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Che, Hui-Lian,Muthiah, Muthunarayanan,Ahn, Youngkeun,Son, Sejin,Kim, Won Jong,Seonwoo, Hoon,Chung, Jong Hoon,Cho, Chong-Su,Park, In-Kyu American Scientific Publishers 2011 Journal of Nanoscience and Nanotechnology Vol.11 No.8
<P>In this study, we present nanofiber-mediated gene delivery for myocardial infarction (MI). Branched polyethylenimine cross-linked via disulfide bonds (ssPEI) complexed with vascular endothelial growth factor (VEGF) were immobilized on electrospun polycaprolactone (PCL)/polyethylenimine (PEI) nanofibers for the local expression of VEGF angiogenic factor. We studied whether the production of VEGF from myoblast cells adhering on the nanofibers has therapeutic potential for MI. In this method, the non-specific adsorption of VEGF nanoparticles to the nanofibers occurred uniformly over all of the surface area of the nanofibers, resulting in increased transgene uptake and expression in a great number of cells. The amount of DNA required for transfection was also minimal compared to bolus delivery, because the adhered DNA was directly available in the cell microenvironment, which also helps in localized delivery. Reporter genes luciferase (Luc), red fluorescence protein (RFP), and therapeutic gene VEGF were tested to evaluate the transfection efficiency of ssPEI nanoparticles immobilized on the nanofiber surface. Our results demonstrated that the delivery of therapeutic genes from biodegradable nanoparticles immobilized on the nanofiber represented minimal cytotoxicity of H9C2 myoblasts than branched PEI 25 kDa did. According to Luc assay, fluorescence microscope analysis, and reverse transcription polymerase chain reaction (RT-PCR), this vector showed high transgene expression efficiency to the reporter gene and VEGF gene. The surface-mediated delivery of the DNA nanoparticles did not adversely affect cell growth, and facilitated the transgene expression inside the cells.</P>
Hui-Lian Che,In-Ho Bae,Kyung-Seob Lim,Saji Uthaman,In Taek Song,이해신,이두환,김원종,Young Keun Ahn,박인규,Myung Ho Jeong 대한심장학회 2016 Korean Circulation Journal Vol.46 No.1
Background and Objectives: MicroRNA 145 is known to be responsible for cellular proliferation, and its enhanced expression reportedly inhibits the retardation of vascular smooth muscle cell growth specifically. In this study, we developed a microRNA 145 nanoparticle immobilized, hyaluronic acid (HA)-coated stent. Materials and Methods: For the gene therapy, we used disulfide cross-linked low molecular polyethylenimine as the carrier. The microRNA 145 was labeled with YOYO-1 and the fluorescent microscopy images were obtained. The release of microRNA 145 from the stent was measured with an ultra violet spectrophotometer. The downstream targeting of the c-Myc protein and green fluorescent protein was determined by Western blotting. Finally, we deployed microRNA 145/ssPEI nanoparticles immobilized on HA-coated stents in the balloon- injured external iliac artery in a rabbit restenosis model. Results: Cellular viability of the nanoparticle-immobilized surface tested using A10 vascular smooth muscle cells showed that MSN exhibited negligible cytotoxicity. In addition, microRNA 145 and downstream signaling proteins were identified by western blots with smooth muscle cell (SMC) lysates from the transfected A10 cell, as the molecular mechanism for decreased SMC proliferation that results in the inhibition of in-stent restenosis. MicroRNA 145 released from the stent suppressed the growth of the smooth muscle at the peri- stent implantation area, resulting in the prevention of restenosis at the post-implantation. We investigated the qualitative analyses of in- stent restenosis in the rabbit model using micro-computed tomography imaging and histological staining. Conclusion: MicroRNA 145-eluting stent mitigated in-stent restenosis efficiently with no side effects and can be considered a successful substitute to the current drug-eluting stent.
Che, Hui-Je,Jung, Young-Jin,Lee, Seung-Hwan,Im, Chang-Hwan The Korean Society of Medical and Biological Engin 2010 의공학회지 Vol.31 No.1
Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.
Wang Hui-Ching,Moi Sin-Hua,Chan Leong-Perng,Wu Chun-Chieh,Du Jeng-Shiun,Liu Pei-Lin,Chou Meng-Chun,Wu Che-Wei,Huang Chih-Jen,Hsiao Hui-Hua,Pan Mei-Ren,Chen Li-Tzong 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-
Personalized genetic profiling has focused on improving treatment efficacy and predicting risk stratification by identifying mutated genes and selecting targeted agents according to genetic testing. Therefore, we evaluated the role of genetic profiling and tumor mutation burden (TMB) using next-generation sequencing in patients with head and neck squamous cell carcinoma (HNSC). The relapse mutation signature (RMS) and chromatin remodeling mutation signature (CRMS) were explored to predict the risk of relapse in patients with HNSC treated with concurrent chemoradiotherapy (CCRT) with platinum-based chemotherapy. Patients in the high RMS and CRMS groups showed significantly shorter relapse-free survival than those in the low RMS and CRMS groups, respectively (p < 0.001 and p = 0.006). Multivariate Cox regression analysis showed that extranodal extension, CCRT response, and three somatic mutation profiles (TMB, RMS, and CRMS) were independent risk predictors for HNSC relapse. The predictive nomogram showed satisfactory performance in predicting relapse-free survival in patients with HNSC treated with CCRT.
Hui-Fen Wu,Suresh Kumar Kailasa,Ja-Yi Yan,Chen-Che Chin,Hsin-Yi Ku 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.4
This paper describes the use of single-drop microextraction and micro-volume pipette extraction coupled with capillary electrophoresis for the analysis of five antidepressant drugs (nortriptyline, imipramine, trimeprazine, promethazine, and iminodibenzyl). The five antidepressant drugs are well separated by using micellar electrokinetic capillary chromatography with SDS and organic modifiers. The best extraction was achieved within 10 min and effectively separated within 15 min by using ammonium acetate buffer at 28 kV. This method shows good reproducibility, with RSD values ranging from 4.3 to 8.7%. The LODs values were found to be 0.4 and 1.0 mg mL-1 for SDME-CE and 0.15 and 0.5 mg mL-1 for MVPE-CE. These methods are simple, rapid, sensitive and efficient for the extraction, separation and detection of tricyclic antidepressant drugs.
Convolutional Neural Network Based Multi-feature Fusion for Non-rigid 3D Model Retrieval
( Hui Zeng ),( Yanrong Liu ),( Siqi Li ),( Jianyong Che ),( Xiuqing Wang ) 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.1
This paper presents a novel convolutional neural network based multi-feature fusion learning method for nonrigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.