• Animal Bioscience
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• v.37 no.2
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• pp.193-202
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• 2024

Objective: Oxidative stress (OS) is a pathological process arising from the excessive production of free radicals in the body. It has the potential to alter animal gene expression and cause damage to the jejunum. However, there have been few reports of changes in the expression of long noncoding RNAs (lncRNAs) in the jejunum in piglets under OS. The purpose of this research was to examine how lncRNAs in piglet jejunum change under OS. Methods: The abdominal cavities of piglets were injected with diquat (DQ) to produce OS. Raw reads were downloaded from the SRA database. RNA-seq was utilized to study the expression of lncRNAs in piglets under OS. Additionally, six randomly selected lncRNAs were verified using quantitative real-time polymerase chain reaction (qRT-PCR) to examine the mechanism of oxidative damage. Results: A total of 79 lncRNAs were differentially expressed (DE) in the treatment group compared to the negative control group. The target genes of DE lncRNAs were enriched in gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathways. Chemical carcinogenesis-reactive oxygen species, the Foxo signaling pathway, colorectal cancer, and the AMPK signaling pathway were all linked to OS. Conclusion: Our results demonstrated that DQ-induced OS causes differential expression of lncRNAs, laying the groundwork for future research into the processes involved in the jejunum's response to OS.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

• Journal of Life Science
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• v.31 no.2
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• pp.219-222
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• 2021

In this study, we examined low molecular weight peptides using proteomics in order to identify their original proteins, derive their peptides, and determine the functions of the proteins in Tenebrio molitor, the mealworm (larvae, pupae, or adult) from which the peptides were extracted. Fifty-four proteins were finally identified through an analysis of proteome to derive the analyzed peptides. The proteins that induced low molecular weight peptides were identified to be the most abundant in adults only, and the next highest were derived from a group containing both adults and larva. However, other groups, including pupa, were detected to have a lower frequency of peptides. As a result of orthologous classification of the detected proteins, the general function prediction was only investigated at the highest frequency among the examined proteins. Proteins related to chromatin structure and dynamics were detected by their higher frequency among functional classes. The next highest frequency was shown by proteins related to amino acid transport and metabolism and carbohydrate transport and metabolism. Therefore, it is assumed that proteins correlated with chromatin, amino acid, and carbohydrate metabolisms are easily induced into low molecular weight peptides, and that their peptides could play a role as bioactive substances.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of the Korean Society of Radiology
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• v.8 no.3
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• pp.123-136
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• 2014

In this paper, we study to classify molecular imaging and applications to predict future. Molecular imaging in vivo at the cellular level and the molecular level changes taking place to be imaged, that is molecular cell biology and imaging technology combined with the development of the new field. Molecular imaging is used fluorescence, bioluminescence, SPECT, PET, MRI, Ultrasound and other imaging technologies. That is applied to monitoring of gene therapy, cell tracking and monitoring of cell therapy, antibody imaging, drug development, molecular interaction picture, the near-infrared fluorescence imaging of cancer using fluorescence, bacteria using tumor-targeting imaging, therapeutic early assessment, prediction and therapy. The future of molecular imaging would be developed through fused interdisciplinary research and mutual cooperation, which molecular cell biology, genetics, chemistry, physics, computer science, biomedical engineering, nuclear medicine, radiology, clinical medicine, etc. The advent of molecular imaging will be possible to early diagnosis and personalized treatment of disease in the future.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.191-194
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• 2012

We conducted a case-control study in China to clarify the association between XRCC1-Arg399Gln polymorphism and HCC risk. A total of 150 cases and 158 controls were selected from the the Affiliated Hospital of Qingdao University from May 2008 to May 2010. XRCC1-Arg399Gln polymorphism was based upon duplex polymerase-chain-reaction with the confronting-two-pairprimer (PCR-CTPP) method. All analyses were performed using the STATA statistical package. A significantly increased risk was associated with the Arg/Gln genotype (adjusted OR 1.78, 95%CI=1.13-2.79) compared with genotype Arg/Arg. In contrast, the Gln/Gln genotype had non-significant increased risk of HCC with adjusted OR (95%CI) of 1.69 (0.93-2.66). A significant association was found between positive HBsAg and Arg/Gln, with an OR of 3.43 (95% CI=1.45-8.13). Patients carrying Gln/Gln genotypes showed significantly lower median survival than Arg/Arg genotypes (HR=1.38, 95% CI=1.04-1.84). Further Kaplan-Meier analysis showed decreased median survival in Arg/Gln+Gln/Gln genotype carriers in comparison to Arg/Arg carriers (HR=1.33, 95% CI=1.02-1.76). In conclusion, we observed that XRCC1-Arg399Cln polymorphism is associated with susceptibility to HCC, and XRCC1 Gln allele genotype showed significant prognostic associations.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3751-3755
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• 2013

