, was decreased in the mutant, while the digalactosyldiacylglycerol (DGDG) amount was not significantly altered, suggesting that PHD1 participates mainly in UDP-galactose supply for MGDG biosynthesis in chloroplasts. The phd1 mutant showed decreased chlorophyll content, photosynthetic activity, and altered chloroplast ultrastructure, suggesting that a correct amount of galactoglycerolipids and the ratio of glycolipids versus phospholipids are necessary for proper chloroplast function. Downregulated expression of starch biosynthesis genes and upregulated expression of sucrose cleavage genes might be a result of reduced photosynthetic activity and account for the decreased starch and sucrose levels seen in phd1 leaves. PHD1 overexpression increased photosynthetic efficiency, biomass, and grain production, suggesting that PHD1 plays an important role in supplying sufficient galactolipids to thylakoid membranes for proper chloroplast biogenesis and photosynthetic activity. These findings will be useful for improving crop yields and for bioenergy crop engineering

Approachability in Stackelberg Stochastic Games with Vector Costs

The notion of approachability was introduced by Blackwell [1] in the context of vector-valued repeated games. The famous Blackwell's approachability theorem prescribes a strategy for approachability, i.e., for `steering' the average cost of a given agent towards a given target set, irrespective of the strategies of the other agents. In this paper, motivated by the multi-objective optimization/decision making problems in dynamically changing environments, we address the approachability problem in Stackelberg stochastic games with vector valued cost functions. We make two main contributions. Firstly, we give a simple and computationally tractable strategy for approachability for Stackelberg stochastic games along the lines of Blackwell's. Secondly, we give a reinforcement learning algorithm for learning the approachable strategy when the transition kernel is unknown. We also recover as a by-product Blackwell's necessary and sufficient condition for approachability for convex sets in this set up and thus a complete characterization. We also give sufficient conditions for non-convex sets.Comment: 18 Pages, Submitted to Dynamic Games and Application

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Plant-Type Trehalose Synthetic Pathway in Cryptosporidium and Some Other Apicomplexans

The trehalose synthetic pathway is present in bacteria, fungi, plants and invertebrate animals, but is absent in vertebrates. This disaccharide mainly functions as a stress protectant against desiccation, heat, cold and oxidation. Genes involved in trehalose synthesis have been observed in apicomplexan parasites, but little was known about these enzymes. Study on trehalose synthesis in apicomplexans would not only shed new light into the evolution of this pathway, but also provide data for exploring this pathway as novel drug target.We have observed the presence of the trehalose synthetic pathway in Cryptosporidium and other apicomplexans and alveolates. Two key enzymes (trehalose 6-phosphate synthase [T6PS; EC 2.4.1.15] and trehalose phosphatase [TPase; EC 3.1.3.12] are present as Class II bifunctional proteins (T6PS-TPase) in the majority of apicomplexans with the exception of Plasmodium species. The enzyme for synthesizing the precursor (UDP-glucose) is homologous to dual-substrate UDP-galactose/glucose pyrophosphorylases (UGGPases), rather than the "classic" UDP-glucose pyrophosphorylase (UGPase). Phylogenetic recontructions indicate that both T6PS-TPases and UGGPases in apicomplexans and other alveolates are evolutionarily affiliated with stramenopiles and plants. The expression level of T6PS-TPase in C. parvum is highly elevated in the late intracellular developmental stage prior to or during the production of oocysts, implying that trehalose may be important in oocysts as a protectant against environmental stresses. Finally, trehalose has been detected in C. parvum oocysts, thus confirming the trehalose synthetic activity in this parasite.A trehalose synthetic pathway is described in the majority of apicomplexan parasites including Cryptosporidium and the presence of trehalose was confirmed in the C. parvum oocyst. Key enzymes in the pathway (i.e., T6PS-TPase and UGGPase) are plant-type and absent in humans and animals, and may potentially serve as novel drug targets in the apicomplexans