Improving the agent selection, release and evaluation process: the role of bioclimatic modelling

The value of CLIMEX models to inform biocontrol programs was assessed, including predicting the potential distribution of biocontrol agents and their subsequent population dynamics, using bioclimatic models for the weed Parkinsonia aculeata, two Lantana camara biocontrol agents, and five Mimosa pigra biocontrol agents. The results showed the contribution of data types to CLIMEX models and the capacity of these models to inform and improve the selection, release and post release evaluation of biocontrol agents. Foremost among these was the quality of spatial and temporal information as well as the extent to which overseas range data samples the species’ climatic envelope. Post hoc evaluation and refinement of these models requires improved long-term monitoring of introduced agents and their dynamics at well selected study sites. The authors described the findings of these case studies, highlighted their implications, and considered how to incorporate models effectively into biocontrol programs.

Rain Damage to Strawberries Grown in Southeast Queensland: Evaluation and Genetic Control.

In Queensland, Australia, strawberries (Fragaria xananassa Duchesne) are grown in open fields and rainfall events can damage fruit. Cultivars that are resistant to rain damage may reduce losses and lower risk for the growers. However, little is known about the genetic control of resistance and in a subtropical climate, unpredictable rainfall events hamper evaluation. Rain damage was evaluated on seedling and clonal trials of one breeding population comprising 645 seedling genotypes and 94 clones and on a second clonal population comprising 46 clones from an earlier crossing to make preliminary estimates of heritability. The incidence of field damage from rainfall and damage after laboratory soaking was evaluated to determine if this soaking method could be used to evaluate resistance to rain damage. Narrow-sense heritability of resistance to rain damage calculated for seedlings was low (0.21 +/- 0.15) and not significantly different from zero; however, broad-sense heritability estimates were moderate in both seedlings (0.49 +/- 0.16) and clones (0.45 +/- 0.08) from the first population and similar in clones (0.56 +/- 0.21) from the second population. Immersion of fruit in deionized water produced symptoms consistent with rain damage in the field. Lengthening the duration of soaking of 'Festival' fruit in deionized water exponentially increased the proportion of damage to fruit ranging in ripeness from immature to ripe during the first 6-h period of soaking. When eight genotypes were evaluated, the proportion of sound fruit after soaking in deionized water in the laboratory for up to 5 h was linearly related (r(2) = 0.90) to the proportion of sound fruit in the field after 89 mm of rain. The proportion of sound fruit of the breeding genotype '2008-208' and 'Festival' under soaking (0.67, 0.60) and field (0.52, 0.43) evaluations, respectively, is about the same and these genotypes may be useful sources of resistance to rain damage.

Genetic effects and genetic relationships among shrunken (sh2) sweet corn lines and F1 hybrids

The objectives of this study were to quantify the components of genetic variance and the genetic effects, and to examine the genetic relationship of inbred lines extracted from various shrunken2(sh2) breeding populations. Ten diverse inbred lines developed from genetic background, were crossed in half diallel. Parents and their F1 hybrids were evaluated at three environments. The parents were genotyped using 20 polymorphic simple sequence repeats (SSR). Agronomic and quality traits were analysed by a mixed linear model according to additive-dominance genetic model. Genetic effects were estimated using an adjusted unbiased prediction method. Additive variance was more important than dominance variance in the expression of traits related to ear aspects (husk ratio and percentage of ear filled) and eating quality (flavour and total soluble solids). For agronomic traits, however, dominance variance was more important than additive variance. The additive genetic correlation between flavour and tenderness was strong (r = 0.84, P <0.01). Flavour, tenderness and kernel colour additive genetic effects were not correlated with yield related traits. Genetic distance (GD), estimated from SSR profiles on the basis of Jaccard's similarity coefficient varied from 0.10 to 0.77 with an average of 0.56. Cluster analysis classified parents according to their pedigree relationships. In most studied traits, F1 performance was not associated with GD.

