Complete assignments of (1)H and (13)C NMR spectral data for 7,7 `-dihydroarylnaphthalene lignan lactones

In this article we present a complete (1)H and (13)C NMR spectral analysis of three 7,7`-dihydroarylnaphthalene lignan lactones using modern NMR techniques such as COSY, HSQC, HMBC and NOE experiments. Complete assignment and homonuclear hydrogen coupling constant measurements were performed. Copyright (C) 2009 John Wiley & Sons, Ltd.

Geospatial clustering in data-rich environments: Features and issues

Geospatial clustering must be designed in such a way that it takes into account the special features of geoinformation and the peculiar nature of geographical environments in order to successfully derive geospatially interesting global concentrations and localized excesses. This paper examines families of geospaital clustering recently proposed in the data mining community and identifies several features and issues especially important to geospatial clustering in data-rich environments.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Molecular evidence of horizontal transmission of hepatitis C virus within couples

Hepatitis C virus (HCV) transmission has decreased with the adoption of universal blood donor screening and social policies to reduce the risk of infection in intravenous drug users, but remains a worldwide health problem. The objective of this study was to evaluate the phylogenetic relationships among sequences from different HCV genomic regions from sexual partners of infected patients. Nine couples with a stable relationship and without other risk factors for HCV infection and 42 control patients were selected, and the NS3 and NS5B regions were analysed. Phylogenetic analysis showed that viruses from five of the couples had a common origin, clustering in the same monophyletic group, with bootstrap values greater than 70. For the other couples, monophyletic groups were observed, but without bootstrap support. Thus, using two different viral genome regions, a common source of infection was observed in both members of five couples. These data strongly support HCV transmission within couples.

Genotypic distribution of hepatitis C among hepatitis C and HIV co-infected patients in Brazil

Information on hepatitis C virus (HCV) genotypic distribution among HIV-HCV co-infected patients is lacking in Brazil as well as other Latin American countries. The objective of this study was to evaluate the level of exposure to different risk factors associated with HCV transmission among a group of co-infected patients and to characterize the genotypic distribution of HCV in this cluster. A series of 100 HIV-HCV co-infected patients was analysed. The data to be analysed were collected from specific laboratory tests. Information was collected through a questionnaire. HCV genotyping was carried out by sequencing the 5 ` non-coding region of HCV. Chi-square and Fischer association tests or Kruskal-Wallis test were used to study the association between HCV transmission-related variables and the established genotypes. In conclusion, exposure to multiple risk factors associated with HCV transmission was common among HIV co-infected patients and an association between HCV genotype 3 and intravenous drug user was observed.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Demographic profile of blood donors at three major Brazilian blood centers: results from the International REDS-II study, 2007 to 2008

BACKGROUND: The profile of blood donors changed dramatically in Brazil over the past 20 years, from remunerated to nonremunerated and then from replacement to community donors. Donor demographic data from three major blood centers establish current donation profiles in Brazil, serving as baseline for future analyses and tracking longitudinal changes in donor characteristics. STUDY DESIGN AND METHODS: Data were extracted from the blood center, compiled in a data warehouse, and analyzed. Population data were obtained from the Brazilian census. RESULTS: During 2007 to 2008, there were 615,379 blood donations from 410,423 donors. A total of 426,142 (69.2%) were from repeat (Rpt) donors and 189,237 (30.8%) were from first-time (FT) donors. Twenty percent of FT donors returned to donate in the period. FT donors were more likely to be younger, and Rpt donors were more likely to be community donors. All were predominantly male. Replacement donors still represent 50% of FT and 30% of Rpt donors. The mean percentage of the potentially general population who were donors was approximately 1.2% for the three centers (0.7, 1.5, and 3.1%). Adjusting for the catchment`s area, the first two were 2.1 and 1.6%. CONCLUSIONS: Donors in the three Brazilian centers tended to be younger with a higher proportion of males than in the general population. Donation rates were lower than desirable. There were substantial differences in sex, age, and community/replacement status by center. Studies on the safety, donation frequencies, and motivations of donors are in progress to orient efforts to enhance the availability of blood.

Expression of genes related to apoptosis, cell cycle and signaling pathways are independent of TP53 status in urinary bladder cancer cells

Urinary bladder cancer is the fourth most common malignancy in the Western world. Transitional cell carcinoma (TCC) is the most common subtype, accounting for about 90% of all bladder cancers. The TP53 gene plays an essential role in the regulation of the cell cycle and apoptosis and therefore contributes to cellular transformation and malignancy; however, little is known about the differential gene expression patterns in human tumors that present with the wild-type or mutated TP53 gene. Therefore, because gene profiling can provide new insights into the molecular biology of bladder cancer, the present study aimed to compare the molecular profiles of bladder cancer cell lines with different TP53 alleles, including the wild type (RT4) and two mutants (5637, with mutations in codons 280 and 72; and T24, a TP53 allele encoding an in-frame deletion of tyrosine 126). Unsupervised hierarchical clustering and gene networks were constructed based on data generated by cDNA microarrays using mRNA from the three cell lines. Differentially expressed genes related to the cell cycle, cell division, cell death, and cell proliferation were observed in the three cell lines. However, the cDNA microarray data did not cluster cell lines based on their TP53 allele. The gene profiles of the RT4 cells were more similar to those of T24 than to those of the 5637 cells. While the deregulation of both the cell cycle and the apoptotic pathways was particularly related to TCC, these alterations were not associated with the TP53 status.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Spatial distribution of benthic microalgae on coral reefs determined by remote sensing

