SUMMARYPurpose: Clinically, perturbations in the semaphorin signaling system have been associated with autism and epilepsy. The semaphorins have been implicated in guidance, migration, differentiation, and synaptic plasticity of neurons. The semaphorin 3F (Sema3F) ligand and its receptor, neuropilin 2 (NPN2) are highly expressed within limbic areas. NPN2 signaling may intimately direct the apposition of presynaptic and postsynaptic locations, facilitating the development and maturity of hippocampal synaptic function. To further understand the role of NPN2 signaling in central nevous system (CNS) plasticity, structural and functional alterations were assessed in NPN2 deficient mice. Methods: In NPN2 deficient mice, we measured seizure susceptibility after kainic acid or pentylenetetrazol, neuronal excitability and synaptic throughput in slice preparations, principal and interneuron cell counts with immunocytochemical protocols, synaptosomal protein levels with immunoblots, and dendritic morphology with Golgi-staining.Results: NPN2 deficient mice had shorter seizure latencies, increased vulnerability to seizurerelated death, were more likely to develop spontaneous recurrent seizure activity after chemical challenge, and had an increased slope on input/ output curves. Principal cell counts were unchanged, but GABA, parvalbumin, and neuropeptide Y interneuron cell counts were significantly reduced. Synaptosomal NPN2 protein levels and total number of GABAergic synapses were decreased in a gene dose-dependent fashion. CA1 pyramidal cells showed reduced dendritic length and complexity, as well as an increased number of dendritic spines. Discussion: These data suggest the novel hypothesis that the Sema 3F signaling system's role in appropriate placement of subsets of hippocampal interneurons has critical downstream consequences for hippocampal function, resulting in a more seizure susceptible phenotype.

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KCM (KnowledgeCrunching Machine) is a highperformance back-end processor which, coupled to a UNIX' desk-top workstatrbn, provides a powerful and user-friendfy Prolog environment catering for both development and exewtbn of sbnificant Prolog applications. This paper gives a general ovem'ew of the architecture of KCM stressing some new features like a 64&t tagged architeoture, shallow backtracking and an original memory management unit. Some early benchmark results obtained on prototvpe machines are presented. They show that KCM, which runs at a peak speed of 833 Klips on fist concatenation, compares favorably with other dedicated Prolog machines and available commercial systems nmning on fast general purpose plOC8SSOrS.

KCM (Knowledge Crunching Machine) is a high performance back-end processor which, coupled t o a UNIX desktop workstation, provides a powerful and user-friendly Prolog environment catering for both the development and execution of significant Prolog appIications. This paper first gives a short overview of the architecture of KCM. Then the benefits of the main hardware design choices are quantified, using statistics and simulations, in order to make a detailed evaluation.

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