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Abstract: Cytokines are important in the understanding of the immune process in health and disease and are valuable indicators in diagnostics. Measurements of cytokines are based on immunometric methods, and it is important to understand possible pitfalls in these methods to produce reliable cytokine data. This paper focuses on obtaining optimal measurements when applying enzyme-linked immunosorbent assay (ELISA) or multiplex immunoassays (MIA). Cytokines are measured in serum or plasma, as well as in various other body fluids, all containing a series of antibodies and the possibility of interference from these. Some antibodies, such as heterophilic and human anti-animal antibodies, are able to interfere with all immunoassays, but the immunometric techniques are most prone to serious interference from this source. Another type, rheumatoid factor (RF) is a composite of different autoimmune antibodies which can be present in both blood and synovial fluid. RF is present in some arthritic diseases as well as in some other medical conditions. When present, especially RF IgM is known to interfere with the immunometric measurements. A possible and affordable solution to diminish this interference is PEG precipitation, but other efficient, but more expensive, methods, such as precipitation using Protein L or commercially available blocking agents, are also available. Interference of RF is at present not tested in all cytokine assays, but degree of interference from RF, human anti-animal and heterophilic antibodies, as well as from other possible disease-specific antibodies, must always be considered when developing and applying new assays for cytokine measurements. [Copyright &y& Elsevier]

Abstract: Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class I binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify HLA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. [Copyright &y& Elsevier]