Understanding the ecological role of benthic microalgae, a highly productive component of coral reef ecosystems, requires information on their spatial distribution. The spatial extent of benthic microalgae on Heron Reef (southern Great Barrier Reef, Australia) was mapped using data from the Landsat 5 Thematic Mapper sensor. integrated with field measurements of sediment chlorophyll concentration and reflectance. Field-measured sediment chlorophyll concentrations. 2 ranging from 23-1.153 mg chl a m(2), were classified into low, medium, and high concentration classes (1-170, 171-290, and > 291 mg chl a m(-2)) using a K-means clustering algorithm. The mapping process assumed that areas in the Thematic Mapper image exhibiting similar reflectance levels in red and blue bands would correspond to areas of similar chlorophyll a levels. Regions of homogenous reflectance values corresponding to low, medium, and high chlorophyll levels were identified over the reef sediment zone by applying a standard image classification algorithm to the Thematic Mapper image. The resulting distribution map revealed large-scale ( > 1 km 2) patterns in chlorophyll a levels throughout the sediment zone of Heron Reef. Reef-wide estimates of chlorophyll a distribution indicate that benthic Microalgae may constitute up to 20% of the total benthic chlorophyll a at Heron Reef. and thus contribute significantly to total primary productivity on the reef.

Characterization of redox centers in dimethyl sulfide dehydrogenase from Rhodovulum sulfidophilum

Dimethyl sulfide dehydrogenase from the purple phototrophic bacterium Rhodovulum sulfidophilum catalyzes the oxidation of dimethyl sulfide to dimethyl sulfoxide. Recent DNA sequence analysis of the ddh operon, encoding dimethyl sulfide dehydrogenase (ddhABC), and biochemical analysis (1) have revealed that it is a member of the DMSO reductase family of molybdenum enzymes and is closely related to respiratory nitrate reductase (NarGHI). Variable temperature X-band EPR spectra (120122 K) of purified heterotrimeric dimethyl sulfide dehydrogenase showed resonances arising from multiple redox centers, Mo(V), [3Fe-4S](+), [4Fe-4S](+), and a b-type heme. A pH-dependent EPR study of the Mo(V) center in (H2O)-H-1 and (H2O)-H-2 revealed the presence of three Mo(V) species in equilibrium, Mo(V)-OH2, Mo(v)-anion, and Mo(V)-OH. Above pH 8.2 the dominant species was Mo(V)-OH. The maximum specific activity occurred at pH 9.27. Comparison of the rhombicity and anisotropy parameters for the Mo(V) species in DMS dehydrogenase with other molybdenum enzymes of the DMSO reductase family showed that it was most similar to the low-pH nitrite spectrum of Escherichia coli nitrate reductase (NarGHI), consistent with previous sequence analysis of DdhA and NarG. A sequence comparison of DdhB and NarH has predicted the presence of four [Fe-S] clusters in DdhB. A [3Fe-4S](+) cluster was identified in dimethyl sulfide dehydrogenase whose properties resembled those of center 2 of NarH. A [4Fe-4S](+) cluster was also identified with unusual spin Hamiltonian parameters, suggesting that one of the iron atoms may have a fifth non-sulfur ligand. The g matrix for this cluster is very similar to that found for the minor conformation of center 1 in NarH [Guigliarelli, B., Asso, M., More, C., Augher, V., Blasco, F., Pommier, J., Giodano, G., and Bertrand, P. (1992) Eur. J. Biochem. 307,63-68]. Analysis of a ddhC mutant showed that this gene encodes the b-type cytochrome in dimethyl sulfide dehydrogenase. Magnetic circular dichroism studies revealed that the axial ligands to the iron in this cytochrome are a histidine and methionine, consistent with predictions from protein sequence analysis. Redox potentiometry showed that the b-type cytochrome has a high midpoint redox potential (E-o = +315 mV, pH 8).

Analysis of genetic diversity within Australian lucerne cultivars and implications for future genetic improvement

Lucerne (Medicago sativa L.) is autotetraploid, and predominantly allogamous. This complex breeding structure maximises the genetic diversity within lucerne populations making it difficult to genetically discriminate between populations. The objective of this study was to evaluate the level of random genetic diversity within and between a selection of Australian-grown lucerne cultivars, with tetraploid M. falcata included as a possible divergent control source. This diversity was evaluated using random amplified polymorphic DNA (RAPDs). Nineteen plants from each of 10 cultivars were analysed. Using 11 RAPD primers, 96 polymorphic bands were scored as present or absent across the 190 individuals. Genetic similarity estimates (GSEs) of all pair-wise comparisons were calculated from these data. Mean GSEs within cultivars ranged from 0.43 to 0.51. Cultivar Venus (0.43) had the highest level of intra-population genetic diversity and cultivar Sequel HR (0.51) had the lowest level of intra-population genetic diversity. Mean GSEs between cultivars ranged from 0.31 to 0.49, which overlapped with values obtained for within-cultivar GSE, thus not allowing separation of the cultivars. The high level of intra- and inter-population diversity that was detected is most likely due to the breeding of synthetic cultivars using parents derived from a number of diverse sources. Cultivar-specific polymorphisms were only identified in the M. falcata source, which like M. sativa, is outcrossing and autotetraploid. From a cluster analysis and a principal components analysis, it was clear that M. falcata was distinct from the other cultivars. The results indicate that the M. falcata accession tested has not been widely used in Australian lucerne breeding programs, and offers a means of introducing new genetic diversity into the lucerne gene pool. This provides a means of maximising heterozygosity, which is essential to maximising productivity in lucerne.

Modelling High-Dimensional Data by Mixtures of Factor Analyzers

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.