84 resultados para 06 Biological Sciences


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Instances of parallel ecotypic divergence where adaptation to similar conditions repeatedly cause similar phenotypic changes in closely related organisms are useful for studying the role of ecological selection in speciation. Here we used a combination of traditional and next generation genotyping techniques to test for the parallel divergence of plants from the Senecio lautus complex, a phenotypically variable groundsel that has adapted to disparate environments in the South Pacific. Phylogenetic analysis of a broad selection of Senecio species showed that members of the S. lautus complex form a distinct lineage that has diversified recently in Australasia. An inspection of thousands of polymorphisms in the genome of 27 natural populations from the S. lautus complex in Australia revealed a signal of strong genetic structure independent of habitat and phenotype. Additionally, genetic differentiation between populations was correlated with the geographical distance separating them, and the genetic diversity of populations strongly depended on geographical location. Importantly, coastal forms appeared in several independent phylogenetic clades, a pattern that is consistent with the parallel evolution of these forms. Analyses of the patterns of genomic differentiation between populations further revealed that adjacent populations displayed greater genomic heterogeneity than allopatric populations and are differentiated according to variation in soil composition. These results are consistent with a process of parallel ecotypic divergence in face of gene flow.

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Understanding the evolutionary history and phylogenetic relationships between rare and common species is necessary for the effective management of rare species. The genus Cherax, a group of freshwater crayfish species, is of interest in this regard as a number of species are rare or have restricted distributions while other species are common and widespread. Here we describe the characterisation of three novel nuclear genes of the haemocyanin superfamily for phylogenetic reconstruction of the genus. All novel markers developed in this study amplified consistently in species from three divergent clades of the genus Cherax. The level of polymorphism found in these markers was consistently higher than that found in other nuclear genes previously used in invertebrate systematics, such as NaK ATP-ase. In combination, these markers will be useful to delineate phylogenetic relationships between rare and common Cherax species.

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Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

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Interest in insect small RNA viruses (SRVs) has grown slowly but steadily. A number of new viruses have been analyzed at the sequence level, adding to our knowledge of their diversity at the level of both individual virus species and families. In particular, a number of possible new virus families have emerged. This research has largely been driven by interest in their potential for pest control, as well as in their importance as the causal agents of disease in beneficial arthropods. At the same time, research into known viruses has made valuable contributions to our understanding of an emerging new field of central importance to molecular biology-the existence of RNA-based gene silencing, developmental control, and adaptive immune systems in eukaryotes. Subject to RNA-based adaptive immune responses in their hosts, viruses have evolved a variety of genes encoding proteins capable of suppressing the immune response. Such genes were first identified in plant viruses, but the first examples known from animal viruses were identified in insect RNA viruses. This chapter will address the diversity of insect SRVs, and attempts to harness their simplicity in the engineering of transgenic plants expressing viruses for resistance to insect pests. We also describe RNA interference and antiviral pathways identified in plants and animals, how they have led viruses to evolve genes capable of suppressing such adaptive immunity, and the problems presented by these pathways for the strategy of expressing viruses in transgenic plants. Approaches for countering these problems are also discussed. © 2006 Elsevier Inc. All rights reserved.

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Genetic studies are revealing the pathway for RNA-mediated gene silencing. Short RNA molecules are the key, giving sequence specificity for RNA degradation and mediating communication within and between cells; these short RNAs are common to transcriptional and post-transcriptional silencing pathways. The expression of transgenes in plants varies between independent transformants and there are many examples where the transgenic trait is not expressed, or disappears in subsequent generations, despite the presence of the transgene. This loss of a trait, but not of the transgene, has become known as gene silencing and can take two forms, transcriptional or post-transcriptional. As their names imply, transcriptional gene silencing occurs when a transgene is not transcribed, whereas in post-transcriptional gene silencing, the transgene mRNA is produced but degraded before it is translated (reviewed in [1]). Both forms of silencing seem to be the result of inherent mechanisms for protecting plants against mobile or invading DNA — for example, transposable elements or the T-DNA of Agrobacterium — or RNA viruses. Plants are not alone in their capacity for transgene silencing; both forms of silencing occur in flies and fungi, where it is known as RIP or quelling, while nematodes exhibit post-transcriptional silencing, generally referred to as RNA interference (RNAi). A clearer picture of the mechanisms and relationships of the different types of transgene silencing is beginning to emerge from a number of recent studies [2], [3], [4], [5], [6], [7] and [8]. Some of these studies [2], [3], [4] and [5] have enhanced our understanding of the steps within the post-transcriptional silencing pathway, and others [6], [7] and [8] have demonstrated that the two forms of silencing may be mechanistically linked.

