• Biomolecules & Therapeutics
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• v.26 no.3
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• pp.290-297
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• 2018

We aimed to understand the molecular changes in host cells that accompany infection by the seasonal influenza A H1N1 virus because the initial response rapidly changes owing to the fact that the virus has a robust initial propagation phase. Human epithelial alveolar A549 cells were infected and total RNA was extracted at 30 min, 1 h, 2 h, 4 h, 8 h, 24 h, and 48 h post infection (h.p.i.). The differentially expressed host genes were clustered into two distinct sets of genes as the infection progressed over time. The patterns of expression were significantly different at the early stages of infection. One of the responses showed roles similar to those associated with the enrichment gene sets to known 'gp120 pathway in HIV.' This gene set contains genes known to play roles in preventing the progress of apoptosis, which infected cells undergo as a response to viral infection. The other gene set showed enrichment of 'Drug Metabolism Enzymes (DMEs).' The identification of two distinct gene sets indicates that the virus regulates the cell's mechanisms to create a favorable environment for its stable replication and protection of gene metabolites within 8 h.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.1-11
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• 2012

When the microarray experiment developed, main interest was limited to detect differentially expressed genes associated with a phenotype of interest. However, as human diseases are thought to occur through the interactions of multiple genes within a same functional category, the unit of analysis of the microarray experiment expanded to the set of genes. For the phenotype of censored survival time, Gene Set Enrichment Analysis(GSEA), Global test and Wald type test are widely used. In this paper, we modified the Wald type test by adopting normal score transformation of gene expression values and developed a parametric test which requires much less computation than others. The proposed method is compared with other methods using a real data set of ovarian cancer and a simulation data set.

• Journal of Periodontal and Implant Science
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• v.52 no.2
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• pp.127-140
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• 2022

Purpose: In dental avulsion, delayed replantation usually has an uncertain prognosis. After tooth replantation, complex inflammatory responses promote a return to periodontal tissue homeostasis. Various types of cytokines are produced in the inflammatory microenvironment, and these cytokines determine the periodontal tissue response. This study aimed to identify the gene expression profiles of replanted teeth and evaluate the functional differences between immediate and delayed replantation. Methods: Maxillary molars from Sprague-Dawley rats were extracted, exposed to a dry environment, and then replanted. The animals were divided into 2 groups according to the extra-oral time: immediate replantation (dry for 5 minutes) and delayed replantation (dry for 60 minutes). Either 3 or 7 days after replantation, the animals were sacrificed. Periodontal soft tissues were harvested for mRNA sequencing. Hallmark gene set enrichment analysis was performed to predict the function of gene-gene interactions. The normalized enrichment score (NES) was calculated to determine functional differences. Results: The hallmark gene sets enriched in delayed replantation at 3 days were oxidative phosphorylation (NES=2.82, Q<0.001) and tumor necrosis factor-alpha (TNF-α) signaling via the nuclear factor kappa light chain enhancer of activated B cells (NF-κB) pathway (NES=1.52, Q=0.034). At 7 days after delayed replantation, TNF-α signaling via the NF-κB pathway (NES=-1.82, Q=0.002), angiogenesis (NES=-1.66, Q=0.01), and the transforming growth factor-beta signaling pathway (NES=-1.46, Q=0.051) were negatively highlighted. Conclusions: Differentially expressed gene profiles were significantly different between immediate and delayed replantation. TNF-α signaling via the NF-κB pathway was marked during the healing process. However, the enrichment score of this pathway changed in a time-dependent manner between immediate and delayed replantation.

• Molecules and Cells
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• v.46 no.1
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• pp.65-67
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• 2023

SMILES (simplified molecular-input line-entry system) information of small molecules parsed by one-hot array is passed to a convolutional neural network called black box. Outputs data representing a gene signature is then matched to the genetic signature of a disease to predict the appropriate small molecule. Efficacy of the predicted small molecules is examined by in vivo animal models. GSEA, gene set enrichment analysis.

• Journal of Life Science
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• v.29 no.1
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• pp.105-111
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• 2019

In recent years, progress has been made in the search for the development of new anti-cancer agents by employing specific inhibitors of histone deacetylase (HDAC)-6 to block signal transduction pathways in cancer cells. This study examined the effects of tubastatin A (TubA), an HDAC-6 inhibitor, on the growth and development of immature oocytes in murine ovaries using RNA sequencing analysis. The results from a gene set enrichment analysis (GSEA) indicated that the expression of most of the gene sets involved in the cell cycle and control and progression of meiosis decreased in the TubA-treated group as compared with that in germinal vesicle (GV) stage oocytes. In addition, an ingenuity pathway analysis (IPA) suggested that TubA not only caused increased expression of p53 and pRB and decreased expression of CDK4/6 and cyclin D but also caused elevated expression of genes involved in the control of the DNA check point in G2/M stage oocytes. These results suggest that TubA may induce cell cycle arrest and apoptosis through the induction of changes in the expression of genes involved in signal transduction pathways associated with DNA damage and the cell cycle of immature oocytes in the ovary.

