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A novel gene Jpk (Jopock) has been originally isolated through yeast 1 hybridization technique as a trans-acting factor interacting with the position-specific regulatory element of a murine Hoxa-7. Northern analysis revealed that the Jpk was expressed at day 7.0 post coitum (p.c.) during early gastrulation. Previously it has been shown that a trace amount of JPK protein led bacterial cells to death. In eukaryotic F9 cells, Jpk also led the cell to death-generating DNA ladder: fewer than 50% of the cells survived after 72-h transfection. Flow cytometric analysis with cells stained with each Annexin V/7-amino-actinomycin D (7-AAD), MitoTracker, and hydroethidine (HE) revealed that Jpk induced apoptotic cell death in a time-dependent manner, reduced mitochondrial membrane potential, and increased ROS (reactive oxygen species) production, respectively. Additionally, Jpk seemed to regulate the Bcl family at the transcriptional level when RT-PCR was performed. Although the precise mechanism is not clear, these results altogether suggest that Jpk is a potent inducer of apoptosis through generation of ROS as well as concomitant reduction of mitochondrial membrane potential.

Currently, the two primary patient-derived xenograft (PDX) models of glioblastoma are established through intracranial or subcutaneous injection. In this study, a novel PDX model of glioblastoma was developed via intravitreal injection to facilitate tumor formation in a brain-mimicking microenvironment with improved visibility and fast development. Glioblastoma cells were prepared from the primary and recurrent tumor tissues of a 39-year-old female patient. To demonstrate the feasibility of intracranial tumor formation, U-87 MG and patient-derived glioblastoma cells were injected into the brain parenchyma of Balb/c nude mice. Unlike the U-87 MG cells, the patient-derived glioblastoma cells failed to form intracranial tumors until 6 weeks after tumor cell injection. In contrast, the patient-derived cells effectively formed intraocular tumors, progressing from plaques at 2 weeks to masses at 4 weeks after intravitreal injection. The in vivo tumors exhibited the same immunopositivity for human mitochondria, GFAP, vimentin, and nestin as the original tumors in the patient. Furthermore, cells isolated from the in vivo tumors also demonstrated morphology similar to that of their parental cells and immunopositivity for the same markers. Overall, a novel PDX model of glioblastoma was established via the intravitreal injection of tumor cells. This model will be an essential tool to investigate and develop novel therapeutic alternatives for the treatment of glioblastoma.

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SummaryLast-mile bottleneck, fire-wall bottleneck, and internal network congestion bottleneck are well-known performance bottleneck problems of private sector in national R&E network since Internet is adopted for R&E network. The emergency of big data science makes these problems more severe because a famous scientist under such a circumstance is severely restricted in his/her big data R&D. Therefore, government cannot leave these stubs in the realm of a private organization any longer. We, KREONET (Korea Research Environment Open Network), tried to solve these problems by SDN-IP (software-defined network-Internet protocol) based on ONOS (Open Network Operation System); SDN-IP is the leading technology for the softwarization of network, and it is developed by On Lab. KREONET began to deploy SDN-IP as a tool for the softwarization of Korea R&E network even though others studied to business its' feature for the enhancement of resource management of data center first. The initial goal during the construction of SDN-IP for KREONET is to solve well-known problems in R&E network, which are related with last-mile, fire-wall, and internal network congestion. These 3 problems are not solved for a long time because it costs too much when we try to solve them by the way of the existed hardware networking. In this paper, we introduce our experience that can catch two rabbits at the same time. These experiences are about the provision of the initial popular service of SDN-IP with the solution of those well-known bottleneck problems and about the economic way of SDN-IP construction by incremental hybrid networking of legacy Internet and SDN-IP. KEYWORDSphysical network separation, R&E network, software-defined network, SD WAN, SDN-IP INTRODUCTIONRecently, software-defined networking (SDN) 1 has emerged as a new paradigm for R&E network innovation. SDN is changing how to design, build, and operate R&E networks to achieve high availability from a scientist point of view. With the aid of SDN, R&E networks can be more open to scientists and easily controlled by user than before. SDN-based R&E network can be transformed into an open and programmable component of the larger science cloud infrastructure. SDN can give network users and operators more control of their infrastructure, more allowance of customization and optimization, and more reduction of the overall operational costs. Figure 1 illustrates SDN architecture that decouples the network control and forwarding functions and that enables the network control to become directly programmable. Figure 1 depicts the underlying infrastructure to be abstracted for applications and network services. The OpenFlow 2,3 protocol in Figure 1 is a foundational element for building SDN networks.OpenFlow is a communication protocol that gives access to the forwarding plane of a network switch or router over the network. 2 OpenFlow