Bgee: integrating and comparing heterogeneous transcriptome data among species

Gene expression patterns are a key feature in understanding gene function, notably in development. Comparing gene expression patterns between animals is a major step in the study of gene function as well as of animal evolution. It also provides a link between genes and phenotypes. Thus we have developed Bgee, a database designed to compare expression patterns between animals, by implementing ontologies describing anatomies and developmental stages of species, and then designing homology relationships between anatomies and comparison criteria between developmental stages. To define homology relationships between anatomical features we have developed the software Homolonto, which uses a modified ontology alignment approach to propose homology relationships between ontologies. Bgee then uses these aligned ontologies, onto which heterogeneous expression data types are mapped. These already include microarrays and ESTs.

Hours worked - Productivity puzzle: identification in fractional integration settings

A recent finding of the structural VAR literature is that the response of hours worked to a technology shock depends on the assumption on the order of integration of the hours. In this work we relax this assumption, allowing for fractional integration and long memory in the process for hours and productivity. We find that the sign and magnitude of the estimated impulse responses of hours to a positive technology shock depend crucially on the assumptions applied to identify them. Responses estimated with short-run identification are positive and statistically significant in all datasets analyzed. Long-run identification results in negative often not statistically significant responses. We check validity of these assumptions with the Sims (1989) procedure, concluding that both types of assumptions are appropriate to recover the impulse responses of hours in a fractionally integrated VAR. However, the application of longrun identification results in a substantial increase of the sampling uncertainty. JEL Classification numbers: C22, E32. Keywords: technology shock, fractional integration, hours worked, structural VAR, identification

Micropapillary pattern in lung adenocarcinoma: aspect on 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging.

We diagnosed a non-small cell lung carcinoma in a 49-year-old female patient with the histopathological diagnosis of stage IIIB mixed bronchioloalveolar and papillary adenocarcinoma with extensive micropapillary feature, which was not visualized on the preoperative multimodality imaging with positron emission tomography (PET) and computed tomography (CT). The micropapillary component characterized by a unique growth pattern with particular morphological features can be observed in all subtypes of lung adenocarcinoma. Micropapillary component is increasingly recognized as a distinct entity associated with higher aggressiveness. Even the most modern multimodality PET/CT imaging technology may fail to adequately visualize this important component with highly relevant prognostic implications. Thus, the pathologist needs to consciously look for a micropapillary component in the surgical specimen or in preoperative biopsies or cytology. This may have potential future treatment implications, as adjuvant or neoadjuvant chemotherapy may be of relevance, even in the early stages of the disease.

Bristle pattern formation in the thorax formation of Drosophila: a systems level approach

A fundamental question in developmental biology is how tissues are patterned to give rise to differentiated body structures with distinct morphologies. The Drosophila wing disc offers an accessible model to understand epithelial spatial patterning. It has been studied extensively using genetic and molecular approaches. Bristle patterns on the thorax, which arise from the medial part of the wing disc, are a classical model of pattern formation, dependent on a pre-pattern of trans-activators and –repressors. Despite of decades of molecular studies, we still only know a subset of the factors that determine the pre-pattern. We are applying a novel and interdisciplinary approach to predict regulatory interactions in this system. It is based on the description of expression patterns by simple logical relations (addition, subtraction, intersection and union) between simple shapes (graphical primitives). Similarities and relations between primitives have been shown to be predictive of regulatory relationships between the corresponding regulatory factors in other Systems, such as the Drosophila egg. Furthermore, they provide the basis for dynamical models of the bristle-patterning network, which enable us to make even more detailed predictions on gene regulation and expression dynamics. We have obtained a data-set of wing disc expression patterns which we are now processing to obtain average expression patterns for each gene. Through triangulation of the images we can transform the expression patterns into vectors which can easily be analysed by Standard clustering methods. These analyses will allow us to identify primitives and regulatory interactions. We expect to identify new regulatory interactions and to understand the basic Dynamics of the regulatory network responsible for thorax patterning. These results will provide us with a better understanding of the rules governing gene regulatory networks in general, and provide the basis for future studies of the evolution of the thorax-patterning network in particular.

