LAITOR - Literature Assistant for Identification of Terms co-Occurrences and Relationships

<p>Abstract</p> <p>Background</p> <p>Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.</p> <p>Results</p> <p>We created a text mining system (LAITOR: <it><b>L</b>iterature <b>A</b>ssistant for <b>I</b>dentification of <b>T</b>erms co-<b>O</b>ccurrences and <b>R</b>elationships</it>) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic.</p> <p>Conclusions</p> <p>Text mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds.</p

Soil-induced impacts on forest structure drive coarse woody debris stocks across central Amazonia

PublishedJournal Article© 2014, © 2014 Botanical Society of Scotland and Taylor & Francis. Background: Coarse woody debris (CWD) is an essential component in tropical forest ecosystems and its quantity varies widely with forest types. Aims: Relationships among CWD, soil, forest structure and other environmental factors were analysed to understand the drivers of variation in CWD in forests on different soil types across central Amazonia. Methods: To estimate CWD stocks and density of dead wood debris, 75 permanent forest plots of 0.5 ha in size were assessed along a transect that spanned ca. 700 km in undisturbed forests from north of the Rio Negro to south of the Rio Amazonas. Soil physical properties were evaluated by digging 2-m-deep pits and by taking auger samples. Results: Soil physical properties were the best predictors of CWD stocks; 37% of its variation was explained by effective soil depth. CWD stocks had a two-fold variation across a gradient of physical soil constraints (i.e. effective soil depth, anoxia and soil structure). Average biomass per tree was related to physical soil constraints, which, in turn, had a strong relationship with local CWD stocks. Conclusions: Soil physical properties appear to control average biomass per tree (and through this affect forest structure and dynamics), which, in turn, is correlated with CWD production and stocks

Holography For a De Sitter-Esque Geometry

Warped dS$_3$ arises as a solution to topologically massive gravity (TMG) with positive cosmological constant $+1/\ell^2$ and Chern-Simons coefficient $1/\mu$ in the region $\mu^2 \ell^2 < 27$. It is given by a real line fibration over two-dimensional de Sitter space and is equivalent to the rotating Nariai geometry at fixed polar angle. We study the thermodynamic and asymptotic structure of a family of geometries with warped dS$_3$ asymptotics. Interestingly, these solutions have both a cosmological horizon and an internal one, and their entropy is unbounded from above unlike black holes in regular de Sitter space. The asymptotic symmetry group resides at future infinity and is given by a semi-direct product of a Virasoro algebra and a current algebra. The right moving central charge vanishes when $\mu^2 \ell^2 = 27/5$. We discuss the possible holographic interpretation of these de Sitter-esque spacetimes.Comment: 22 pages, 1 figure; v2: typos corrected, to match with published versio

Oral health-related quality of life of paediatric patients with AIDS

<p>Abstract</p> <p>Background</p> <p>Children with Acquired Immune Deficiency Syndrome (AIDS) exhibit impaired dental status, which can affect their quality of life. This study assessed the oral health-related quality of life of these patients and associated factors.</p> <p>Methods</p> <p>The "Child Perceptions Questionnaire 11-14", rating overall and domain-specific (oral symptoms, functional limitations, emotional well being, and social well being) oral health-related quality of life (OHR-QoL) was completed by 88 children with AIDS assisted in the Child Institute, Sao Paulo, Brazil. Parents or guardians provided behavioural and socio-demographic information. The clinical status was provided by hospital records. OHR-QoL covariates were assessed by Poisson regression analysis.</p> <p>Results</p> <p>The most affected OHR-QoL subscale concerned oral symptoms, whose rate was 23.9%. The direct answer for oral health and well being made up a rate of 47.7%. Brushing the teeth less than two times a day and viral load exceeding 10,000 HIV-RNA copies per millilitre of plasma were directly associated (p < 0.05) with a poorer oral health-related quality of life.</p> <p>Conclusions</p> <p>Children with more severe AIDS manifestations complained of poorer status of oral symptoms, functional limitations, emotional and social well being related to their oral health. Recognizing the factors that are associated with poorer OHR-QoL in children with AIDS may contribute to the planning of dental services for this population.</p

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis