Boutet de Monvel J H, Martin O C
Division de Physique Théorique, Unité de Recherche des Universités Paris, Cedex, France.
Bull Math Biol. 1995 Jan;57(1):109-36. doi: 10.1007/BF02458319.
Many models of immune networks have been proposed since the original work of Jerne [1974, Ann. Immun. (Inst. Pasteur)125C, 373-389]. Recently, a limited class of models (Weisbuch et al., 1990, J. theor. Biol 146, 483-499) have been shown to maintain immunological memory by idiotypic network interactions. We examine generalizations of these models when the networks are both large and highly connected to study their memory capacity, i.e., their ability to account for immunization to a large number of random antigens. Our calculations show that in these minimal models, random connectivities with continuously distributed affinities reduce the memory capacity to essentially nil.
自耶尔内1974年发表最初的研究成果（《巴斯德研究所年鉴·免疫学》125C卷，第373 - 389页）以来，人们提出了许多免疫网络模型。最近，一类有限的模型（韦斯布赫等人，1990年，《理论生物学杂志》第146卷，第483 - 499页）已被证明可通过独特型网络相互作用维持免疫记忆。当网络规模大且连接高度密集时，我们研究了这些模型的推广情况，以探究其记忆容量，即它们对大量随机抗原进行免疫的能力。我们的计算表明，在这些最简模型中，具有连续分布亲和力的随机连接会将记忆容量降低至基本为零。
