Transgenic tobacco revealing altered bacterial diversity in the rhizosphere during early plant development

The rhizosphere constitutes a complex niche that may be exploited by a wide variety of bacteria. Bacterium-plant interactions in this niche can be influenced by factors such as the expression of heterologous genes in the plant. The objective of this work was to describe the bacterial communities associated with the rhizosphere and rhizoplane regions of tobacco plants, and to compare communities from transgenic tobacco lines (CAB1, CAB2 and TRP) with those found in wild-type (WT) plants. Samples were collected at two stages of plant development, the vegetative and flowering stages (1 and 3 months after germination). The diversity of the culturable microbial community was assessed by isolation and further characterization of isolates by amplified ribosomal RNA gene restriction analysis (ARDRA) and 16S rRNA sequencing. These analyses revealed the presence of fairly common rhizosphere organisms with the main groups Alphaproteobacteria, Betaproteobacteria, Actinobacteria and Bacilli. Analysis of the total bacterial communities using PCR-DGGE (denaturing gradient gel electrophoresis) revealed that shifts in bacterial communities occurred during early plant development, but the reestablishment of original community structure was observed over time. The effects were smaller in rhizosphere than in rhizoplane samples, where selection of specific bacterial groups by the different plant lines was demonstrated. Clustering patterns and principal components analysis (PCA) were used to distinguish the plant lines according to the fingerprint of their associated bacterial communities. Bands differentially detected in plant lines were found to be affiliated with the genera Pantoea, Bacillus and Burkholderia in WT, CAB and TRP plants, respectively. The data revealed that, although rhizosphere/rhizoplane microbial communities can be affected by the cultivation of transgenic plants, soil resilience may be able to restore the original bacterial diversity after one cycle of plant cultivation.

The bacterial diversity in a Brazilian non-disturbed mangrove sediment

The bacterial diversity present in sediments of a well-preserved mangrove in Ilha do Cardoso, located in the extreme south of So Paulo State coastline, Brazil, was assessed using culture-independent molecular approaches (denaturing gradient gel electrophoresis (DGGE) and analysis of 166 sequences from a clone library). The data revealed a bacterial community dominated by Alphaproteobacteria (40.36% of clones), Gammaproteobacteria (19.28% of clones) and Acidobacteria (27.71% of clones), while minor components of the assemblage were affiliated to Betaproteobacteria, Deltaproteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. The clustering and redundancy analysis (RDA) based on DGGE were used to determine factors that modulate the diversity of bacterial communities in mangroves, such as depth, seasonal fluctuations, and locations over a transect area from the sea to the land. Profiles of specific DGGE gels showed that both dominant (`universal` Bacteria and Alphaproteobacteria) and low-density bacterial communities (Betaproteobacteria and Actinobacteria) are responsive to shifts in environmental factors. The location within the mangrove was determinant for all fractions of the community studied, whereas season was significant for Bacteria, Alphaproteobacteria, and Betaproteobacteria and sample depth determined the diversity of Alphaproteobacteria and Actinobacteria.

Air Entrainment Processes in a Full-Scale Rectangular Dropshaft at Large Flows

Rectangular dropshafts, commonly used in sewers and storm water systems, are characterised by significant flow aeration. New detailed air-water flow measurements were conducted in a near-full-scale dropshaft at large discharges. In the shaft pool and outflow channel, the results demonstrated the complexity of different competitive air entrainment mechanisms. Bubble size measurements showed a broad range of entrained bubble sizes. Analysis of streamwise distributions of bubbles suggested further some clustering process in the bubbly flow although, in the outflow channel, bubble chords were in average smaller than in the shaft pool. A robust hydrophone was tested to measure bubble acoustic spectra and to assess its field application potential. The acoustic results characterised accurately the order of magnitude of entrained bubble sizes, but the transformation from acoustic frequencies to bubble radii did not predict correctly the probability distribution functions of bubble sizes.

Bubbly Flow Structure in Hydraulic Jump

In an open channel, a hydraulic jump is the rapid transition from super- to sub-critical flow associated with strong turbulence and air bubble entrainment in the mixing layer. New experiments were performed at relatively large Reynolds numbers using phase-detection probes. Some new signal analysis provided characteristic air-water time and length scales of the vortical structures advecting the air bubbles in the developing shear flow. An analysis of the longitudinal air-water flow structure suggested little bubble clustering in the mixing layer, although an interparticle arrival time analysis showed some preferential bubble clustering for small bubbles with chord times below 3 ms. Correlation analyses yielded longitudinal air-water time scales Txx*V1/d1 of about 0.8 in average. The transverse integral length scale Z/d1 of the eddies advecting entrained bubbles was typically between 0.25 and 0.4, irrespective of the inflow conditions within the range of the investigations. Overall the findings highlighted the complicated nature of the air-water flow

Equational Reasoning as a Tool for Data Analysis

A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

Multiple Sclerosis with Idiopathic Dilated Cardiomyopathy: A Case Report

Multiple sclerosis and idiopathic dilated cardiomyopathy are two conditions in which an autoimmune process is implicated in the pathogenesis. There is evidence to support clustering of autoimmune diseases in patients with multiple sclerosis and their families. To our knowledge, this is the first report of idiopathic dilated cardiomyopathy occurring in a patient with multiple sclerosis.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Sequence analysis of rabbit haemorrhagic disease virus (RHDV) in Australia: alterations after its release

Liver samples from rabbits killed by RHDV, collected from five States in Australia in 1996 and 1997 were analysed by RT-PCR. A 398 bp fragment of the capsid protein (VP60) gene was amplified by PCR and directly sequenced. The alignment of the nucleotide and amino acid sequences and their comparison with the original strain of the virus released in Australia indicated genetic changes after two years have been small with 98.2% to 100% identity. The constructed phylogenetic tree suggests slight differences in nucleotide substitutions in various States but there is no clear evidence of clustering of sequences according to their geographic origin. In practical terms, sequencing of viral RNA provides a means of testing the efficacy of further releases and subsequent spread of the virus if such a strategy is employed as a means of enhancing RHD as a biological control of the wild rabbit in Australia.

