Diversity of Somatic Coliphages in Coastal Regions with Different Levels of Anthropogenic Activity in Sao Paulo State, Brazil

Bacteriophages are the most abundant and genetically diverse viruses on Earth, with complex ecology in both quantitative and qualitative terms. Somatic coliphages (SC) have been reported to be good indicators of fecal pollution in seawater. This study focused on determining the concentration of SC and their diversity by electron microscopy of seawater, plankton, and bivalve samples collected at three coastal regions in Sao Paulo, Brazil. The SC counts varied from < 1 to 3.4 x 103 PFU/100 ml in seawater (73 samples tested), from < 1 to 4.7 x 10(2) PFU/g in plankton (46 samples tested), and from < 1 to 2.2 x 10(1) PFU/g in bivalves (11 samples tested). In seawater samples, a relationship between the thermotolerant coliforms and Escherichia coli and SC was observed at the three regions (P = 0.0001) according to the anthropogenic activities present at each region. However, SC were found in plankton samples from three regions: Baixada Santista (17/20), Canal de Sao Sebastiao (6/14), and Ubatuba (3/12). In seawater samples collected from Baixada Santista, four morphotypes were observed: A1 (4.5%), B1 (50%), C1 (36.4%), and D1 (9.1%). One coliphage, Siphoviridae type T1, had the longest tail: between 939 and 995 nm. In plankton samples, Siphoviridae (65.8%), Podoviridae (15.8%), Microviridae (15.8%), and Myoviridae (2.6%) were found. In bivalves, only the morphotype B1 was observed. These SC were associated with enteric hosts: enterobacteria, E. coli, Proteus, Salmonella, and Yersinia. Baixada Santista is an area containing a high level of fecal pollution compared to those in the Canal de Sao Sebastiao and Ubatuba. This is the first report of coliphage diversity in seawater, plankton, and bivalve samples collected from Sao Paulo coastal regions. A better characterization of SC diversity in coastal environments will help with the management and evaluation of the microbiological risks for recreation, seafood cultivation, and consumption.

Adapting Web content for low-literacy readers by using lexical elaboration and named entities labeling

This paper presents an approach for assisting low-literacy readers in accessing Web online information. The oEducational FACILITAo tool is a Web content adaptation tool that provides innovative features and follows more intuitive interaction models regarding accessibility concerns. Especially, we propose an interaction model and a Web application that explore the natural language processing tasks of lexical elaboration and named entity labeling for improving Web accessibility. We report on the results obtained from a pilot study on usability analysis carried out with low-literacy users. The preliminary results show that oEducational FACILITAo improves the comprehension of text elements, although the assistance mechanisms might also confuse users when word sense ambiguity is introduced, by gathering, for a complex word, a list of synonyms with multiple meanings. This fact evokes a future solution in which the correct sense for a complex word in a sentence is identified, solving this pervasive characteristic of natural languages. The pilot study also identified that experienced computer users find the tool to be more useful than novice computer users do.

GRASSIUS: A Platform for Comparative Regulatory Genomics across the Grasses

Transcription factors (TFs) are major players in gene regulatory networks and interactions between TFs and their target genes furnish spatiotemporal patterns of gene expression. Establishing the architecture of regulatory networks requires gathering information on TFs, their targets in the genome, and the corresponding binding sites. We have developed GRASSIUS (Grass Regulatory Information Services) as a knowledge-based Web resource that integrates information on TFs and gene promoters across the grasses. In its initial implementation, GRASSIUS consists of two separate, yet linked, databases. GrassTFDB holds information on TFs from maize (Zea mays), sorghum (Sorghum bicolor), sugarcane (Saccharum spp.), and rice (Oryza sativa). TFs are classified into families and phylogenetic relationships begin to uncover orthologous relationships among the participating species. This database also provides a centralized clearinghouse for TF synonyms in the grasses. GrassTFDB is linked to the grass TFome collection, which provides clones in recombination-based vectors corresponding to full-length open reading frames for a growing number of grass TFs. GrassPROMDB contains promoter and cis-regulatory element information for those grass species and genes for which enough data are available. The integration of GrassTFDB and GrassPROMDB will be accomplished through GrassRegNet as a first step in representing the architecture of grass regulatory networks. GRASSIUS can be accessed from www.grassius.org.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.