NEURONAL INNERVATION, INTRACELLULAR SIGNAL-TRANSDUCTION AND INTERCELLULAR COUPLING - A MODEL FOR SYNCYTIAL TISSUE RESPONSES IN THE STEADY-STATE

A model tissue is proposed in which chemically responsive cells are in terconnected by gap junctions and innervated by the autonomic nervous system. The model is explicitly dependent on the following physiologic ally relevant assumptions: (1) a fraction of the cells are directly in nervated, and these cells respond to a periodic neuronal stimulus (i.e . the release of neurotransmitter) by production of an intracellular s ubstance (i.e. second messenger molecule); (2) production of second me ssenger molecules modulates the amplitude of a cellular response, such as contraction or secretion; (3) intracellular formation of second me ssenger molecules in innervated cells is proportional to the periodici ty of the neuronal stimulus, while the intracellular concentration in non-innervated cells is governed by the half-life of the second messen ger molecule and the extent of cell-to-cell coupling; (4) the amplitud e of the graded response of the individual cell is related to the intr acellular second messenger concentration by a Michaelis-Menten functio n; (5) the amplitude of the graded tissue response is a function of th e innervation density, the frequency of stimulation, and the extent of intercellular coupling. Thus, a stimulus-response relationship was de veloped, where the; magnitude of the tissue response was described as a function of the total tissue stimulus. The predicted stimulus-respon se curve was encapsulated by two parameters: (1) the Hill-exponent, wh ich reflects the steepness of the stimulus-response curve; and (2) the location of the stimulus-response curve, or the half-maximally effect ive stimulus. Both random and uniform neuronal innervation patterns we re considered in model tissues with various effective dimensions. The simulations were also applied to a realistic model of vascular tissue. The shape of the stimulus-response curve is critically dependent on t he geometry of innervation. For physiologically relevant (10-90% over 2-3 orders of magnitude) dose-response curves, the model yields an imp licit relationship between three different dimensionless parameters. I f, in a system, two of these parameters are known, the model can be us ed to bracket the possible range of the third parameter. (C) 1998 Acad emic Press.