Integration of olfactory information in a spatial representation enabling accurate arm choice in the radial arm maze

The aim of the present study was to determine whether and how rats can use local olfactory cues for spatial orientation. Rats were trained in an eight-arm radial maze under different conditions as defined by the presence or absence of supplementary olfactory cues marking each arm, the availability of distant visuospatial information, and the illumination of the maze (light or darkness). The different visual conditions were designed to dissociate among the effects of light per se and those of visuospatial cues, on the use of olfactory cues for accurate arm choice. Different procedures with modifications of the arrangement of olfactory cues were used to determine if rats formed a representation of the spatial configuration of the olfactory cues and if they could rely on such a representation for accurate arm choice in the radial maze. The present study demonstrated that the use of olfactory cues to direct arm choice in the radial arm maze was critically dependent on the illumination conditions and implied two different modes of processing of olfactory information according to the presence or the absence of light. Olfactory cues were used in an explicit manner and enabled accurate arm choice only in the absence of light. Rats, however, had an implicit memory of the location of the olfactory cues and formed a representation of the spatial position of these cues, whatever the lighting conditions. They did not memorize the spatial configuration of the olfactory cues per se but needed these cues to be linked to the external spatial frame of reference.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

A multicase study for the evaluation of a pattern-based visual design process for collaborative learning

Collage is a pattern-based visual design authoring tool for the creation of collaborative learning scripts computationally modelled with IMS Learning Design (LD). The pattern-based visual approach aims to provide teachers with design ideas that are based on broadly accepted practices. Besides, it seeks hiding the LD notation so that teachers can easily create their own designs. The use of visual representations supports both the understanding of the design ideas and the usability of the authoring tool. This paper presents a multicase study comprising three different cases that evaluate the approach from different perspectives. The first case includes workshops where teachers use Collage. A second case implies the design of a scenario proposed by a third-party using related approaches. The third case analyzes a situation where students follow a design created with Collage. The cross-case analysis provides a global understanding of the possibilities and limitations of the pattern-based visual design approach.

@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

From a pattern-language to a pattern ontology approach for CSCL script design

Collaborative activities, in which students actively interact with each other, have proved to provide significant learning benefits. In Computer-Supported Collaborative Learning (CSCL), these collaborative activities are assisted by technologies. However, the use of computers does not guarantee collaboration, as free collaboration does not necessary lead to fruitful learning. Therefore, practitioners need to design CSCL scripts that structure the collaborative settings so that they promote learning. However, not all teachers have the technical and pedagogical background needed to design such scripts. With the aim of assisting teachers in designing effective CSCL scripts, we propose a model to support the selection of reusable good practices (formulated as patterns) so that they can be used as a starting point for their own designs. This model is based on a pattern ontology that computationally represents the knowledge captured on a pattern language for the design of CSCL scripts. A preliminary evaluation of the proposed approach is provided with two examples based on a set of meaningful interrelated patters computationally represented with the pattern ontology, and a paper prototyping experience carried out with two teaches. The results offer interesting insights towards the implementation of the pattern ontology in software tools.

Coordination pattern variability provides functional adaptations to constraints in swimming performance.

In a biophysical approach to the study of swimming performance (blending biomechanics and bioenergetics), inter-limb coordination is typically considered and analysed to improve propulsion and propelling efficiency. In this approach, 'opposition' or 'continuous' patterns of inter-limb coordination, where continuity between propulsive actions occurs, are promoted in the acquisition of expertise. Indeed a 'continuous' pattern theoretically minimizes intra-cyclic speed variations of the centre of mass. Consequently, it may also minimize the energy cost of locomotion. However, in skilled swimming performance there is a need to strike a delicate balance between inter-limb coordination pattern stability and variability, suggesting the absence of an 'ideal' pattern of coordination toward which all swimmers must converge or seek to imitate. Instead, an ecological dynamics framework advocates that there is an intertwined relationship between the specific intentions, perceptions and actions of individual swimmers, which constrains this relationship between coordination pattern stability and variability. This perspective explains how behaviours emerge from a set of interacting constraints, which each swimmer has to satisfy in order to achieve specific task performance goals and produce particular task outcomes. This overview updates understanding on inter-limb coordination in swimming to analyse the relationship between coordination variability and stability in relation to interacting constraints (related to task, environment and organism) that swimmers may encounter during training and performance.

