• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.845-848
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• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.292-302
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• 2022

The radar tomographic imaging is based on the Radar Cross-Section "RCS" of the materials of a shape under examination and investigation. The RCS varies as the conductivity and permittivity of a target, where the target has a different material profile than other background objects in a scene. In this research paper, we use Hierarchical Performance Modeling "HPM" and a framework developed earlier to determine/spot bottleneck(s) for pattern recognition of materials using a combination of the Single Layer Perceptron (SLP) technique and tomographic images in radar systems. HPM provides mathematical equations which create Objective Functions "OFs" to find an average performance metric such as throughput or response time. Herein, response time is used as the performance metric and during the estimation of it, bottlenecks are found with the help of OFs. The obtained results indicate that processing images consumes around 90% of the execution time.

• Journal of Pharmaceutical Investigation
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• v.30 no.3
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• pp.191-199
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• 2000

Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.

• Genomics & Informatics
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• v.20 no.2
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• pp.20.1-20.13
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• 2022

Recent studies have focused on the early detection of ovarian cancer (OC) using tumor materials by liquid biopsy. The mechanisms of microRNAs (miRNAs) to impact OC and signaling pathways are still unknown. This study aims to reliably perform functional analysis of previously validated circulating miRNAs' target genes by using pathfindR. Also, overall survival and pathological stage analyses were evaluated with miRNAs' target genes which are common in the The Cancer Genome Atlas and GTEx datasets. Our previous studies have validated three downregulated miRNAs (hsa-miR-885-5p, hsa-miR-1909-5p, and hsa-let7d-3p) having a diagnostic value in OC patients' sera, with high-throughput techniques. The predicted target genes of these miRNAs were retrieved from the miRDB database (v6.0). Active-subnetwork-oriented Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by pathfindR using the target genes. Enrichment of KEGG pathways assessed by the analysis of pathfindR indicated that 24 pathways were related to the target genes. Ubiquitin-mediated proteolysis, spliceosome and Notch signaling pathway were the top three pathways with the lowest p-values (p < 0.001). Ninety-three common genes were found to be differentially expressed (p < 0.05) in the datasets. No significant genes were found to be significant in the analysis of overall survival analyses, but 24 genes were found to be significant with pathological stages analysis (p < 0.05). The findings of our study provide in-silico evidence that validated circulating miRNAs' target genes and enriched pathways are related to OC and have potential roles in theranostics applications. Further experimental investigations are required to validate our results which will ultimately provide a new perspective for translational applications in OC management.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7547-7552
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• 2014

The mir-155 family is not only involved in a diversity of cancers, but also as a regulator of the immune system. However, the evolutionary history of this family is still unclear. The present study indicates that mir-155 evolved independently with lineage-specific gain of miRNAs. In addition, arm switching has occurred in the mir-155 family, and alternative splicing could produce two different lengths of ancestral sequences, implying the alternative splicing can also drive evolution for intragenic miRNAs. Here we screened validated target genes and immunity-related proteins, followed by analyzation of the mir-155 family function by high-throughput methods like the gene ontology (GO) and Kyoto Eneyclopedin of Genes and Genemes (KEGG) pathway enrichment analysis. The high-throughput analysis showed that the CCND1 and EGFR genes were outstanding in being significantly enriched, and the target genes cebpb and VCAM1 and the protein SMAD2 were also vital in mir-155-related immune reponse activities. Therefore, we conclude that the mir-155 family is highly conserved in evolution, and CCND1 and EGFR genes might be potential targets of mir-155 with regard to progress of cancers, while the cebpb and VCAM1 genes and the protein SMAD2 might be key factors in the mir-155 regulated immune activities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.2967-2981
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• 2014

Device-to-Device (D2D) communication is a technology component for long-term evolution-advanced (LTE-A). In D2D communication, users in close proximity to each other can communicate directly without going through a base station; such direct communication can improve spectral efficiency. Although D2D communication brings improvement in spectral efficiency, it also causes interference to the cellular network as a result of spectrum sharing. In particularly, D2D communication can generate interference for each D2D pair when the common wireless medium in a co-located limited area is accessed. Even though the interference management for between the D2D pair and cellular networks has been proposed, the interference reducing methods have still not been fully studied for the D2D pairs. In this paper, we investigate the problem of D2D pair coexistence in which interference is considered between D2D pairs. Using a signal to interference model for a target D2D pair, we provide an analysis of the aggregated throughput of a dense D2D network. For a target D2D pair, we assume that the desired signal and interference signals obey multipath fading and shadow fading. Through analysis, we demonstrate the effect of cluster size such as the number of D2D pairs and the size of the considered area on the network performance. The analytical results are compared with computer simulations. Our work can be used for a rough guideline for controlling the system throughput in a dense D2D network environment.

