Verso: A data base machine based on non 1NF relations

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Antigen-Specific B Memory Cell Responses to Plasmodium falciparum Malaria Antigens and Schistosoma haematobium Antigens in Co-Infected Malian Children

Polyparasitism is common in the developing world. We have previously demonstrated that schistosomiasis-positive (SP) Malian children have age-dependent protection from malaria compared to matched schistosomiasis-negative (SN) children. Evidence of durable immunologic memory to malaria antigens is conflicting, particularly in young children and the effect of concomitant schistomiasis upon acquisition of memory is unknown. We examined antigen-specific B memory cell (MBC) frequencies (expressed as percentage of total number of IgG-secreting cells) in 84 Malian children aged 4–14 to malaria blood-stage antigens, apical membrane antigen 1 (AMA-1) and merozoite surface protein 1 (MSP-1) and to schistosomal antigens, Soluble Worm Antigenic Preparation (SWAP) and Schistosoma Egg Antigen (SEA), at a time point during the malaria transmission season and a follow-up dry season visit. We demonstrate, for the first time, MBC responses to S. haematobium antigens in Malian children with urinary egg excretion and provide evidence of seasonal acquisition of immunologic memory, age-associated differences in MBC acquisition, and correlation with circulating S. haematobium antibody. Moreover, the presence of a parasitic co-infection resulted in older children, aged 9–14 years, with underlying S. haematobium infection having significantly more MBC response to malaria antigens (AMA1 and MSP1) than their age-matched SN counterparts. We conclude that detectable MBC response can be measured against both malaria and schistosomal antigens and that the presence of S. haematobium may be associated with enhanced MBC induction in an age-specific manner

Drawing Euler Diagrams with Circles

Euler diagrams are a popular and intuitive visualization tool which are used in a wide variety of application areas, including biological and medical data analysis. As with other data visualization methods, such as graphs, bar charts, or pie charts, the automated generation of an Euler diagram from a suitable data set would be advantageous, removing the burden of manual data analysis and the subsequent task of drawing an appropriate diagram. To this end, various methods have emerged that automatically draw Euler diagrams from abstract descriptions of them. One such method draws some, but not all, abstract descriptions using only circles. We extend that method so that more abstract descriptions can be drawn with circles. Furthermore, we show how to transform any `undrawable' abstract description into a drawable one. Thus, given any abstract description, our method produces a drawing using only circles. The method has been implemented in a software tool available for download

General Euler Diagram Generation

Euler diagrams are a natural method of representing set-theoretic data and have been employed in diverse areas such as Visualizing statistical data, as a basis for diagrammatic logics and for displaying the results of database search queries. For effective use of Euler diagrams in practical computer based applications, the generation of a diagram as a set of curves from an abstract description is necessary. Various practical methods for Euler diagram generation have been proposed, but in all of these methods the diagrams that can be produced are only for it restricted Subset of all possible abstract descriptions. We describe a method for Euler diagram generation, demonstrated by implemented software. and illustrate the advances in methodology via the production of diagrams which were difficult or impossible to draw using previous approaches. To allow the generation of all abstract descriptions we may be reqUired to have some properties of the final diagram that are not considered nice. In particular we permit more than two curves to pass though it single point, permit sonic curve segments to be drawn Concurrently, and permit duplication of curve labels. However, Our method attempts to minimize these bad properties according to it chosen prioritization