Molecular characterization of the toxic cyanobacterium Cylindrospermopsis raciborskii and design of a species-specific PCR

Cylindrospermopsis raciborskii is a toxic-bloom-forming cyanobacterium that is commonly found in tropical to subtropical climatic regions worldwide, but it is also recognized as a common component of cyanobacterial communities in temperate climates. Genetic profiles of C. raciborskii were examined in 19 cultured isolates originating from geographically diverse regions of Australia and represented by two distinct morphotypes. A 609-bp region of rpoC1, a DNA-dependent RNA polymerase gene, was amplified by PCR from these isolates with cyanobacterium-specific primers. Sequence analysis revealed that all isolates belonged to the same species, including morphotypes with straight or coiled trichomes. Additional rpoC1 gene sequences obtained for a range of cyanobacteria highlighted clustering of C. raciborskii with other heterocyst-producing cyanobacteria (orders Nostocales and Stigonematales). In contrast, randomly amplified polymorphic DNA and short tandemly repeated repetitive sequence profiles revealed a greater level of genetic heterogeneity among C. raciborskii isolates than did rpoC1 gene analysis, and unique band profiles were also found among each of the cyanobacterial genera examined. A PCR test targeting a region of the rpoC1 gene unique to C. raciborskii was developed for the specific identification of C. raciborskii from both purified genomic DNA and environmental samples. The PCR was evaluated with a number of cyanobacterial isolates, but a PCR-positive result was only achieved with C, raciborskii. This method provides an accurate alternative to traditional morphological identification of C. raciborskii.

Robust Mixture Modelling Using the t Distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.

Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data

Examples from the Murray-Darling basin in Australia are used to illustrate different methods of disaggregation of reconnaissance-scale maps. One approach for disaggregation revolves around the de-convolution of the soil-landscape paradigm elaborated during a soil survey. The descriptions of soil ma units and block diagrams in a soil survey report detail soil-landscape relationships or soil toposequences that can be used to disaggregate map units into component landscape elements. Toposequences can be visualised on a computer by combining soil maps with digital elevation data. Expert knowledge or statistics can be used to implement the disaggregation. Use of a restructuring element and k-means clustering are illustrated. Another approach to disaggregation uses training areas to develop rules to extrapolate detailed mapping into other, larger areas where detailed mapping is unavailable. A two-level decision tree example is presented. At one level, the decision tree method is used to capture mapping rules from the training area; at another level, it is used to define the domain over which those rules can be extrapolated. (C) 2001 Elsevier Science B.V. All rights reserved.

The large-scale distribution of neutral hydrogen in the Fornax region

Using data from the H I Parkes All Sky Survey (HIPASS), we have searched for neutral hydrogen in galaxies in a region similar to25x25 deg(2) centred on NGC 1399, the nominal centre of the Fornax cluster. Within a velocity search range of 300-3700 km s(-1) and to a 3sigma lower flux limit of similar to40 mJy, 110 galaxies with H I emission were detected, one of which is previously uncatalogued. None of the detections has early-type morphology. Previously unknown velocities for 14 galaxies have been determined, with a further four velocity measurements being significantly dissimilar to published values. Identification of an optical counterpart is relatively unambiguous for more than similar to90 per cent of our H I galaxies. The galaxies appear to be embedded in a sheet at the cluster velocity which extends for more than 30degrees across the search area. At the nominal cluster distance of similar to20 Mpc, this corresponds to an elongated structure more than 10 Mpc in extent. A velocity gradient across the structure is detected, with radial velocities increasing by similar to500 km s(-1) from south-east to north-west. The clustering of galaxies evident in optical surveys is only weakly suggested in the spatial distribution of our H I detections. Of 62 H I detections within a 10degrees projected radius of the cluster centre, only two are within the core region (projected radius

Price dispersion and price indexes

The traditional theory of price index numbers is based on the law of one price. But in the real world, we frequently observe the existence of an equilibrium price dispersion instead of one price of equilibrium. This article discusses the effects of price dispersion on two price indexes: the cost of living index and the consumer price index. With price dispersion and consumer searching for the lowest price, these indexes cannot be interpreted as deterministic indicators, but as stochastic indicators, and they can be biased if price dispersion is not taken into account. A measure for the bias of the consumer price index is proposed and the article ends with an estimation of the bias based on data obtained from the consumer price index calculated for the city of Sao Paulo, Brazil, from January 1988 through December 2004. The period analysed is very interesting, because it exhibits different inflationary environments: high levels and high volatility of the rates of inflation with great price dispersion until July 1994 and low and relatively stable rates of inflation with prices less dispersed after August 1994.