• Journal of Microbiology and Biotechnology
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• v.33 no.3
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• pp.329-338
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• 2023

Enterohemorrhagic Escherichia coli (EHEC) is a foodborne pathogen that produces attaching and effacing lesions on the large intestine and causes hemorrhagic colitis. It is primarily transmitted through the consumption of contaminated meat or fresh produce. Similar to other bacterial pathogens, antibiotic resistance is of concern for EHEC. Furthermore, since the production of Shiga toxin by this pathogen is enhanced after antibiotic treatment, alternative agents that control EHEC are necessary. This study aimed to discover alternative treatments that target virulence factors and reduce EHEC toxicity. The locus of enterocyte effacement (LEE) is essential for EHEC attachment to host cells and virulence, and most of the LEE genes are positively regulated by the transcriptional regulator, Ler. GrlA protein, a transcriptional activator of ler, is thus a potential target for virulence inhibitors of EHEC. To identify the GrlA inhibitors, an in vivo high-throughput screening (HTS) system consisting of a GrlA-expressing plasmid and a reporter plasmid was constructed. Since the reporter luminescence gene was fused to the ler promoter, the bioluminescence would decrease if inhibitors affected the GrlA. By screening 8,201 compounds from the Korea Chemical Bank, we identified a novel GrlA inhibitor named Grlactin [3-[(2,4-dichlorophenoxy)methyl]-4-(3-methylbut-2-en-1-yl)-4,5-dihydro-1,2,4-oxadiazol-5-one], which suppresses the expression of LEE genes. Grlactin significantly diminished the adhesion of EHEC strain EDL933 to human epithelial cells without inhibiting bacterial growth. These findings suggest that the developed screening system was effective at identifying GrlA inhibitors, and Grlactin has potential for use as a novel anti-adhesion agent for EHEC while reducing the incidence of resistance.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3681-3685
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• 2012

Background: In breast cancer, estrogen receptors have been demonstrated to interact with transcription factors to regulate target gene expression. However, high-throughput identification of the transcription regulation relationship between transcription factors and their target genes in response to estradiol is still in its infancy. Purpose: Thus, the objective of our study was to interpret the transcription regulation network of MCF7 breast cancer cells exposed to estradiol. Methods: In this work, GSE11352 microarray data were used to identify differentially expressed genes (DEGs). Results: Our results showed that the MYB (v-myb myeloblastosis viral oncogene homolog [avian]), PGR (progesterone receptor), and MYC (v-myc myelocytomatosis viral oncogene homolog [avian]) were hub nodes in our transcriptome network, which may interact with ER and, in turn, regulate target gene expression. MYB can up-regulate MCM3 (minichromosome maintenance 3) and MCM7 expression; PGR can suppress BCL2 (B-cell lymphoma 2) expression; MYC can inhibit TGFB2 (transforming growth factor, beta 2) expression. These genes are associated with breast cancer progression via cell cycling and the $TGF{\beta}$ signaling pathway. Conclusion: Analysis of transcriptional regulation may provide a better understanding of molecular mechanisms and clues to potential therapeutic targets in the treatment of breast cancer.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.429-447
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• 2020

The considered simulation tasks are based on an electrometallurgical process development strategy and associated telemanipulator simulation systems are proposed with various scales of experimental facilities. Fundamentally, target facilities are assumed to be operated only by remote handling systems because the considered process is operated in hazardous environments. Futhermore, the feasibility at various scales should be experimentally verified with gradual increase in throughput. In this regard, bench, engineering, and pilot-scale simulation systems are important early-stage tools for assessing the practical operability of the target process with the material handling systems. Such simulation systems are highly customized for applications and are a precursor to larger pilot and demonstration-scale plants. This paper introduced and classified the developed simulator systems for this approach at various scales using remote handling systems which were assembled inside a virtual target facility, and the manmachine interface was included for a more realistic operation of the simulator. The results obtained for each simulator show the feasibility and requirement for improvement of the systems for the considered test issues with respect to the operation and maintenance of the process.

• BMB Reports
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• v.55 no.9
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• pp.417-428
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• 2022

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network-based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound-target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in high-throughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data.