Eukaryotic expression:Developments for structural proteomics

The production of sufficient quantities of protein is an essential prelude to a structure determination, but for many viral and human proteins this cannot be achieved using prokaryotic expression systems. Groups in the Structural Proteomics In Europe (SPINE) consortium have developed and implemented high-throughput (HTP) methodologies for cloning, expression screening and protein production in eukaryotic systems. Studies focused on three systems: yeast (Pichia pastoris and Saccharomyces cerevisiae), baculovirus-infected insect cells and transient expression in mammalian cells. Suitable vectors for HTP cloning are described and results from their use in expression screening and protein-production pipelines are reported. Strategies for co-expression, selenomethionine labelling (in all three eukaryotic systems) and control of glycosylation (for secreted proteins in mammalian cells) are assessed. © International Union of Crystallography, 2006.

First year qualifying report: neural networks for extracting wind vectors from satellite scatterometer data

The ERS-1 Satellite was launched in July 1991 by the European Space Agency into a polar orbit at about km800, carrying a C-band scatterometer. A scatterometer measures the amount of radar back scatter generated by small ripples on the ocean surface induced by instantaneous local winds. Operational methods that extract wind vectors from satellite scatterometer data are based on the local inversion of a forward model, mapping scatterometer observations to wind vectors, by the minimisation of a cost function in the scatterometer measurement space.par This report uses mixture density networks, a principled method for modelling conditional probability density functions, to model the joint probability distribution of the wind vectors given the satellite scatterometer measurements in a single cell (the `inverse' problem). The complexity of the mapping and the structure of the conditional probability density function are investigated by varying the number of units in the hidden layer of the multi-layer perceptron and the number of kernels in the Gaussian mixture model of the mixture density network respectively. The optimal model for networks trained per trace has twenty hidden units and four kernels. Further investigation shows that models trained with incidence angle as an input have results comparable to those models trained by trace. A hybrid mixture density network that incorporates geophysical knowledge of the problem confirms other results that the conditional probability distribution is dominantly bimodal.par The wind retrieval results improve on previous work at Aston, but do not match other neural network techniques that use spatial information in the inputs, which is to be expected given the ambiguity of the inverse problem. Current work uses the local inverse model for autonomous ambiguity removal in a principled Bayesian framework. Future directions in which these models may be improved are given.

Structure and dynamics of multiple cationic vectors-siRNA complexation by all-atomic molecular dynamics simulations

Understanding the molecular mechanism of gene condensation is a key component to rationalizing gene delivery phenomena, including functional properties such as the stability of the gene-vector complex and the intracellular release of the gene. In this work, we adopt an atomistic molecular dynamics simulation approach to study the complexation of short strand duplex RNA with four cationic carrier systems of varying charge and surface topology at different charge ratios. At lower charge ratios, polymers bind quite effectively to siRNA, while at high charge ratios, the complexes are saturated and there are free polymers that are unable to associate with RNA. We also observed reduced fluctuations in RNA structures when complexed with multiple polymers in solution as compared to both free siRNA in water and the single polymer complexes. These novel simulations provide a much better understanding of key mechanistic aspects of gene-polycation complexation and thereby advance progress toward rational design of nonviral gene delivery systems.

Insect pest control research : the analysis of historical trends with special reference to scientometric analysis

The thesis investigates the value of quantitative analyses for historical studies of science through an examination of research trends in insect pest control, or economic entomology. Reviews are made of quantitative studies of science, and historical studies of pest control. The methodological strengths and weaknesses of bibliometric techniques are examined in a special chapter; techniques examined include productivity studies such as paper counts, and relational techniques such as co-citation and co-word analysis. Insect pest control is described. This includes a discussion of the socio-economic basis of the concept of `pest'; a series of classifications of pest control techniques are provided and analysed with respect to their utility for scientometric studies. The chemical and biological approaches to control are discussed as scientific and technological paradigms. Three case studies of research trends in economic entomology are provided. First a scientometric analysis of samples of chemical control and biological control papers; providing quantitative data on institutional, financial, national, and journal structures associated with pest control research fields. Second, a content analysis of a core journal, the Journal of Economic Entomology, over a period of 1910-1985; this identifies the main research innovations and trends, in particular the changing balance between chemical and biological control. Third, an analysis of historical research trends in insecticide research; this shows the rise, maturity and decline of research of many groups of compounds. These are supplemented by a collection of seven papers on scientometric studies of pest control and quantitative techniques for analysing science.

