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U Behn

Publications and source records attributed to U Behn.

10 recordsLinked to original sources
PubMed2001

Architecture of idiotypic networks: percolation and scaling behavior.

We investigate a model where idiotypes (characterizing B lymphocytes and antibodies of an immune system) and anti-idiotypes are represented by complementary bit strings of a given length d allowing for a number of mismatches (matching rules). In this model, the vertices of the hypercube in dimension d represent the potential repertoire of idiotypes. A random set of (with probability p) occupied vertices corresponds to the expressed repertoire of idiotypes at a given moment. Vertices of this set linked by the above matching rules build random clusters. We give a structural and statistical characterization of these clusters, or in other words of the architecture of the idiotypic network. Increasing the probability p one finds at a critical p a percolation transition where for the first time a large connected graph occurs with probability 1. Increasing p further, there is a second transition above which the repertoire is complete in the sense that any newly introduced idiotype finds a complementary anti-idiotype. We introduce structural characteristics such as the mass distribution and the fragmentation rate for random clusters, and determine the scaling behavior of the cluster size distribution near the percolation transition, including finite size corrections. We find that slightly above the percolation transition the large connected cluster (the central part of the idiotypic network) consists typically of one highly connected part and a number of weakly connected constituents and coexists with a number of small, isolated clusters. This is in accordance with the picture of a central and a peripheral part of the idiotypic network and gives some support to idealized architectures of the central part used in recent dynamical mean field models.

Animals↗
PubMed1994

Central immune system, the self and autoimmunity.

We model how auto-reactive B cells are kept under control by an idiotypic network. Autoimmunity occurs when the control is broken by an infection or not achieved through an abnormal ontogenetic evolution. We describe the idiotypic network, viz., the central immune system, by idiotype-anti-idiotype pairs which are coupled to a set of highly connected clones, which interact with each clone of the network. Some clones of the central immune system recognize self-antigen. We find a huge variety of fixed points which can be classified as tolerant, autoimmune, and neutral states according to the concentration of the auto-reactive antibody. Most significant are auto-reactive clones which are a member of an idiotype-anti-idiotype pair. In a healthy individual, an autoimmune disease is induced by an antigen infection which triggers a transition from a tolerant to an autoimmune state. Autoimmunity is induced more readily by an antigen coupling to the anti-idiotype than by one interacting with the auto-reactive clone itself. We indicate a possible therapy which simply reverses the processes that have lead to the autoimmune disease. In the early development of the central immune system its highly connected, core part serves to draw the more specific clones of idiotype-anti-idiotype pairs into the network. In order to avoid autoimmunity in ontogenetic evolution the anti-idiotype of an auto-reactive clone must be formed in advance by a sufficiently long period of time. Thus, a well ordered succession of the appearance of the more specific clones is required.

Animals↗
PubMed1993

Memory to antigenic challenge of the immune system: synergy of idiotypic interactions and memory B cells.

Memory to antigenic challenge of the immune system is described as a synergy of two components: cycles of interacting B cells in a dynamic equilibrium which store an internal image of an antigen, and long-lived memory B cells which stabilize the cycle that generates them. Small cycles are most relevant to the immune system's memory. The network is globally stable and supports Jerne's idea that suppression is important. Our model allows for exponential increase of antigens during the initial stage of infection. It has a number of stable fixed points, viz the virgin state, the healthy immunized state, and a state of chronic infection, the last occurring if the antigen is virulent enough. Numerical simulations show a difference between primary and secondary response and exhibit both predator-prey and intracycle oscillations. In the case of a chronic infection, the simulations suggest a specific stimulation therapy triggered by repeatedly injecting the antigens, thus making the infection acute. An optimal therapy is indicated.

Antigens↗
PubMed1993

Memory in idiotypic networks due to competition between proliferation and differentiation.

A model employing separate dose-dependent response functions for proliferation and differentiation of idiotypically interacting B cell clones is presented. For each clone the population dynamics of proliferating B cells, non-proliferating B cells and free antibodies are considered. An effective response function, which contains the total impact of proliferation and differentiation at the fixed points, is defined in order to enable an exact analysis. The analysis of the memory states is restricted in this paper to a two-species system. The conditions for the existence of locally stable steady states with expanded B cell and antibody populations are established for various combinations of different field-response functions (e.g. linear, saturation, log-bell functions). The stable fixed points are interpreted as memory states in terms of immunity and tolerance. It is proven that a combination of linear response functions for both proliferation and differentiation does not give rise to stable fixed points. However, due to competition between proliferation and differentiation saturation response functions are sufficient to obtain two memory states, provided proliferation precedes differentiation and also saturates earlier. The use of log-bell-shaped response functions for both proliferation and differentiation gives rise to a "mexican-hat" effective response function and allows for multiple (four to six) memory states. Both a primary response and a much more pronounced secondary response are observed. The stability of the memory states is studied as a function of the parameters of the model. The attractors lose their stability when the mean residence time of antibodies in the system is much longer than the B cells' lifetime. Neither the stability results nor the dynamics are qualitatively changed by the existence of non-proliferating B cells: memory states can exist and be stable without non-proliferating B cells. Nevertheless, the activation of non-proliferating B cells and the competition between proliferation and differentiation enlarge the parameter regime for which stable attractors are found. In addition, it is shown that a separate activation step from virgin to active B cells renders the virgin state stable for any choice of biologically reasonable parameters.

Animals↗
PubMedDate not supplied

Structural characterization of canine PYY.

PYY was purified from canine colonic mucosa by sequential steps of reverse phase HPLC and ion-exchange FPLC. Microsequence, amino acid and mass spectral analyses of the purified peptide and its tryptic fragments were consistent with the structure: YPAKPEAPGEDASPEELSRYYASLRHYLNLVTRQRY-amide. Canine PYY(1-36) has the identical sequence as porcine and rat PYY but differs from human PYY at position 3, with Ala instead of Ile, and position 18, with Ser instead of Asn. A smaller form, PYY(3-36), was also purified and characterized. It may differ in its biological activity from the intact peptide and could act as a partial antagonist or agonist of PYY(1-36).

Amino Acid Sequence↗