DeCS terminology and the new rules on orthography of Portuguese language: guidelines for an update

PURPOSE: To indicate orthographic changes to be used as a basic reference for professionals, researchers, doctors, teachers, students and users, which are directly linked and performing activities in health services in general, aimed at implementing the correct orthography in recovery and production of their scientific studies. METHODS: For data collection, were shown some examples of terminology DeCS (Descriptors in Health Science) analyzed according to the current spelling and compared with the Orthographic Vocabulary of Portuguese Language (VOLP). RESULTS: It was select and listed examples of key words and/or terms related to Health Sciences, which was compared to the respective rules of the Orthographic Agreement of Portuguese Language, and divided into three items: graphical accentuation, the non use of dieresis and exceptions and, the use of hyphen. CONCLUSION: This study show some guidelines for the orthographic alterations of the terms used by scientific community, according the new orthographic rules, contributing for the efficiency in the description of the documents and consequently in their recovery.

Finding our way through phenotypes.

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Consensus nomenclature for the human ArfGAP domain-containing proteins.

At the FASEB summer research conference on "Arf Family GTPases", held in Il Ciocco, Italy in June, 2007, it became evident to researchers that our understanding of the family of Arf GTPase activating proteins (ArfGAPs) has grown exponentially in recent years. A common nomenclature for these genes and proteins will facilitate discovery of biological functions and possible connections to pathogenesis. Nearly 100 researchers were contacted to generate a consensus nomenclature for human ArfGAPs. This article describes the resulting consensus nomenclature and provides a brief description of each of the 10 subfamilies of 31 human genes encoding proteins containing the ArfGAP domain.

Revised definitions of invasive fungal disease from the European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC/MSG) Consensus Group.

BACKGROUND: Invasive fungal diseases are important causes of morbidity and mortality. Clarity and uniformity in defining these infections are important factors in improving the quality of clinical studies. A standard set of definitions strengthens the consistency and reproducibility of such studies. METHODS: After the introduction of the original European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC/MSG) Consensus Group definitions, advances in diagnostic technology and the recognition of areas in need of improvement led to a revision of this document. The revision process started with a meeting of participants in 2003, to decide on the process and to draft the proposal. This was followed by several rounds of consultation until a final draft was approved in 2005. This was made available for 6 months to allow public comment, and then the manuscript was prepared and approved. RESULTS: The revised definitions retain the original classifications of "proven," "probable," and "possible" invasive fungal disease, but the definition of "probable" has been expanded, whereas the scope of the category "possible" has been diminished. The category of proven invasive fungal disease can apply to any patient, regardless of whether the patient is immunocompromised, whereas the probable and possible categories are proposed for immunocompromised patients only. CONCLUSIONS: These revised definitions of invasive fungal disease are intended to advance clinical and epidemiological research and may serve as a useful model for defining other infections in high-risk patients.

Esperanto for histones: CENP-A, not CenH3, is the centromeric histone H3 variant

The first centromeric protein identified in any species was CENP-A, a divergent member of the histone H3 family that was recognised by autoantibodies from patients with scleroderma-spectrum disease. It has recently been suggested to rename this protein CenH3. Here, we argue that the original name should be maintained both because it is the basis of a long established nomenclature for centromere proteins and because it avoids confusion due to the presence of canonical histone H3 at centromeres.

Semantic Classes in Topic Detection and Tracking

Topic detection and tracking (TDT) is an area of information retrieval research the focus of which revolves around news events. The problems TDT deals with relate to segmenting news text into cohesive stories, detecting something new, previously unreported, tracking the development of a previously reported event, and grouping together news that discuss the same event. The performance of the traditional information retrieval techniques based on full-text similarity has remained inadequate for online production systems. It has been difficult to make the distinction between same and similar events. In this work, we explore ways of representing and comparing news documents in order to detect new events and track their development. First, however, we put forward a conceptual analysis of the notions of topic and event. The purpose is to clarify the terminology and align it with the process of news-making and the tradition of story-telling. Second, we present a framework for document similarity that is based on semantic classes, i.e., groups of words with similar meaning. We adopt people, organizations, and locations as semantic classes in addition to general terms. As each semantic class can be assigned its own similarity measure, document similarity can make use of ontologies, e.g., geographical taxonomies. The documents are compared class-wise, and the outcome is a weighted combination of class-wise similarities. Third, we incorporate temporal information into document similarity. We formalize the natural language temporal expressions occurring in the text, and use them to anchor the rest of the terms onto the time-line. Upon comparing documents for event-based similarity, we look not only at matching terms, but also how near their anchors are on the time-line. Fourth, we experiment with an adaptive variant of the semantic class similarity system. The news reflect changes in the real world, and in order to keep up, the system has to change its behavior based on the contents of the news stream. We put forward two strategies for rebuilding the topic representations and report experiment results. We run experiments with three annotated TDT corpora. The use of semantic classes increased the effectiveness of topic tracking by 10-30\% depending on the experimental setup. The gain in spotting new events remained lower, around 3-4\%. The anchoring the text to a time-line based on the temporal expressions gave a further 10\% increase the effectiveness of topic tracking. The gains in detecting new events, again, remained smaller. The adaptive systems did not improve the tracking results.

Evidence-based practice and information literacy

Evidence-based Practice (EBP) has recently emerged as a topic of discussion amongst professionals within the library and information services (LIS) industry. Simply stated, EBP is the process of using formal research skills and methods to assist in decision making and establishing best practice. The emerging interest in EBP within the library context serves to remind the library profession that research skills and methods can help ensure that the library industry remains current and relevant in changing times. The LIS sector faces ongoing challenges in terms of the expectation that financial and human resources will be managed efficiently, particularly if library budgets are reduced and accountability to the principal stakeholders is increased. Library managers are charged with the responsibility to deliver relevant and cost effective services, in an environment characterised by rapidly changing models of information provision, information access and user behaviours. Consequently they are called upon not only to justify the services they provide, or plan to introduce, but also to measure the effectiveness of these services and to evaluate the impact on the communities they serve. The imperative for innovation in and enhancements to library practice is accompanied by the need for a strong understanding of the processes of review, measurement, assessment and evaluation. In 2001 the Centre for Information Research was commissioned by the Chartered Institute of Library and Information Professionals (CILIP) in the UK to conduct an examination into the research landscape for library and information science. The examination concluded that research is “important for the LIS [library and information science] domain in a number of ways” (McNicol & Nankivell, 2001, p.77). At the professional level, research can inform practice, assist in the future planning of the profession, raise the profile of the discipline, and indeed the reputation and standing of the library and information service itself. At the personal level, research can “broaden horizons and offer individuals development opportunities” (McNicol & Nankivell, 2001, p.77). The study recommended that “research should be promoted as a valuable professional activity for practitioners to engage in” (McNicol & Nankivell, 2001, p.82). This chapter will consider the role of EBP within the library profession. A brief review of key literature in the area is provided. The review considers issues of definition and terminology, highlights the importance of research in professional practice and outlines the research approaches that underpin EBP. The chapter concludes with a consideration of the specific application of EBP within the dynamic and evolving field of information literacy (IL).

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.