Showing papers by "Derek J. Smith published in 1997"

The cross-reactive immune response: analysis, modeling, and application to vaccine design

Abstract: of Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Computer Science The University of New Mexico Albuquerque, New Mexico

Modeling the effects of prior infection on vaccine efficacy

Abstract: We performed computer simulations to study the effects of prior infection on vaccine efficacy. We injected three antigens sequentially. The first antigen, designated the prior, represented a prior infection or vaccination. The second antigen, the vaccine, represented a single component of the trivalent influenza vaccine. The third antigen, the epidemic, represented challenge by an epidemic strain. For a fixed vaccine to epidemic strain cross-reactivity, we generated prior strains over a full range of cross-reactivities to the vaccine and to the epidemic strains. We found that, for many cross-reactivities, vaccination, when it had been preceded by a prior infection, provided more protection than vaccination alone. However, at some cross-reactivities, the prior infection reduced protection by clearing the vaccine before it had the chance to produce protective memory. The cross-reactivities between the prior, vaccine and epidemic strains played a major role in determining vaccine efficacy. This work has applications to understanding vaccination against viruses such as influenza that are continually mutating.

Deriving Shape Space Parameters from Immunological Data for a Model of Cross-Reactive Memory

Abstract: Cross-reactive memory responses occur when the immune system is primed by one strain of a pathogen and challenged with a related, but different strain Much of the nature of a cross-reactive response is determined by the quantity and distribution of the memory cells, raised to the primary antigen, that cross-react with the secondary antigen B cells with above threshold affinity for an antigen lie in a region of shape space that we call a {\it ball of stimulation} In a cross-reactive response, the intersection of balls of stimulation of the primary and secondary antigens contains the cross-reactive B cells and thus determines the degree of cross-reactivity between the antigens We derive formulas for the volume of intersection of balls of stimulation in different shape spaces, and show that the parameters of shape space, such as its dimensionality, have a large impact on the number of B cells in the intersection We present a method for deriving shape space parameters that are consistent with immunological data, and illustrate the method by deriving shape space parameters for a model of cross-reactive memory For Hamming shape spaces, the method indicates that twenty to twenty-five dimensions, a three or four letter alphabet, and balls of stimulation of radius five or six, are choices that match the experimental data For Euclidean shape spaces, five to eight dimensions and balls of stimulation with radius about twenty percent of the radius of the whole space, match the experimental data

Using Lazy Evaluation to Simulate Realistic-Size Repertoires in Models of the Immune System

Abstract: We describe a method of implementing efficient computer simulations of immune systems that have a large number of unique B and/or T cell clones. The method uses an implementation technique called lazy evaluation to create the illusion that all clones are being simulated, while only actually simulating a much smaller number of clones that can respond to the antigens in the simulation. The method is effective because only 0.001% to 0.01% of clones can typically be simulated by an antigen, and because many simulations involve only a small number of distinct antigens. A lazy simulation of a realistic number of clones and 10 distinct antigens is 1,000 times faster and 10,000 times smaller than a conventional simulation---making simulations of immune systems with realistic-size repertoires computationally tractable.