Reciprocal and advanced generation hybrids between Corymbia citriodora and C-torelliana: forestry breeding and the risk of gene flow

Corymbia F1 hybrids have high potential for plantation forestry; however, little is known of their reproductive biology and potential for genetic pollution of native Corymbia populations. This study aims to quantify the influence of reproductive isolating barriers on the success of novel reciprocal and advanced generation Corymbia hybrids. Two maternal taxa, Corymbia citriodora subsp. citriodora and Corymbia torelliana, were pollinated using five paternal taxa, C. citriodora subsp. citriodora, C. torelliana, one C. torelliana x C. citriodora subsp. citriodora hybrid and two C. torelliana x C. citriodora subsp. variegata hybrids. Pollen tube, embryo and seed development were assessed. Reciprocal hybridisation between C. citriodora subsp. citriodora and C. torelliana was successful. Advanced generation hybrids were also created when C. citriodora subsp. citriodora or C. torelliana females were backcrossed with F1 hybrid taxa. Prezygotic reproductive isolation was identified via reduced pollen tube numbers in the style and reduced numbers of ovules penetrated by pollen tubes. Reproductive isolation was weakest within the C. citriodora subsp. citriodora maternal taxon, with two hybrid backcrosses producing equivalent capsule and seed yields to the intraspecific cross. High hybridising potential was identified between all Corymbia species and F1 taxa studied. This provides opportunities for advanced generation hybrid breeding, allowing desirable traits to be amplified. It also indicates risks of gene flow between plantation and native Corymbia populations.

Epidemiology and genetic diversity of Tobacco streak virus and related subgroup 1 ilarviruses

A quarter of Australia’s sunflower production is from the central highlands region of Queensland and is currently worth six million dollars ($AUD) annually. From the early 2000s a severe necrosis disorder of unknown aetiology was affecting large areas of sunflower crops in central Queensland, leading to annual losses of up to 20%. Other crops such as mung bean and cotton were also affected. This PhD study was undertaken to determine if the causal agent of the necrosis disorder was of viral origin and, if so, to characterise its genetic diversity, biology and disease cycle, and to develop effective control strategies. The research described in this thesis identified Tobacco streak virus (TSV; genus Ilarvirus, family Bromoviridae) as the causal agent of the previously unidentified necrosis disorder of sunflower in central Queensland. TSV was also the cause of commonly found diseases in a range of other crops in the same region including cotton, chickpea and mung bean. This was the first report from Australia of natural field infections of TSV from these four crops. TSV strains have previously been reported from other regions of Australia in several hosts based on serological and host range studies. In order to determine the relatedness of previously reported TSV strains with TSV from central Queensland, we characterised the genetic diversity of the known TSV strains from Australia. We identified two genetically distinct TSV strains from central Queensland and named them based on their major alternative hosts, TSV-parthenium from Parthenium hysterophorus and TSV-crownbeard from Verbesina encelioides. They share only 81 % total-genome nucleotide sequence identity. In addition to TSV-parthenium and TSV-crownbeard from central Queensland, we also described the complete genomes of two other ilarvirus species. This proved that previously reported TSV strains, TSV-S isolated from strawberry and TSV-Ag from Ageratum houstonianum, were actually the first record of Strawberry necrotic shock virus from Australia, and a new subgroup 1 ilarvirus, Ageratum latent virus. Our results confirmed that the TSV strains found in central Queensland were not related to previously described strains from Australia and may represent new incursions. This is the first report of the genetic diversity within subgroup 1 ilarviruses from Australia. Based on field observations we hypothesised that parthenium and crownbeard were acting as symptomless hosts of TSV-parthenium and TSV-crownbeard, respectively. We developed strain-specific multiplex PCRs for the three RNA segments to accurately characterise the range of naturally infected hosts across central Queensland. Results described in this thesis show compelling evidence that parthenium and crownbeard are the major (symptomless) alternative hosts of TSV-parthenium and TSV-crownbeard. While both TSV strains had wide natural host ranges, the geographical distribution of each strain was closely associated with the respective distribution of their major alternative hosts. Both TSV strains were commonly found across large areas of central Queensland, but we only found strong evidence for the TSV-parthenium strain being associated with major disease outbreaks in nearby crops. The findings from this study demonstrate that both TSV-parthenium and TSV-crownbeard have similar life cycles but some critical differences. We found both TSV strains to be highly seed transmitted from their respective major alternative hosts from naturally infected mother plants and survived in seed for more than 2 years. We conclusively demonstrated that both TSV strains were readily transmitted via virus-infected pollen taken from the major alternative hosts. This transmission was facilitated by the most commonly collected thrips species, Frankliniella schultzei and Microcephalothrips abdominalis. These results illustrate the importance of seed transmission and efficient thrips vector species for the effective survival of these TSV strains in an often harsh environment and enables the rapid development of TSV disease epidemics in surrounding crops. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was naturally infected by, and an experimental host of TSV-parthenium. However, this infection combination resulted in non-viable crownbeard seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. Based on our field observations we hypothesised that there were differences in relative tolerance to TSV infection between different sunflower hybrids and that seasonal variation in disease levels was related to rainfall in the critical early crop stage. Results from our field trials conducted over multiple years conclusively demonstrated significant differences in tolerance to natural infections of TSV-parthenium in a wide range of sunflower hybrids. Glasshouse tests indicate the resistance to TSV-parthenium identified in the sunflower hybrids is also likely to be effective against TSV-crownbeard. We found a significant negative association between TSV disease incidence in sunflowers and accumulated rainfall in the months of March and April with increasing rainfall resulting in reduced levels of disease. Our results indicate that the use of tolerant sunflower germplasm will be a critical strategy to minimise the risk of TSV epidemics in sunflower.

