Eutrophication and macroalgal blooms in temperate and tropical coastal waters: nutrient enrichment experiments with Ulva spp.

Receiving coastal waters and estuaries are among the most nutrient-enriched environments on earth, and one of the symptoms of the resulting eutrophication is the proliferation of opportunistic, fast-growing marine seaweeds. Here, we used a widespread macroalga often involved in blooms, Ulva spp., to investigate how supply of nitrogen (N) and phosphorus (P), the two main potential growth-limiting nutrients, influence macroalgal growth in temperate and tropical coastal waters ranging from low- to high-nutrient supplies. We carried out N and P enrichment field experiments on Ulva spp. in seven coastal systems, with one of these systems represented by three different subestuaries, for a total of nine sites. We showed that rate of growth of Ulva spp. was directly correlated to annual dissolved inorganic nitrogen (DIN) concentrations, where growth increased with increasing DIN concentration. Internal N pools of macroalgal fronds were also linked to increased DIN supply, and algal growth rates were tightly coupled to these internal N pools. The increases in DIN appeared to be related to greater inputs of wastewater to these coastal waters as indicated by high delta 15N signatures of the algae as DIN increased. N and P enrichment experiments showed that rate of macroalgal growth was controlled by supply of DIN where ambient DIN concentrations were low, and by P where DIN concentrations were higher, regardless of latitude or geographic setting. These results suggest that understanding the basis for macroalgal blooms, and management of these harmful phenomena, will require information as to nutrient sources, and actions to reduce supply of N and P in coastal waters concerned.

Semantic information extraction from images of complex documents

Even though the digital processing of documents is increasingly widespread in industry, printed documents are still largely in use. In order to process electronically the contents of printed documents, information must be extracted from digital images of documents. When dealing with complex documents, in which the contents of different regions and fields can be highly heterogeneous with respect to layout, printing quality and the utilization of fonts and typing standards, the reconstruction of the contents of documents from digital images can be a difficult problem. In the present article we present an efficient solution for this problem, in which the semantic contents of fields in a complex document are extracted from a digital image.

A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation

The Neotropical evaniid genus Evaniscus Szepligeti currently includes six species. Two new species are described, Evaniscus lansdownei Mullins, sp. n. from Colombia and Brazil and E. rafaeli Kawada, sp. n. from Brazil. Evaniscus sulcigenis Roman, syn. n., is synonymized under E. rufithorax Enderlein. An identification key to species of Evaniscus is provided. Thirty-five parsimony informative morphological characters are analyzed for six ingroup and four outgroup taxa. A topology resulting in a monophyletic Evaniscus is presented with E. tibialis and E. rafaeli as sister to the remaining Evaniscus species. The Hymenoptera Anatomy Ontology and other relevant biomedical ontologies are employed to create semantic phenotype statements in Entity-Quality (EQ) format for species descriptions. This approach is an early effort to formalize species descriptions and to make descriptive data available to other domains.

Semantic Dementia Versus Nonfluent Progressive Aphasia Neuropsychological Characterization and Differentiation

Background: Early progressive nonfluent aphasia (PNFA) may be difficult to differentiate from semantic dementia (SD) in a nonspecialist setting. There are descriptions of the clinical and neuropsychological profiles of patients with PNFA and SD but few systematic comparisons. Method: We compared the performance of groups with SD (n = 27) and PNFA (n = 16) with comparable ages, education, disease duration, and severity of dementia as measured by the Clinical Dementia Rating Scale on a comprehensive neuropsychological battery. Principal components analysis and intergroup comparisons were used. Results: A 5-factor solution accounted for 78.4% of the total variance with good separation of neuropsychological variables. As expected, both groups were anomic with preserved visuospatial function and mental speed. Patients with SD had lower scores on comprehension-based semantic tests and better performance on verbal working memory and phonological processing tasks. The opposite pattern was found in the PNFA group. Conclusions: Neuropsychological tests that examine verbal and nonverbal semantic associations, verbal working memory, and phonological processing are the most helpful for distinguishing between PNFA and SD.

Environmental enrichment blocks ethanol-induced locomotor sensitization and decreases BDNF levels in the prefrontal cortex in mice

The use of addictive drugs can lead to long-term neuroplastic changes in the brain, including behavioral sensitization, a phenomenon related to addiction. Environmental enrichment (EE) is a strategy used to study the effect of environment on the response to several manipulations, including treatment with addictive drugs. Brain-derived neurotrophic factor (BDNF) has been associated with behaviors related to ethanol addiction. The aim of the present study was to evaluate the effects of EE on ethanol-induced behavioral sensitization and BDNF expression. Mice were exposed to EE and then repeatedly treated with a low dose (1.8 g/kg) of ethanol. Another group of mice was first subjected to repeated ethanol treatment according to the behavioral sensitization protocol and then exposed to EE. Environmental enrichment prevented the development of ethanol-induced behavioral sensitization and blocked behavioral sensitization in sensitized mice. Both repeated ethanol and EE decreased BDNF levels in the prefrontal cortex but not in the hippocampus. However, BDNF levels were lower in ethanol-treated mice exposed to EE. These findings suggest that EE can act on the mechanisms implicated in behavioral sensitization, a model for drug-induced neuroplasticity and relapse. Additionally, EE alters BDNF levels, which regulate addiction-related behaviors.

