Takuya Kurihara

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DARPP-32, a dopamine- and adenosine 3':5'-monophosphate regulated neuronal phosphoprotein, Mr 32 kDa, is a phenotypic marker of the medium-size spiny neurons of the mammalian caudate-putamen. In the present study, we examined the ontogeny of DARPP-32 protein and mRNA, and compared it to the ontogeny of tyrosine hydroxylase and synapsin I, a synaptic-vesicle(More)
DARPP-32, a substrate for cyclic AMP-dependent protein kinase, is highly enriched in the caudate nucleus. In the present study, the cDNA for rat DARPP-32 was isolated and characterized. When compared to the coding region of bovine DARPP-32 cDNA, there was 86% identity at the nucleotide level, and 84% identity at the amino acid level. The homology in the(More)
In situ hybridization histochemistry has been used to determine the regional distribution and cellular localization of DARPP-32 mRNA in the rat brain. Results support the concept that DARPP-32 is present primarily in cells expressing the dopamine D1 subtype receptor, and that DARPP-32 is not synthesized in dopamine-containing cells. Strongly labelled(More)
A cDNA clone for the mRNA of bovine DARPP-32 (dopamine- and adenosine 3',5'-monophosphate-regulated phosphoprotein, Mr = 32,000) was isolated from a modified Okayama-Berg plasmid library. Transformed Escherichia coli colonies were screened by in situ colony hybridization with 2 different oligonucleotide probes corresponding to a region unusually rich in(More)
A cDNA clone for the mRNA of bovine ARPP-21 (cAMP-regulated phosphoprotein, Mr = 21,000 as determined by SDS-PAGE) was isolated from a modified Okayama-Berg plasmid library. Transformed Escherichia coli colonies were screened by in situ colony hybridization with 2 different oligonucleotide probes derived from the amino acid sequence of the bovine protein.(More)
—This article analyzes the convergence property of the particle swarm optimization and its application to the nonlinear blind source separation system. The inter-particle communication of the particle swarm optimization is realized by the past history of the neighbors and depends on the network structure of the swarm. We focus on an average path length of(More)