Use of humanised rat basophilic leukaemia cell line RS-ATL8 for the assessment of allergenicity of Schistosoma mansoni proteins.

BACKGROUND Parasite-specific IgE is thought to correlate with protection against Schistosoma mansoni infection or re-infection. Only a few molecular targets of the IgE response in S. mansoni infection have been characterised. A better insight into the basic mechanisms of anti-parasite immunity could be gained from a genome-wide characterisation of such S. mansoni allergens. This would have repercussions on our understanding of allergy and the development of safe and efficacious vaccinations against helminthic parasites. METHODOLOGY/PRINCIPAL FINDINGS A complete medium- to high-throughput amenable workflow, including important quality controls, is described, which enables the rapid translation of S. mansoni proteins using wheat germ lysate and subsequent assessment of potential allergenicity with a humanised Rat Basophilic Leukemia (RBL) reporter cell line. Cell-free translation is completed within 90 minutes, generating sufficient amounts of parasitic protein for rapid screening of allergenicity without any need for purification. Antigenic integrity is demonstrated using Western Blotting. After overnight incubation with infected individuals' serum, the RS-ATL8 reporter cell line is challenged with the complete wheat germ translation mixture and Luciferase activity measured, reporting cellular activation by the suspected allergen. The suitability of this system for characterization of novel S. mansoni allergens is demonstrated using well characterised plant and parasitic allergens such as Par j 2, SmTAL-1 and the IgE binding factor IPSE/alpha-1, expressed in wheat germ lysates and/or E. coli. SmTAL-1, but not SmTAL2 (used as a negative control), was able to activate the basophil reporter cell line. CONCLUSION/SIGNIFICANCE This method offers an accessible way for assessment of potential allergenicity of anti-helminthic vaccine candidates and is suitable for medium- to high-throughput studies using infected individual sera. It is also suitable for the study of the basis of allergenicity of helminthic proteins

Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups

This paper develops a maximum likelihood based methodology for simultaneously performing multidimensional unfolding and cluster analysis on two-way dominance or profile data. This new procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of stimulus coordinates and K ideal points, one for each cluster or group, in a T -dimensional space. The conditional mixture, maximum likelihood methodology is introduced together with an E-M algorithm utilized for parameter estimation. A marketing strategy application is provided with an analysis of PIMS data for a set of firms drawn from the same competitive industry to determine strategic groups, while simultaneously depicting strategy-performance relationships.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47056/1/11002_2004_Article_BF00436033.pd

Tscale: A new multidimensional scaling procedure based on tversky's contrast model

Tversky's contrast model of proximity was initially formulated to account for the observed violations of the metric axioms often found in empirical proximity data. This set-theoretic approach models the similarity/dissimilarity between any two stimuli as a linear (or ratio) combination of measures of the common and distinctive features of the two stimuli. This paper proposes a new spatial multidimensional scaling (MDS) procedure called TSCALE based on Tversky's linear contrast model for the analysis of generally asymmetric three-way, two-mode proximity data. We first review the basic structure of Tversky's conceptual contrast model. A brief discussion of alternative MDS procedures to accommodate asymmetric proximity data is also provided. The technical details of the TSCALE procedure are given, as well as the program options that allow for the estimation of a number of different model specifications. The nonlinear estimation framework is discussed, as are the results of a modest Monte Carlo analysis. Two consumer psychology applications are provided: one involving perceptions of fast-food restaurants and the other regarding perceptions of various competitive brands of cola soft-drinks. Finally, other applications and directions for future research are mentioned.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45750/1/11336_2005_Article_BF02294658.pd

A nonspatial methodology for the analysis of two-way proximity data incorporating the distance-density hypothesis

This paper presents a nonspatial operationalization of the Krumhansl (1978, 1982) distancedensity model of similarity. This model assumes that the similarity between two objects i and j is a function of both the interpoint distance between i and j and the density of other stimulus points in the regions surrounding i and j . We review this conceptual model and associated empirical evidence for such a specification. A nonspatial, tree-fitting methodology is described which is sufficiently flexible to fit a number of competing hypotheses of similarity formation. A sequential, unconstrained minimization algorithm is technically presented together with various program options. Three applications are provided which demonstrate the flexibility of the methodology. Finally, extensions to spatial models, three-way analyses, and hybrid models are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45746/1/11336_2005_Article_BF02295285.pd