Neural networks for modelling wind vectors

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Estimation of the Offspring and Immigration Mean Vectors for Bisexual Branching Processes with Immigration of Females and Males

2000 Mathematics Subject Classification: 60J80, 62M05.

Seasonal dynamic pattern analysis in service of climate change research. A methodical case-study - monitoring and simulation based on an aquatic insect community

Our aim was to approach an important and well-investigable phenomenon – connected to a relatively simple but real field situation – in such a way, that the results of field observations could be directly comparable with the predictions of a simulation model-system which uses a simple mathematical apparatus and to simultaneously gain such a hypothesis-system, which creates the theoretical opportunity for a later experimental series of studies. As a phenomenon of the study, we chose the seasonal coenological changes of aquatic and semiaquatic Heteroptera community. Based on the observed data, we developed such an ecological model-system, which is suitable for generating realistic patterns highly resembling to the observed temporal patterns, and by the help of which predictions can be given to alternative situations of climatic circumstances not experienced before (e.g. climate changes), and furthermore; which can simulate experimental circumstances. The stable coenological state-plane, which was constructed based on the principle of indirect ordination is suitable for unified handling of data series of monitoring and simulation, and also fits for their comparison. On the state-plane, such deviations of empirical and model-generated data can be observed and analysed, which could otherwise remain hidden.

Comparative analysis of the relationship between phenological phenomena and meteorological indicators based on insect and plant monitoring

Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors.

Ornamental plants as climatic indicators of arthropod vectors

The importance and risk of vector-borne diseases (eg. leishmaniasis, West Nile Virus, Lyme borreliosis) is going to increase in the European temperate areas due to climate change. Our previous studies have shown that the potential distribution of Leishmania infantum and some Phlebotomus (sand fly) species – a parasite of leishmaniasis, and its vectors – may be expanded even to the southern coastline of the Baltic Sea by the end of the 21st century. The lowland areas of the Carpathian Basin and the main part of Hungary are projected to be suitable for the studied sand fly vectors in the near future. It is important to find some indicator plants to examine whether the sand flies are able to live in a certain climate at a certain time. We studied several Mediterranean and Sub-Mediterranean plant species, and we found that the aggregated distribution of three ligneous species (Juniperus oxycedrus L., Quercus ilex L. and Pinus brutia Ten.) shows high correlation with the union distribution of five sand flies (Phlebotomus ariasi Tonn., Ph. neglectus Tonn., Ph. perfiliewi Parrot, Ph. perniciosus Newst. and Ph. tobbi Adler, Theodor et Lourie). Since these Mediterranean species are highly tolerant of the edaphic characteristics of the planting site, they may prove to be good indicators. The present and upcoming climate of Hungary is seen to be suitable for the selected indicator plant species, and it draws attention to and verifies the potential of the expansion of sand flies, which has been proved by some recent observations of the vectors in Southern Hungary.

Ornamental plants as climatic indicators of arthropod vectors

The importance and risk of vector-borne diseases (e.g., leishmaniasis, West Nile Virus, Lyme borreliosis) is going to increase in the European temperate areas due to climate change. Our previous studies have shown that the potential distribution of Leishmania infantum and some Phlebotomus (sand fly) species – a parasite of leishmaniasis, and its vectors – may be expanded even to the southern coastline of the Baltic Sea by the end of the 21st century. The lowland areas of the Carpathian Basin and the main part of Hungary are projected to be suitable for the studied sand fly vectors in the near future. It is important to find some indicator plants to examine whether the sand flies are able to live in a certain climate at a certain time. We studied several Mediterranean and Sub-Mediterranean plant species, and we found that the aggregated distribution of three ligneous species (Juniperus oxycedrus L., Quercus ilex L. and Pinus brutia Ten.) shows high correlation with the union distribution of five sand flies (Phlebotomus ariasi Tonn., Ph. neglectus Tonn., Ph. perfiliewi Parrot, Ph. perniciosus Newst. and Ph. tobbi Adler, Theodor et Lourie). Since these Mediterranean species are highly tolerant of the edaphic characteristics of the planting site, they may prove to be good indicators. The present and upcoming climate of Hungary is seen to be suitable for the selected indicator plant species, and it draws attention to and verifies the potential of the expansion of sand flies, which has been proved by some recent observations of the vectors in Southern Hungary.

Canals as Vectors for Fish Movement: Potential Southward Range Expansion of Lepisosteus osseus L. (Longnose Gar) in South Florida

Lepisosteus osseus (Longnose Gar) is a large-bodied predator, whose Florida distribution remains unclear at the southern edge of its range. We reviewed available literature and museum voucher specimens to provide a more accurate range description, and we discuss recent collections in south Florida. Longnose Gar has not been previously reported in natural habitats south of Lake Okeechobee. Instead, records south of the lake are from canals, and most are recent (since 2000), including our own southernmost 2011 record. No records from Everglades natural habitats have been collected. Previous studies have shown native range expansions in anthropogenically disturbed landscapes. We suggest that the Longnose Gar is expanding its range southward in Florida using canals as dispersal vectors and/or suitable habitat.