Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Preimplantation development regulatory pathway construction through a text-mining approach

Background: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. Results: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. Conclusions: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.

SLCO1B1 rs4149056 polymorphism associated with statin-induced myopathy is differently distributed according to ethnicity in the Brazilian general population: Amerindians as a high risk ethnic group

Background Recent studies reported the association between SLCO1B1 polymorphisms and the development of statin-induced myopathy. In the scenario of the Brazilian population, being one of the most heterogeneous in the world, the main aim here was to evaluate SLCO1B1 polymorphisms according to ethnic groups as an initial step for future pharmacogenetic studies. Methods One hundred and eighty-two Amerindians plus 1,032 subjects from the general urban population were included. Genotypes for the SLCO1B1 rs4149056 (c.T521C, p.V174A, exon 5) and SLCO1B1 rs4363657 (g.T89595C, intron 11) polymorphisms were detected by polymerase chain reaction followed by high resolution melting analysis with the Rotor Gene 6000® instrument. Results The frequencies of the SLCO1B1 rs4149056 and rs4363657 C variant allele were higher in Amerindians (28.3% and 26.1%) and were lower in African descent subjects (5.7% and 10.8%) compared with Mulatto (14.9% and 18.2%) and Caucasian descent (14.8% and 15.4%) ethnic groups (p < 0.001 and p < 0.001, respectively). Linkage disequilibrium analysis show that these variant alleles are in different linkage disequilibrium patterns depending on the ethnic origin. Conclusion Our findings indicate interethnic differences for the SLCO1B1 rs4149056 C risk allele frequency among Brazilians. These data will be useful in the development of effective programs for stratifying individuals regarding adherence, efficacy and choice of statin-type.

Pharmacological interventions in the treatment of the acute effects of cannabis: a systematic review of literature

Abstract Background Cannabis intoxication is related to a number of physical and mental health risks with ensuing social costs. However, little attention has been given to the investigation of possible pharmacological interactions in this condition. Objective To review the available scientific literature concerning pharmacological interventions for the treatment of the acute effects of cannabis. Methods A search was performed on the Pubmed, Lilacs, and Scielo online databases by combining the terms cannabis, intoxication, psychosis, anxiety, and treatment. The articles selected from this search had their reference lists checked for additional publications related to the topic of the review. Results The reviewed articles consisted of case reports and controlled clinical trials and are presented according to interventions targeting the physiological, psychiatric, and cognitive symptoms provoked by cannabis. The pharmacological interventions reported in these studies include: beta-blockers, antiarrhythmic agents, antagonists of CB-1 and GABA-benzodiazepine receptors, antipsychotics, and cannabidiol. Conclusion Although scarce, the evidence on pharmacological interventions for the management of cannabis intoxication suggests that propanolol and rimonabant are the most effective compounds currently available to treat the physiological and subjective effects of the drug. Further studies are necessary to establish the real effectiveness of these two medications, as well as the effectiveness of other candidate compounds to counteract the effects of cannabis intoxication, such as cannabidiol and flumazenil.

Weight loss in combat sports: physiological, psychological and performance effects

Abstract Background The present article briefly reviews the weight loss processes in combat sports. We aimed to discuss the most relevant aspects of rapid weight loss (RWL) in combat sports. Methods This review was performed in the databases MedLine, Lilacs, PubMed and SciELO, and organized into sub-topics: (1) prevalence, magnitude and procedures, (2) psychological, physiological and performance effects, (3) possible strategies to avoid decreased performance (4) organizational strategies to avoid such practices. Results There was a high prevalence (50%) of RWL, regardless the specific combat discipline. Methods used are harmful to performance and health, such as laxatives, diuretics, use of plastic or rubber suits, and sauna. RWL affects physical and cognitive capacities, and may increase the risk of death. Conclusion Recommendations during different training phases, educational and organizational approaches are presented to deal with or to avoid RWL.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.

The biopsychosocial processes in autism spectrum disorder

Abstract Background Autism is a disorder characterized by pervasive social and communicative impairments, repetitive and stereotyped behaviors and restricted interests. Its causes and effects have been researched from various neurocognitive theoretical perspectives and with the aid of neuroimaging technology. We aimed to describe biopsychosocial processes characteristic of the Autism Spectrum Disorders. Method Literature review using Medline and Scopus databases published between 2001 and 2011, with the keywords "autism", "theory of mind", "executive functions", "central coherence" and “fMRI”. Results The studies found were plotted and organized into tables and an explanatory diagram of the main findings was produced. Conclusions The most popular neurocognitive theories are still unable to fully explain the characteristics of the complications that autistic spectrum disorder causes to the quality of life of individuals living with autism. The association of clinical research and neuroimaging may contribute to a better understanding of the functioning of the brain affected by the disorder.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

Denominal Verbs in Brazilian Portuguese: distinguishing between diachronic and synchronic structures within Distributed Morphology approach

Recent work on argument structure has shown that there must be a synchronic relation between nouns and derived verbs that can be treated in structural terms. However, a simple phonological/morphological identity or diachronic derivation between a verb and a noun cannot guarantee that there is a denominal structure in a synchronic approach. In this paper we observe the phenomenon of Denominal Verbs in Brazilian Portuguese and argue for a distinction between etymological and synchronic morphological derivation. The objectives of this paper are 1) to identify synchronic and formal criteria to define which diachronic Denominal Verbs can also be considered denominal under a synchronic analysis; and 2) to detect in which cases the label "denominal" can be justifiably abandoned. Based on results of argument structure tests submitted to the judgments of native speakers, it was possible to classify the supposed homogenous Denominal Verbs class into three major groups: Real Denominal Verbs, Root-derived Verbs, and Ambiguous Verbs. In a Distributed Morphology approach, it was possible to explain the distinction between these groups based on the ideia of phases in words and the locality of restriction in the interpretation of roots.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.