Evidence of a spotted fever-like rickettsia and a potential new vector from northeastern Australia

A spotted fever-like rickettsia was identified in a Hemaphysalis tick by polymerase chain reaction (PCR) amplification and sequencing of the 16S rDNA, ompA, and ompB genes. A comparison of these nucleotide sequences with those of other spotted fever group (SFG) rickettsiae revealed that the Hemaphysalis tick rickettsia was distinct from other previously reported strains. Phylogenetic analysis based on both ompA and ompB also indicates that the strain’s closest relatives are the agents of Thai tick typhus (Rickettsia honei strain TT-118) and Flinders Island spotted fever (R. honei). This study represents the first report of an R. honei-like agent from a Hemaphysalis tick in Australia and of a spotted fever group rickettsia from Cape York Peninsula, Queensland.

Semliki Forest virus as an expression vector in insect cell lines

Studies were undertaken to determine if replication-deficient Semliki Forest virus expression vectors could be successfully used to express foreign gene constructs in insect cell lines. Using green fluorescent protein (GFP) as a marker we recorded infection levels of nearly 100% in the Aedes albopictus cell lines C6/36 and Aa23T, as well as in the Ae. aegypti cell line MOS20. The virus was capable of infecting an Anopheles gambiae cell line MOS55. The amount of GFP protein produced in each cell line was quantified. Northern analysis of viral transcription revealed the presence of novel transcripts in Aa23T, C6/36, and MOS55 cell lines, but not in the BHK or MOS20. The initial characterization of these transcripts is described.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

Optimising fed-batch production of recombinant proteins using the baculovirus expression vector system

Fed-batch culture can offer significant improvement in recombinant protein production compared to batch culture in the baculovirus expression vector system (BEVS), as shown by Nguyen et al. (1993) and Bedard et al. (1994) among others. However, a thorough analysis of fed-batch culture to determine its limits in improving recombinant protein production over batch culture has yet to be performed. In this work, this issue is addressed by the optimisation of single-addition fed-batch culture. This type of fed-batch culture involves the manual addition of a multi-component nutrient feed to batch culture before infection with the baculovirus. The nutrient feed consists of yeastolate ultrafiltrate, lipids, amino acids, vitamins, trace elements, and glucose, which were added to batch cultures of Spodoptera frugiperda (Sf9) cells before infection with a recombinant Autographa californica nuclear polyhedrosis virus (Ac-NPV) expressing beta-galactosidase (beta-Gal). The fed-batch production of beta-Gal was optimised using response surface methods (RSM). The optimisation was performed in two stages, starting with a screening procedure to determine the most important variables and ending with a central-composite experiment to obtain a response surface model of volumetric beta-Gal production. The predicted optimum volumetric yield of beta-Gal in fed-batch culture was 2.4-fold that of the best yields in batch culture. This result was confirmed by a statistical analysis of the best fed-batch and batch data (with average beta-Gal yields of 1.2 and 0.5 g/L, respectively) obtained from this laboratory. The response surface model generated can be used to design a more economical fed-batch operation, in which nutrient feed volumes are minimised while maintaining acceptable improvements in beta-Gal yield. (C) 1998 John Wiley & Sons, Inc.

High-breakdown linear discriminant analysis

The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

Transfer of an autonomously replicating vector between vegetatively incompatible biotypes of Colletotrichum gloeosporioides

Previous research has indicated that biotypes A and B of Colletotrichum gloeosporioides that infect Stylosanthes spp. in Australia are asexual and vegetatively incompatible. Selectable marker genes conferring resistance either to hygromycin or phleomycin were introduced into isolates of these biotypes. Vectors conferring resistance to hygromycin and carrying telomeric sequences from Fusarium oxysporum replicated autonomously in C. gloeosporioides and gave frequencies of transformation 100-times higher than vectors that integrated into the genome. Monoconidial colonies resistant to both antibiotics were recovered when hygromycin-resistant biotype-A transformants carrying an autonomously replicating vector were paired in culture with a phleomycin-resistant biotype-B transformant carrying integrative vector sequences. Molecular analysis of double antibiotic-resistant progeny indicated that they contained the autonomous vector in a biotype-B genetic background, Results indicate that transfer of the autonomous vector had occurred from biotype A to biotype B, demonstrating the potential for transfer of genetic information between these biotypes.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Neonatal BCG Immunization Followed by DNAhsp65 Boosters: Highly Immunogenic but not Protective Against Tuberculosis - a Paradoxical Effect of the Vector?

A new tuberculosis vaccine is urgently needed. Prime-boost strategies are considered very promising and the inclusion of BCG is highly desirable. In this investigation, we tested the protective efficacy of BCG delivered in the neonatal period followed by boosters in the adult phase with a DNA vaccine containing the hsp65 gene from Mycobacterium leprae (pVAXhsp65). Immune responses were characterized by serum anti-hsp65 antibody levels and IFN-gamma and IL-5 production by the spleen. Amounts of these cytokines were also determined in lung homogenates. Protective efficacy was established by the number of colony-forming units (CFU) and histopathological analysis of the lungs after challenge with Mycobacterium tuberculosis. Immunization with BCG alone triggered a significant reduction of CFU in the lungs and also clearly preserved the pulmonary parenchyma. BCG priming also increased the immunogenicity of pVAXhsp65. However, boosters with pVAXhsp65 or the empty vector abolished the protective efficacy of BCG. Also, higher IL-5 levels were produced by spleen and lungs after DNA boosters. These results demonstrated that neonatal BCG immunization followed by DNAhsp65 boosters is highly immunogenic but is not protective against tuberculosis.

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Stream-bank shade and larval distribution of the Philippine malaria vector Anopheles flavirostris

The principal malaria vector in the Philippines, Anopheles flavirostris (Ludlow) (Diptera: Culicidae), is regarded as 'shade-loving' for its breeding sites, i.e. larval habitats. This long-standing belief, based on circumstantial observations rather than ecological analysis, has guided larval control methods such as 'stream-clearing' or the removal of riparian vegetation, to reduce the local abundance of An. flavirostris . We measured the distribution and abundance of An. flavirostris larvae in relation to canopy vegetation cover along a stream in Quezon Province, the Philippines. Estimates of canopy openness and light measurements were obtained by an approximation method that used simplified assumptions about the sun, and by hemispherical photographs analysed using the program hemiphot(C) . The location of larvae, shade and other landscape features was incorporated into a geographical information system (GIS) analysis. Early larval instars of An. flavirostris were found to be clustered and more often present in shadier sites, whereas abundance was higher in sunnier sites. For later instars, distribution was more evenly dispersed and only weakly related to shade. The best predictor of late-instar larvae was the density of early instars. Distribution and abundance of larvae were related over time (24 days). This pattern indicates favoured areas for oviposition and adult emergence, and may be predictable. Canopy measurements by the approximation method correlated better with larval abundance than hemispherical photography, being economical and practical for field use. Whereas shade or shade-related factors apparently have effects on larval distribution of An. flavirostris , they do not explain it completely. Until more is known about the bionomics of this vector and the efficacy and environmental effects of stream-clearing, we recommend caution in the use of this larval control method.

Dengue in the South-eastern region of Brazil: historical analysis and epidemiology

The aim of the study is an historical analysis of the work undertaken by the Public Health organizations dedicated to the combat of the Aedes aegypti, as well as an epidemiolocal study of persons with unexplained fever, with a view to evaluating the ocurrence of dengue within the population. The Mac-Elisa, Gac-Elisa, hemaglutination inhibition, isolation and typage tests were used. Organophosphate intoxication in agricultural workers was also assessed by measuring concentrations of serie cholinesterase. A sera samples of 2,094 were collected in 23 towns, and the type 1 dengue virus was detected in 17 towns and autochthony was confirmed in 12 of them. The cholinesterase was measured in 2,391 sera samples of which 53 cases had abnormal levels. Poisoning was confirmed in 3 cases. Results reveal an epidemic the gravity of which was not officially know. The relationshipe between levels of IgM and IgG antibodies indicates the outbreak tendency. The widespread distribution of the vector is troubling because of the possibility of the urbanization of wild yellow fever, whereas the absence of A. aegypti in 2 towns with autochthony suggests the existence of another vector. Since there is no vaccine against dengue, the combat of the vector is the most efficient measure for preventing outbreaks. The eradication of the vector depends on government decisions which depend, for their execution, on the organization of the Health System and the propagation of information concerning the prevention of the disease using all possible means because short and long term results depend on the education and the active participation of the entire population.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Evaluation of dynamic pass-through of carbon prices into electricity prices – a cointegrated VECM analysis

This paper addresses the impact of the CO2 opportunity cost on the wholesale electricity price in the context of the Iberian electricity market (MIBEL), namely on the Portuguese system, for the period corresponding to the Phase II of the European Union Emission Trading Scheme (EU ETS). In the econometric analysis a vector error correction model (VECM) is specified to estimate both long–run equilibrium relations and short–run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The model is estimated using daily spot market prices and the four commodities prices are jointly modelled as endogenous variables. Moreover, a set of exogenous variables is incorporated in order to account for the electricity demand conditions (temperature) and the electricity generation mix (quantity of electricity traded according the technology used). The outcomes for the Portuguese electricity system suggest that the dynamic pass–through of carbon prices into electricity prices is strongly significant and a long–run elasticity was estimated (equilibrium relation) that is aligned with studies that have been conducted for other markets.