Backgroud and Aims: MicroRNA-206 has proven to be down-regulated in many human malignancies in correlation with tumour progression. Our study aimed to characterize miR-206 contributions to initiation and malignant progression of human osteosarcoma. Methods: MiR-206 expression was detected in human osteosarcoma cell 1ine MG63, human normal osteoblastic cell line hFOB 1.19, and paired osteosarcoma and normal adjacent tissues from 65 patients using quantitative RT-PCR. Relationships of miR-206 levels to clinicopathological characteristics were also investigated. Moreover, miR-206 mimics and negative control siRNA were transfected into MG63 cells to observe effects on cell viability, apoptosis, invasion and migration. Results: We found that miR-206 was down-regulated in the osteosarcoma cell line MG63 and primary tumor samples, and decreased miR-206 expression was significantly associated with advanced clinical stage, T classification, metastasis and poor histological differentiation. Additionally, transfection of miR-206 mimics could reduce MG-63 cell viability, promote cell apoptosis, and inhibit cell invasion and migration. Conclusions: These findings indicate that miR-206 may have a key role in osteosarcoma pathogenesis and development. It could serve as a useful biomarker for prediction of osteosarcoma progression, and provide a potential target for gene therapy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.2032-2037
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• 2011

Marker genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect marker genes that are selected by ranking genes according to statistics after normalizing data with methods that are the most widely used among several normalization methods proposed the while, And it compare and analyze a performance of each of normalization methods with mult-perceptron neural network layer. The Result that apply Multi-Layer perceptron algorithm at Microarray data set including eight of marker gene that are selected using ANOVA method after Lowess normalization represent the highest classification accuracy of 99.32% and the lowest prediction error estimate.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.8
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• pp.719-727
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• 2008

A 3-D compressible Navier-Stokes solver using overlapped grids is developed to predict a flow-field around a hovering rotor. The flow solver is verified by a parametric study with the grid spacing of wake grid, spatial accuracy and turbulence model. Computations are performed with different Chimera grid systems. Computational results are compared with the experimental data of Caradonna et al. for both blade loading and the tip vortex behavior. Numerical results show good agreements with experiments for the distribution of surface pressure and tip vortex behavior. Pressure distributions over the blade have marginal differences for different numerical methods, whereas large discrepancies are seen in the prediction of the wake behavior. Results unexpectedly show that the vortex strength from an automated cut-paste Chimera grid is weaker than that from the conventional Chimera grid.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7187-7191
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• 2013

Most of the exogenous and endogenous chemical compounds are metabolized by enzymes of xenobiotic processing pathways, including the phase I cytochrome p450 species. Carcinogens and their metabolites are generally detoxified by phase II enzymes like glutathione-S-transferases (GST). The balance of enzymes determines whether metabolic activation of pro-carcinogens or inactivation of carcinogens occurs. Under certain conditions, deregulated expression of xenobiotic enzymes may also convert endogenous substrates to metabolites that can facilitate DNA adduct formation and ultimately lead to cancer development. In this study, we aimed to test the association between deregulation of metabolizing genes and brain tumorigenesis. The expression profile of metabolizing genes CYP1A1 and GSTP1 was therefore studied in a cohort of 36 brain tumor patients and controls using Western blotting. In a second part of the study we analyzed protein expression of GSTs in the same study cohort by ELISA. CYP1A1 expression was found to be significantly high (p<0.001) in brain tumor as compared to the normal tissues, with ~4 fold (OR=4, 95%CI=0.43-37) increase in some cases. In contrast, the expression of GSTP1 was found to be significantly low in brain tumor tissues as compared to the controls (p<0.02). This down regulation was significantly higher (OR=0.05, 95%CI=0.006-0.51; p<0.007) in certain grades of lesions. Furthermore, GSTs levels were significantly down-regulated (p<0.014) in brain tumor patients compared to controls. Statistically significant decrease in GST levels was observed in the more advanced lesions (III-IV, p<0.005) as compared to the early tissue grades (I-II). Thus, altered expression of these xenobiotic metabolizing genes may be involved in brain tumor development in Pakistani population. Investigation of expression of these genes may provide information not only for the prediction of individual cancer risk but also for the prevention of cancer.