Engineering topics

Park, Sang Hyun

Publications and source records attributed to Park, Sang Hyun.

4 records

DOE OSTI2017

Epstein-Barr virus-encoded latent membrane protein 1 induces epithelial to mesenchymal transition by inducing V-set Ig domain containing 4 (VSIG4) expression via NF-kB in renal tubular epithelial HK-2 cells

The epithelial to mesenchymal transition (EMT), a hallmark of chronic kidney disease, is a key event in the conversion from tubular epithelial cells to myofibroblasts in renal fibrosis. Epstein-Barr virus (EBV) is a γ-herpes oncovirus associated with chronic kidney disease. However, the relationship between EBV and the EMT process in renal tubular epithelial cells is not well understood. Among EBV-latent genes, EBV-encoded latent membrane protein 1 (LMP1) induces EMT by regulating a variety of molecules in EBV-induced oncogenic transformation. In this study, we investigated EBV-encoded LMP1 and EMT process markers in human proximal tubule epithelial cell line HK-2. LMP1 overexpression induces cell morphological changes via the epithelial to mesenchymal process in HK-2 cells, and these changes accelerate cell proliferation, cell motility, and invasion. Furthermore, VSIG4 upregulation by EBV-LMP1 induced LMP1-mediated EMT, cell motility, and invasion. VSIG4 upregulation by LMP1 was regulated at the transcriptional level via the NF-kB signaling axis. These results suggest that EBV-encoded LMP1 regulates EMT through the NF-kB-VSIG4 axis in HK-2 cells, and VSIG4 is a potential target in EBV-induced chronic kidney diseases. - Highlights: • Epstein Barr virus-encoded LMP1 overexpression induces epithelial to mesenchymal transition in renal epithelial HK-2 cells. • Upregulation of VISG4 expression by EBV-LMP1 plays an important role in LMP1-induced EMT process in HK-2 cells. • VSIG4 upregulation by EBV-LMP1 is regulated at transcriptional level via LMP1-induced NF-kB activation. • The interruption of VSIG4 expression could be a potential strategy for treatment of EBV-infected renal diseases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Current Status of Human Resource Training Program for Fostering RIBiomics Professionals

RI-Biomics is a state-of-the-art radiation fusion technology for evaluating in-vivo dynamics such as absorption, distribution, metabolism and excretion (ADME) of new drug candidates and biomaterials using radioisotope (RI), and quantitative evaluation of their efficacy via molecular imaging techniques and animal models. The RI-Biomics center is the sole comprehensive research and experiment complex in Korea that can simultaneously perform the radio-synthesis of drug candidate with radioisotope, analysis, and molecular imaging evaluation with animal model. Molecular imaging techniques, including nuclear imaging (SPECT and PET), near-infrared fluorescent (NIRF) imaging, and magnetic resonance imaging (MRI), are the cutting-edge technologies for evaluating drug candidates. Since they allow in vivo real-time imaging of the diseased site, monitoring the biodistribution of drug and determining the optimal therapeutic efficacy following treatments, we have integrated RI-ADME and molecular imaging to provide useful information for drug evaluation and to accelerate the development of new drugs and biomaterials. The RI-Biomics center was established with total investment of 18 million $ during four years from 2009 to 2012 in order to develop a comprehensive analyzing system using RI for new drug development as an axis for national growth in the next generation. The RI-Biomics center has labeling synthesis facility for the radiosynthesis of drug candidate with radioisotope such as Tc-99m, I-125, I-131, F-18, H-3 and C-14 using hot cell. It also includes RI-general analysis facilities, such as Radio-HPLC, LC/MS, GC/MS, gamma counter that can analyzing the radio-synthesized materials, and animal image analysis facilities that developed small animal imaging equipment such as SPECT/PET/CT, 7 T MRI, in-vivo optical imaging system and others. In order to achieve the system to verify safety and effectiveness of the new drugs using RI, it is necessary to establish a human resource training program for fostering RI-Biomics professionals in the following key fields; (1) Radio-pharmaceuticals synthesis and labeled compound development, (2) Development of RI-ADME in the living object and image assessment technology. Personnel training program that carries out theoretical education and practical training in the field related to RI-Biomics in parallel is being conducted. Internship training for university students has been administered twice already while educational program for the existing professionals in the RI-Biomics field will be carried out during the summer of 2014. The human resource training program for combination of RIADME and different molecular imaging techniques can offer synergistic advantages to facilitate understanding RIADME and fostering RI-ADME professionals. (authors)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

An Efficient and Straightforward Method for Radiolabeling of Nanoparticles with {sup 64}Cu via Click Chemistry

Recently, nanoparticles have received a great deal of interest in diagnosis and therapy applications. Since nanoparticles possess intrinsic features that are often required for a drug delivery system and diagnosis, they have potential to be used as platforms for integrating imaging and therapeutic functions, simultaneously. Intrinsic issues that are associated with theranostic nanoparticles, particularly in cancer treatment, include an efficient and straightforward radiolabeling method for understanding the in vivo biodistribution of nanoparticles to reach the tumor region, and monitoring therapeutic responses. Herein, we investigated a facile and highly efficient strategy to prepare radiolabeled nanoparticles with {sup 64}Cu via a strain-promoted azide, i.e., an alkyne cycloaddition strategy, which is often referred to as click chemistry. First, the azide (N3) group, which allows for the preparation of radiolabeled nanoparticles by copper-free click chemistry, was incorporated into glycol chitosan nanoparticles (CNPs). Second, the strained cyclooctyne derivative, dibenzyl cyclooctyne (DBCO) conjugated with a 1,4,7,10-tetraazacyclododecane- 1,4,7,10-tetraacetic acid (DOTA) chelator, was synthesized for preparing the pre-radiolabeled alkyne complex with {sup 64}Cu radionuclide. Following incubation with the {sup 64}Cu-radiolabeled DBCO complex (DBCO-PEG4-Lys-DOTA-{sup 64}Cu with high specific activity, 18.5 GBq/μ mol), the azide-functionalized CNPs were radiolabeled successfully with {sup 64}Cu, with a high radiolabeling efficiency and a high radiolabeling yield (>98%). Importantly, the radiolabeling of CNPs by copper-free click chemistry was accomplished within 30 min, with great efficiency in aqueous conditions. After {sup 64}Cu-CNPs were intravenously administered to tumor-bearing mice, the real time, in vivo biodistribution and tumor-targeting ability of {sup 64}Cu-CNPs were quantitatively evaluated by micro-PET images of tumor-bearing mice. These results demonstrate the benefit of copper-free click chemistry as a facile, pre-radiolabeling approach to Medical sciences conveniently radiolabel nanoparticles for evaluating the real-time in vivo biodistribution of nanoparticles. (authors)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.

07 ISOTOPE AND RADIATION SOURCES↗