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Complexity and the Immune System

Complexity and the Immune System. Why look at the immune system?. -Intermediate level -One of the major information processing systems in the body (with neural system) -Competing theories that can be tested - we’ll see how well the network theory holds up in this case. Main Issues.

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Complexity and the Immune System

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  1. Complexity and the Immune System

  2. Why look at the immune system? -Intermediate level -One of the major information processing systems in the body (with neural system) -Competing theories that can be tested - we’ll see how well the network theory holds up in this case

  3. Main Issues • Protection: find and destroy invaders • Self Recognition: don’t destroy cells from your own body • Memory of past pathogens

  4. Immune System Basics • Antigens and antigen determinants • Multiple epitopes per cell of any type • Antibodies (4 chains; “variable region”) • B cells and clones • T cells (recognize peptide fragments from MHC)

  5. Niels Kaj JerneDanish Immunologist • Shared the Nobel prize in 1984 for his work • Theory of antibody formation (from genetic variation rather than a response to pathogens) - 1955 • The body learns to distinguish between self and nonself in the thymus - 1971 • Concept of the immune system as complex, self-regulating network - 1974

  6. Self Defense in a Network System • Key factors: • Quick and full response from those antibodies that can bind to the right antigen determinants • Response that dies down (ie doesn’t explode) • Memory of past pathogens so that response is quicker next time

  7. Networks that do this • Coupled PDEs involving the concentration of antibodies and antigens • Multi-dimensional space that maps shape characteristics that allow binding (eg hydrophilicity/polarity, physical shape, etc) • Cellular automata where each point r (vector) is coupled to the points around its mirror image, -r

  8. Results -This behavior was seen for a region near the boundary between stable and chaotic behavior of the automata -Preserved over a range of dimensions (biologically need at least 5 dimensions to cover “shape space”) and lattice sizes

  9. But do we really need the network? • Genetic variation can lead to B and T cells that cover the entire range of pathogens, and each antibody hits on average one antigen • B cells differentiate into memory cells, which are able to quickly split into lots of effector cells and more memory cells • After an attack, have more memory cells, and they’re more coordinated

  10. What about self-recognition? -Self recognition is “learned” - each organism has different self-antigens and can recognize them -If “other” antigens are introduced at a particular stage in development, the organism will incorporate them as “self” (mice)

  11. Can networks do this? • Yes! Well, small networks can. Particularly, networks with an odd number of nodes connected in loops can. • Some networks blow up under a small but constant antigen concentration • But some don’t - and those are the ones that seem to correspond most closely to biological reality

  12. But… the non-network solution • T cells are “weeded out” in the thymus if they attack the self antigens • B and T cells somehow trigger a self-destruction signal if they respond too strongly or too weakly to self antigens as they develop

  13. But, immune networks have other applications! • Data analysis • Other computers • Models for body-wide immune events (as models of system-wide behavior, can explain some medical results)

  14. References • Bernandes, A. T. et al. Immune network at the edge of chaos. Journal of Theoretical Biology. ISI Web of Knowledge. 1997. • Calenbuhr, V. et al. Natural tolerance in a simple immune network. Journal of Theoretical Biology. ISI Web of Knowledge. 2001. • Sun, J. et al. Glassy dynamics in the adaptive immune response prevents autoimmune disease. Physical Review Letters. ISI Web of Knowledge. 2005. • Sadava, David, et al. Life: The Science of Biology. 2006. Chapter 18: The Immune System. • Muc-Wierzgon, M, et al. On the holistic approach in cancer biology: Tumer necrosis factor, colon cancer cells, chaos theory and complexity. Journal of Biological Regulators and Homeostatic Agents. ISI Web of Knowledge. 2004. • "Jerne, Niels K.." Encyclopædia Britannica. 2008. Encyclopædia Britannica Online. 3 May 2008  <http://www.britannica.com/eb/article-9043549>. • http://images.google.com/imgres?imgurl=http://farm3.static.flickr.com/2018/2108107685_80a03f1c16.jpg&imgrefurl=http://www.flickr.com/photos/ajc1/2108107685/&h=300&w=300&sz=38&hl=en&start=24&um=1&tbnid=vxsGdLXFDhoDsM:&tbnh=116&tbnw=116&prev=/images%3Fq%3DT%2Bcell%26start%3D20%26ndsp%3D20%26um%3D1%26hl%3Den%26client%3Dsafari%26rls%3Den%26sa%3DN

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