Semantic Equivalence of the Brazilian Portuguese version of the "Body Change Inventory"

With the increase in research on the components of Body Image, validated instruments are needed to evaluate its dimensions. The Body Change Inventory (BCI) assesses strategies used to alter body size among adolescents. The scope of this study was to describe the translation and evaluation for semantic equivalence of the BCI in the Portuguese language. The process involved the steps of (1) translation of the questionnaire to the Portuguese language; (2) back-translation to English; (3) evaluation of semantic equivalence; and (4) assessment of comprehension by professional experts and the target population. The six subscales of the instrument were translated into the Portuguese language. Language adaptations were made to render the instrument suitable for the Brazilian reality. The questions were interpreted as easily understandable by both experts and young people. The Body Change Inventory has been translated and adapted into Portuguese. Evaluation of the operational, measurement and functional equivalence are still needed.

A generalized finite element method with global-local enrichment functions for confined plasticity problems

The main feature of partition of unity methods such as the generalized or extended finite element method is their ability of utilizing a priori knowledge about the solution of a problem in the form of enrichment functions. However, analytical derivation of enrichment functions with good approximation properties is mostly limited to two-dimensional linear problems. This paper presents a procedure to numerically generate proper enrichment functions for three-dimensional problems with confined plasticity where plastic evolution is gradual. This procedure involves the solution of boundary value problems around local regions exhibiting nonlinear behavior and the enrichment of the global solution space with the local solutions through the partition of unity method framework. This approach can produce accurate nonlinear solutions with a reduced computational cost compared to standard finite element methods since computationally intensive nonlinear iterations can be performed on coarse global meshes after the creation of enrichment functions properly describing localized nonlinear behavior. Several three-dimensional nonlinear problems based on the rate-independent J (2) plasticity theory with isotropic hardening are solved using the proposed procedure to demonstrate its robustness, accuracy and computational efficiency.

Enrichment of Pleurotus ostreatus mushrooms with selenium in coffee husks

Pleurotus ostreatus fungus forms an edible mushroom that possesses important nutritional and medicinal properties. Selenium (Se) is essential to human diets and it is in low concentration in the soil, and consequently in food. P. ostreatus was grown in coffee husks enriched with various concentrations of sodium selenite. The biological efficiency of P. ostreatus was affected by the addition of high concentrations of Se. The highest level of Se absorption was obtained by adding 51 mg kg(1) of sodium selenite. The mushrooms from first flush contained more Se than the further flushes. These results demonstrate the great potential of coffee husks in the production of Se-enriched mushrooms and show the ability of this fungus to absorb and biomagnify Se. (C) 2011 Elsevier Ltd. All rights reserved.

A new enrichment space for the treatment of discontinuous pressures in multi-fluid flows

In this work, a new enrichment space to accommodate jumps in the pressure field at immersed interfaces in finite element formulations, is proposed. The new enrichment adds two degrees of freedom per element that can be eliminated by means of static condensation. The new space is tested and compared with the classical P1 space and to the space proposed by Ausas et al (Comp. Meth. Appl. Mech. Eng., Vol. 199, 10191031, 2010) in several problems involving jumps in the viscosity and/or the presence of singular forces at interfaces not conforming with the element edges. The combination of this enrichment space with another enrichment that accommodates discontinuities in the pressure gradient has also been explored, exhibiting excellent results in problems involving jumps in the density or the volume forces. Copyright (c) 2011 John Wiley & Sons, Ltd.

BayGO: Bayesian analysis of ontology term enrichment in microarray data

Abstract Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

Genome mapping and expression analyses of human intronic noncoding RNAs reveal tissue-specific patterns and enrichment in genes related to regulation of transcription

Abstract Background RNAs transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression. However, the complement of human genes in which introns are transcribed, and the number of intronic transcriptional units and their tissue expression patterns are not known. Results A survey of mRNA and EST public databases revealed more than 55,000 totally intronic noncoding (TIN) RNAs transcribed from the introns of 74% of all unique RefSeq genes. Guided by this information, we designed an oligoarray platform containing sense and antisense probes for each of 7,135 randomly selected TIN transcripts plus the corresponding protein-coding genes. We identified exonic and intronic tissue-specific expression signatures for human liver, prostate and kidney. The most highly expressed antisense TIN RNAs were transcribed from introns of protein-coding genes significantly enriched (p = 0.002 to 0.022) in the 'Regulation of transcription' Gene Ontology category. RNA polymerase II inhibition resulted in increased expression of a fraction of intronic RNAs in cell cultures, suggesting that other RNA polymerases may be involved in their biosynthesis. Members of a subset of intronic and protein-coding signatures transcribed from the same genomic loci have correlated expression patterns, suggesting that intronic RNAs regulate the abundance or the pattern of exon usage in protein-coding messages. Conclusion We have identified diverse intronic RNA expression patterns, pointing to distinct regulatory roles. This gene-oriented approach, using a combined intron-exon oligoarray, should permit further comparative analysis of intronic transcription under various physiological and pathological conditions, thus advancing current knowledge about the biological functions of these noncoding RNAs.

Lexical-semantic processing in the semantic priming paradigm in aphasic patients

There is evidence that the explicit lexical-semantic processing deficits which characterize aphasia may be observed in the absence of implicit semantic impairment. The aim of this article was to critically review the international literature on lexical-semantic processing in aphasia, as tested through the semantic priming paradigm. Specifically, this review focused on aphasia and lexical-semantic processing, the methodological strengths and weaknesses of the semantic paradigms used, and recent evidence from neuroimaging studies on lexical-semantic processing. Furthermore, evidence on dissociations between implicit and explicit lexical-semantic processing reported in the literature will be discussed and interpreted by referring to functional neuroimaging evidence from healthy populations. There is evidence that semantic priming effects can be found both in fluent and in non-fluent aphasias, and that these effects are related to an extensive network which includes the temporal lobe, the pre-frontal cortex, the left frontal gyrus, the left temporal gyrus and the cingulated cortex.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.