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Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

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The following research reports the emergence of Leptospira borgpetersenii serovar Arborea as the dominant infecting serovar following the summer of disasters and the ensuing clean up in Queensland, Australia during 2011. For the 12 month period (1 January to 31 December) L. borgpetersenii serovar Arborea accounted for over 49% of infections. In response to a flooding event public health officials need to issue community wide announcements warning the population about the dangers of leptospirosis and other water borne diseases. Communication with physicians working in the affected community should also be increased to update physicians with information such as clinical presentation of leptospirosis and other waterborne diseases. These recommendations will furnish public health officials with considerations for disease management when dealing with future disaster management programs.

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Measuring Earth material behaviour on time scales of millions of years transcends our current capability in the laboratory. We review an alternative path considering multiscale and multiphysics approaches with quantitative structure-property relationships. This approach allows a sound basis to incorporate physical principles such as chemistry, thermodynamics, diffusion and geometry-energy relations into simulations and data assimilation on the vast range of length and time scales encountered in the Earth. We identify key length scales for Earth systems processes and find a substantial scale separation between chemical, hydrous and thermal diffusion. We propose that this allows a simplified two-scale analysis where the outputs from the micro-scale model can be used as inputs for meso-scale simulations, which then in turn becomes the micro-model for the next scale up. We present two fundamental theoretical approaches to link the scales through asymptotic homogenisation from a macroscopic thermodynamic view and percolation renormalisation from a microscopic, statistical mechanics view.

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The ability to understand and predict how thermal, hydrological,mechanical and chemical (THMC) processes interact is fundamental to many research initiatives and industrial applications. We present (1) a new Thermal– Hydrological–Mechanical–Chemical (THMC) coupling formulation, based on non-equilibrium thermodynamics; (2) show how THMC feedback is incorporated in the thermodynamic approach; (3) suggest a unifying thermodynamic framework for multi-scaling; and (4) formulate a new rationale for assessing upper and lower bounds of dissipation for THMC processes. The technique is based on deducing time and length scales suitable for separating processes using a macroscopic finite time thermodynamic approach. We show that if the time and length scales are suitably chosen, the calculation of entropic bounds can be used to describe three different types of material and process uncertainties: geometric uncertainties,stemming from the microstructure; process uncertainty, stemming from the correct derivation of the constitutive behavior; and uncertainties in time evolution, stemming from the path dependence of the time integration of the irreversible entropy production. Although the approach is specifically formulated here for THMC coupling we suggest that it has a much broader applicability. In a general sense it consists of finding the entropic bounds of the dissipation defined by the product of thermodynamic force times thermodynamic flux which in material sciences corresponds to generalized stress and generalized strain rates, respectively.

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Geoscientists are confronted with the challenge of assessing nonlinear phenomena that result from multiphysics coupling across multiple scales from the quantum level to the scale of the earth and from femtoseconds to the 4.5 Ga of history of our planet. We neglect in this review electromagnetic modelling of the processes in the Earth’s core, and focus on four types of couplings that underpin fundamental instabilities in the Earth. These are thermal (T), hydraulic (H), mechanical (M) and chemical (C) processes which are driven and controlled by the transfer of heat to the Earth’s surface. Instabilities appear as faults, folds, compaction bands, shear/fault zones, plate boundaries and convective patterns. Convective patterns emerge from buoyancy overcoming viscous drag at a critical Rayleigh number. All other processes emerge from non-conservative thermodynamic forces with a critical critical dissipative source term, which can be characterised by the modified Gruntfest number Gr. These dissipative processes reach a quasi-steady state when, at maximum dissipation, THMC diffusion (Fourier, Darcy, Biot, Fick) balance the source term. The emerging steady state dissipative patterns are defined by the respective diffusion length scales. These length scales provide a fundamental thermodynamic yardstick for measuring instabilities in the Earth. The implementation of a fully coupled THMC multiscale theoretical framework into an applied workflow is still in its early stages. This is largely owing to the four fundamentally different lengths of the THMC diffusion yardsticks spanning micro-metre to tens of kilometres compounded by the additional necessity to consider microstructure information in the formulation of enriched continua for THMC feedback simulations (i.e., micro-structure enriched continuum formulation). Another challenge is to consider the important factor time which implies that the geomaterial often is very far away from initial yield and flowing on a time scale that cannot be accessed in the laboratory. This leads to the requirement of adopting a thermodynamic framework in conjunction with flow theories of plasticity. This framework allows, unlike consistency plasticity, the description of both solid mechanical and fluid dynamic instabilities. In the applications we show the similarity of THMC feedback patterns across scales such as brittle and ductile folds and faults. A particular interesting case is discussed in detail, where out of the fluid dynamic solution, ductile compaction bands appear which are akin and can be confused with their brittle siblings. The main difference is that they require the factor time and also a much lower driving forces to emerge. These low stress solutions cannot be obtained on short laboratory time scales and they are therefore much more likely to appear in nature than in the laboratory. We finish with a multiscale description of a seminal structure in the Swiss Alps, the Glarus thrust, which puzzled geologists for more than 100 years. Along the Glarus thrust, a km-scale package of rocks (nappe) has been pushed 40 km over its footwall as a solid rock body. The thrust itself is a m-wide ductile shear zone, while in turn the centre of the thrust shows a mm-cm wide central slip zone experiencing periodic extreme deformation akin to a stick-slip event. The m-wide creeping zone is consistent with the THM feedback length scale of solid mechanics, while the ultralocalised central slip zones is most likely a fluid dynamic instability.

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The aim of the current study was to estimate heritabilities and correlations for body traits at different ages (Weeks 10 and 18 after stocking) in a giant freshwater prawn (Macrobrachium rosenbergii) population selected for fast growth rate in Vietnam. The dataset consisted of 4650 body records (2432 and 2218 records collected at Weeks 10 and 18, respectively) in the full pedigree comprising a total of 18 387 records. Variance and covariance components were estimated using restricted maximum likelihood fitting a multi-trait animal model. Estimates of heritability for body traits (bodyweight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) were moderate and ranged from 0.06 to 0.11 and from 0.11 to 0.22 at Weeks 10 and 18, respectively. Body-trait heritabilities estimated at Week 10 were not significantly lower than at Week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Our results suggested that selection for high growth rate in GFP can be undertaken successfully before full market size has been reached.

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Access to clean water is essential for human life and a critical issue facing much of modern society, especially as a result of the 21st Century triad of challenges – population growth, resource scarcity and pollution – which contribute to the rising complexity of providing adequate access to this essential resource for large parts of society. As such, there is now an increasing need for innovative solutions to source, treat and distribute water to cities across the globe. This position paper explores biomimicry – emulating natural form, function, process and systems – as an alternative and sustainable design approach to traditional water infrastructure systems. The key barriers to innovations such as biomimicry are summarised, indicating that regulatory and economic grounds are some of the major hindrances to integrating alternative design approaches in the water sector in developed countries. This paper examines some of the benefits of moving past these barriers to develop sustainable, efficient and resilient solutions that provide adequate access to water in the face of contemporary challenges.

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At the 2012 CDIO conference, it was clear to all that engineering for 21st Century challenges and opportunities will be critical to the success of society over the next 2-3 decades, in dealing with pressures including climate change, resource depletion and urban densification. Within this context there is a growing imperative for rapid curriculum renewal towards education for sustainable development across all types and disciplines of engineering education, around the world. Building on a paper presented by these authors at the 2012 CDIO conference, this 2013 roundtable will draw on participants’ experiences to discuss how sustainability knowledge and skills can be embedded within a CDIO-based program using a holistic approach to curriculum renewal. The highly interactive and dynamic session will include two parts: 1) a short presentation from the chairs of the roundtable on an emergent model for rapid curriculum renewal; and 2) a facilitated discussion with participants about challenges and opportunities for action. Session notes will be recorded for distribution among participants following the conference.

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A general chemo-enzymatic process has been developed to prepare enantiomerically pure L- and D-amino acids in high yield by deracemisation of racemic starting materials. The method has been developed from initial academic studies to be a robust, scalable industrial process. Unnatural amino acids, in high optical purity, are a rapidly growing class of intermediates required for pharmaceuticals, agrochemicals and other fine chemical applications. However, no single method has proven sufficiently adaptable to prepare these compounds generally at large scale. Our approach uses an enantioselective oxidase biocatalyst and a non-selective chemical reducing agent to effect the stereoinversion of one enantiomer and can result in an enantiomeric excess of > 99 % from a starting racemate, and product yields over 90 %. The current approach compares very favourably to resolution methods which have a maximum single pass yield of 50 %. Efficient methods have been developed to adapt the biocatalyst used in this process towards new target compounds and to optimise key factors which improve the process efficiency and offer competitive economics at scale.