Inactive Disease and Remission in Childhood-Onset Systemic Lupus Erythematosus

Objective. To define inactive disease (ID) and clinical remission (CR) and to delineate variables that can be used to measure ID/CR in childhood-onset systemic lupus erythematosus (cSLE). Methods. Delphi questionnaires were sent to an international group of pediatric rheumatologists. Respondents provided information about variables to be used in future algorithms to measure ID/CR. The usefulness of these variables was assessed in 35 children with ID and 31 children with minimally active lupus (MAL). Results. While ID reflects cSLE status at a specific point in time, CR requires the presence of ID for >6 months and considers treatment. There was consensus that patients in ID/CR can have <2 mild nonlimiting symptoms (i.e., fatigue, arthralgia, headaches, or myalgia) but not Raynaud's phenomenon, chest pain, or objective physical signs of cSLE; antinuclear antibody positivity and erythrocyte sedimentation rate elevation can be present. Complete blood count, renal function testing, and complement C3 all must be within the normal range. Based on consensus, only damage-related laboratory or clinical findings of cSLE are permissible with ID. The above parameters were suitable to differentiate children with ID/CR from those with MAL (area under the receiver operating characteristic curve >0.85). Disease activity scores with or without the physician global assessment of disease activity and patient symptoms were well suited to differentiate children with ID from those with MAL. Conclusion. Consensus has been reached on common definitions of ID/CR with cSLE and relevant patient characteristics with ID/CR. Further studies must assess the usefulness of the data-driven candidate criteria for ID in cSLE.

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.