Man Made Black Holes and Big Bangs: Diffusion and Integration of Scientific Information into Everyday Thinking

Drawing on Social Representations Theory, this study investigates focalisation and anchoring during the diffusion of information concerning the Large Hadron Collider (LHC), the particle accelerator at the European Organisation for Nuclear Research (CERN). We hypothesised that people focus on striking elements of the message, abandoning others, that the nature of the initial information affects diffusion of information, and that information is anchored in prior attitudes toward CERN and science. A serial reproduction experiment with two generations and four chains of reproduction diffusing controversial versus descriptive information about the LHC shows a reduction of information through generations, the persistence of terminology regarding the controversy and a decrease of other elements for participants exposed to polemical information. Concerning anchoring, positive attitudes toward CERN and science increase the use of expert terminology unrelated to the controversy. This research highlights the relevance of a social representational approach in the public understanding of science.

MAR elements and transposons for improved transgene integration and expression.

Reliable and long-term expression of transgenes remain significant challenges for gene therapy and biotechnology applications, especially when antibiotic selection procedures are not applicable. In this context, transposons represent attractive gene transfer vectors because of their ability to promote efficient genomic integration in a variety of mammalian cell types. However, expression from genome-integrating vectors may be inhibited by variable gene transcription and/or silencing events. In this study, we assessed whether inclusion of two epigenetic control elements, the human Matrix Attachment Region (MAR) 1-68 and X-29, in a piggyBac transposon vector, may lead to more reliable and efficient expression in CHO cells. We found that addition of the MAR 1-68 at the center of the transposon did not interfere with transposition frequency, and transgene expressing cells could be readily detected from the total cell population without antibiotic selection. Inclusion of the MAR led to higher transgene expression per integrated copy, and reliable expression could be obtained from as few as 2-4 genomic copies of the MAR-containing transposon vector. The MAR X-29-containing transposons was found to mediate elevated expression of therapeutic proteins in polyclonal or monoclonal CHO cell populations using a transposable vector devoid of selection gene. Overall, we conclude that MAR and transposable vectors can be used to improve transgene expression from few genomic transposition events, which may be useful when expression from a low number of integrated transgene copies must be obtained and/or when antibiotic selection cannot be applied.

Health risk behavior pattern among students from Cartagena, Colombia: prevalence and associated variables

The aim of the study was to determine the prevalence and variables associated with the pattern of risky health behavior (PRHB) among adolescent students in Cartagena, Colombia. A cross-sectional study was designed to investigate PRHB in a random cluster sample of students from middle and high schools. The associations were adjusted by logistic regression. A total of 2,625 students participated in this research, with ages from 10 to 20 years, mean=13.8 years (SD=2.0), and 54.3% were women. A total of 332 students reported PRHB (12.7%, 95%CI 11.4–14.0). Age over 15 years (OR=2.19, 95%CI 1.72–2.79), not being heterosexual (OR=1.98, 95%CI 1.36-2.87), poor/mediocre academic performance (OR=1.87, 95%CI 1.47–2.38), family dysfunction (OR=1.78, 95%CI 1.40–2.28) and male gender (OR=1.58, 95%CI 1.24–2.01) were associated with PRHB. One in every eight students presented a PRHB. It is important to pay greater attention to students who are over 15 years of age, male, not heterosexual, with a poor/mediocre academic performance and a dysfunctional family.