Concise review: Humanized models of tumor immunology in the 21st century: Convergence of cancer research and tissue engineering

Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Differences in host species relationships and biogeographic influences produce contrasting patterns of prevalence, community composition and genetic structure in two genera of avian malaria parasites in southern Melanesia

1. Host-parasite interactions have the potential to influence broadscale ecological and evolutionary processes, levels of endemism, divergence patterns and distributions in host populations. Understanding the mechanisms involved requires identification of the factors that shape parasite distribution and prevalence. 2. A lack of comparative information on community-level host-parasite associations limits our understanding of the role of parasites in host population divergence processes. Avian malaria (haemosporidian) parasites in bird communities offer a tractable model system to examine the potential for pathogens to influence evolutionary processes in natural host populations. 3. Using cytochrome b variation, we characterized phylogenetic diversity and prevalence of two genera of avian haemosporidian parasites, Plasmodium and Haemoproteus, and analysed biogeographic patterns of lineages across islands and avian hosts, in southern Melanesian bird communities to identify factors that explain patterns of infection. 4. Plasmodium spp. displayed isolation-by-distance effects, a significant amount of genetic variation distributed among islands but insignificant amounts among host species and families, and strong local island effects with respect to prevalence. Haemoproteus spp. did not display isolation-by-distance patterns, showed marked structuring of genetic variation among avian host species and families, and significant host species prevalence patterns. 5. These differences suggest that Plasmodium spp. infection patterns were shaped by geography and the abiotic environment, whereas Haemoproteus spp. infection patterns were shaped predominantly by host associations. Heterogeneity in the complement and prevalence of parasite lineages infecting local bird communities likely exposes host species to a mosaic of spatially divergent disease selection pressures across their naturally fragmented distributions in southern Melanesia. Host associations for Haemoproteus spp. indicate a capacity for the formation of locally co-adapted host-parasite relationships, a feature that may limit intraspecific gene flow or range expansions of closely related host species.

Development of Microfluidic Devices with the Use of Nanotechnology to Aid in the Analysis of Biological Systems Including Membrane Protein Separation, Single Cell Analysis, and Genetic Markers

Computation technology has dramatically changed the world around us; you can hardly find an area where cell phones have not saturated the market, yet there is a significant lack of breakthroughs in the development to integrate the computer with biological environments. This is largely the result of the incompatibility of the materials used in both environments; biological environments and experiments tend to need aqueous environments. To help aid in these development chemists, engineers, physicists and biologists have begun to develop microfluidics to help bridge this divide. Unfortunately, the microfluidic devices required large external support equipment to run the device. This thesis presents a series of several microfluidic methods that can help integrate engineering and biology by exploiting nanotechnology to help push the field of microfluidics back to its intended purpose, small integrated biological and electrical devices. I demonstrate this goal by developing different methods and devices to (1) separate membrane bound proteins with the use of microfluidics, (2) use optical technology to make fiber optic cables into protein sensors, (3) generate new fluidic devices using semiconductor material to manipulate single cells, and (4) develop a new genetic microfluidic based diagnostic assay that works with current PCR methodology to provide faster and cheaper results. All of these methods and systems can be used as components to build a self-contained biomedical device.

Genetic engineering of microorganisms: free release into the environment

Genetic engineering now makes possible the insertion of DNA from many organisms into other prokaryotic, eukaryotic and viral hosts. This technology has been used to construct a variety of such genetically engineered microorganisms (GEMs). The possibility of accidental or deliberate release of GEMs into the natural environment has recently raised much public concern. The prospect of deliberate release of these microorganisms has prompted an increased need to understand the processes of survival, expression, transfer and rearrangement of recombinant DNA molecules in microbial communities. The methodology which is being developed to investigate these processes will greatly enhance our ability to study microbial population ecology.