Daeyoung Oh

Korea Advanced Institute of Science and Technology, Sŏul, Seoul, South Korea

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Publications (3)12.55 Total impact

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    ABSTRACT: Dendritic arborization is important for neuronal development as well as the formation of neural circuits. Rac1 is a member of the Rho GTPase family which serves as regulators of neuronal development. BCR (breakpoint cluster region) is a Rac1 GTPase-activating protein which is abundantly expressed in the central nervous system. Here we show that BCR plays a key role in neuronal development. Dendritic arborization and actin polymerization were attenuated by overexpression of BCR in hippocampal neurons. Knockdown of BCR using specific shRNAs increased the dendritic arborization as well as actin polymerization. The number of dendrites of null mutant BCR-/- mice was considerably increased compared with wild type. The function of the BCR GTPase-activating domain could be controlled by PTPRT (protein tyrosine phosphatase receptor T) expressed principally in the brain. We demonstrate that tyrosine 177 of BCR was the main target of PTPRT and the BCR mutant mimicking dephosphorylation of tyrosine 177 alleviated the attenuation of dendritic arborization. Additionally the attenuated dendritic arborization by BCR overexpression was relieved upon co-expression of PTPRT. When PTPRT was knocked down by specific shRNA, the dendritic arborization was significantly reduced. The function of the BCR GTPase-activating domain was controlled by means of conversions between the intra- and inter-molecular interactions that are finely regulated through the dephosphorylation of a specific tyrosine residue by PTPRT. We thus show conclusively that BCR is a novel substrate of PTPRT and that BCR is involved in the regulation of neuronal development via control of the BCR GTPase-activating domain function by PTPRT.
    Journal of Cell Science 07/2012; 125(19). DOI:10.1242/jcs.105502 · 5.43 Impact Factor
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    ABSTRACT: Rho family small GTPases are important regulators of neuronal development. Defective Rho regulation causes nervous system dysfunctions including mental retardation and Alzheimer's disease. Rac1, a member of the Rho family, regulates dendritic spines and excitatory synapses, but relatively little is known about how synaptic Rac1 is negatively regulated. Breakpoint cluster region (BCR) is a Rac GTPase-activating protein known to form a fusion protein with the c-Abl tyrosine kinase in Philadelphia chromosome-positive chronic myelogenous leukemia. Despite the fact that BCR mRNAs are abundantly expressed in the brain, the neural functions of BCR protein have remained obscure. We report here that BCR and its close relative active BCR-related (ABR) localize at excitatory synapses and directly interact with PSD-95, an abundant postsynaptic scaffolding protein. Mice deficient for BCR or ABR show enhanced basal Rac1 activity but only a small increase in spine density. Importantly, mice lacking BCR or ABR exhibit a marked decrease in the maintenance, but not induction, of long-term potentiation, and show impaired spatial and object recognition memory. These results suggest that BCR and ABR have novel roles in the regulation of synaptic Rac1 signaling, synaptic plasticity, and learning and memory, and that excessive Rac1 activity negatively affects synaptic and cognitive functions.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 10/2010; 30(42):14134-44. DOI:10.1523/JNEUROSCI.1711-10.2010 · 6.34 Impact Factor
  • Wonjun Kim · Jaeho Lee · Minjin Kim · Daeyoung Oh · Changick Kim ·
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    ABSTRACT: This paper presents a method for recognizing human actions from a single query action video. We propose an action recognition scheme based on the ordinal measure of accumulated motion, which is robust to variations of appearances. To this end, we first define the accumulated motion image (AMI) using image differences. Then the AMI of the query action video is resized to a N×Nsubimage by intensity averaging and a rank matrix is generated by ordering the sample values in the sub-image. By computing the distances from the rank matrix of the query action video to the rank matrices of all local windows in the target video, local windows close to the query action are detected as candidates. To find the best match among the candidates, their energy histograms, which are obtained by projecting AMI values in horizontal and vertical directions, respectively, are compared with those of the query action video. The proposed method does not require any preprocessing task such as learning and segmentation. To justify the efficiency and robustness of our approach, the experiments are conducted on various datasets.
    EURASIP journal on advances in signal processing 02/2010; 2010(12). DOI:10.1155/2010/219190 · 0.78 Impact Factor

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