Constitutive CD8 expression allows inefficient maturation of CD4+ helper T cells in class II major histocompatibility complex mutant mice.

Although mature CD4+ T cells bear T cell receptors (TCRs) that recognize class II major histocompatibility complex (MHC) and mature CD8+ T cells bear TCRs that recognize class I MHC, it is possible that the initial commitment of an immature thymocyte to a CD4 or CD8 lineage is made without regard to the specificity of the TCR. According to this model, CD4+ cells with class I TCR do not mature because the CD8 coreceptor is required for class I MHC recognition and positive selection. If this model is correct, constitutive expression of CD8 should allow CD4+ T cells with class I-specific TCRs to develop. In this report, we show that mature peripheral CD4+ cells are present in class II MHC-deficient mice that express a constitutive CD8.1 transgene. These cells share a number of properties with the major class II MHC-selected CD4 population, including the ability to express CD40 ligand upon activation. Although mature CD4 cells are also detectable in the thymus of class II MHC mutant/CD8.1 transgenic mice, they represent a small fraction of the mature CD4 cells found in mice that express class II MHC. These results indicate that some T cells choose the CD4 helper lineage independent of their antigen receptor specificity; however, the inefficiency of generating class I-specific CD4 cells leaves open the possibility that an instructive signal generated upon MHC recognition may bias lineage commitment

An investigation into the use of physical modelling for the prediction of various feature types visible from different view points

This paper describes a general purpose flexible technique which uses physical modelling techniques for determining the features of a 3D object that are visible from any predefined view. Physical modelling techniques are used to determine which of many different types of features are visible from a complete set of viewpoints. The power of this technique lies in its ability to detect and parameterise object features, regardless of object complexity. Raytracing is used to simulate the physical process by which object features are visible so that surface properties (eg specularity, transparency) as well as object boundaries can be used in the recognition process. Using this technique occluding and non-occluding edge based features are extracted using image processing techniques and then parameterised. Features caused by specularity are also extracted and qualitative descriptions for these are defined