• The Korea Journal of Herbology
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• v.38 no.6
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• pp.73-91
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• 2023

Objectives : This study used a network pharmacology approach to elucidate the efficacy and molecular mechanisms of Daehwangmokdanpitang (DHMDPT) on Psoriasis. Methods : Using OASIS databases and PubChem database, compounds of DHMDPT and their target genes were collected. The putative target genes of DHMDPT and known target genes of psoriasis were compared and found the correlation. Then, the network was constructed using Cytoscape 3.10.1. The key target genes were screened by Analyzer network and their functional enrichment analysis was conducted based on the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results : The result showed that total 30 compounds and 439 related genes were gathered from DHMDPT. 264 genes were interacted with psoriasis gene set, suggesting that the effects of DHMDPT are closely related to psoriasis. Based on GO enrichment analysis and KEGG pathways, 'Binding', 'Cytokine Activity', 'Receptor Ligand Activity' 'HIF-1 signaling pathway', 'IL-17 signaling pathway', 'Toll-like receptor signaling pathway', and 'TNF signaling pathway' were predicted as functional pathways of 16 key target genes of DHMDPT on psoriasis. Among the target genes, IL6, IL1B, TNF, AKT1 showed high correlation with the results of KEGG pathways. Additionally, Emodin, Acetovanillone, Gallic acid, and Ferulic acid showed a high relevance with key genes and their mechanisms. Conclusion : Through a network pharmacological method, DHMDPT was predicted to have high relevance with psoriasis. This study could be used as a basis for studying therapeutic effects of DHMDPT on psoriasis.

• The Korea Journal of Herbology
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• v.38 no.1
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• pp.45-53
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• 2023

Objectives : Network pharmacology-based research is one of useful tool to predict the possible efficacy and molecular mechanisms of natural materials with multi compounds-multi targeting effects. In this study, we investigated the functional underlying mechanisms of Astragalus membranaceus Bunge (AM) on its anti-obesity effects using a network pharmacology analysis. Methods : The constituents of AM were collected from public databases and its target genes were gathered from PubChem database. The target genes of AM were compared with the gene set of obesity to find the correlation. Then, the network was constructed by Cytoscape 3.9.1. and functional enrichment analysis was conducted to predict the most relevant pathway of AM. Results : The result showed that AM network contained the 707 nodes and 6867 edges, and 525 intersecting genes were exhibited between AM and obesity gene set, indicating that high correlation with the effects of AM on obesity. Based on GO biological process and KEGG Pathway, 'Response to lipid', 'Cellular response to lipid', 'Lipid metabolic process', 'Regulation of chemokine production', 'Regulation of lipase activity', 'Chemokine signaling pathway', 'Regulation of lipolysis in adipocytes' and 'PPAR signaling pathway' were predicted as functional pathways of AM on obesity. Conclusions : AM showed high relevance with the lipid metabolism related with the chemokine production and lipolysis pathways. This study could be a basis that AM has promising effects on obesity via network pharmacology analysis.

• Toxicological Research
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• v.32 no.4
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• Journal of Ginseng Research
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• v.44 no.3
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• pp.519-526
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• 2020

Background: Bisphenol A (BPA), known as an endocrine disruptor, is widely used in the world. BPA is reported to cause inflammation-related diseases. Korean Red Ginseng (KRG) has been used safely in human for a long time for the treatment of diverse diseases. KRG has been reported of its mitigating effect on menopausal symptoms and suppress adipose inflammation. Here, we investigate the protective effect of orally administered KRG on the impacts of BPA in the liver and uterus of menopausal mice model. Methods: The transcriptome analysis for the effects of BPA on mice liver was evaluated by Gene Expression Omnibus (GEO) database-based data (GSE26728). In vivo assay to evaluate the protective effect of KRG on BPA impact in ovariectomized (OVX) mice were designed and analyzed by RNA sequencing. Results: We first demonstrated that BPA induced 12 kinds of gene set in the liver of normal mice. The administration of BPA and KRG did not change body, liver, and uterine weight in OVX mice. KRG downregulated BPA-induced inflammatory response and chemotaxis-related gene expression. Several gene set enrichment analysis (GSEA)-derived inflammatory response genes increased by BPA were inhibited by KRG in OVX mice. Conclusion: Our data suggest that BPA has commonly influenced inflammatory response effects on both normal and OVX mice. KRG protects against BPA impact of inflammatory response and chemotaxis in OVX mouse models. Our comparative analysis will provide new insight into the efficacy of KRG on endocrine disrupting chemicals and OVX mouse.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7221-7227
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• 2013

Background: Fascin, an actin-bundling protein forming actin bundles including filopodia and stress fibers, is overexpressed in multiple human epithelial cancers including esophageal squamous cell carcinoma (ESCC). Previously we conducted a microarray experiment to analyze fascin knockdown by RNAi in ESCC. Method: In this study, the differentially expressed genes from mRNA expression profilomg of fascin knockdown were analyzed by multiple bioinformatics methods for a comprehensive understanding of the role of fascin. Results: Gene Ontology enrichment found terms associated with cytoskeleton organization, including cell adhesion, actin filament binding and actin cytoskeleton, which might be related to fascin function. Except GO categories, the differentially expressed genes were annotated by 45 functional categories from the Functional Annotation Chart of DAVID. Subpathway analysis showed thirty-nine pathways were disturbed by the differentially expressed genes, providing more detailed information than traditional pathway enrichment analysis. Two subpathways derivated from regulation of the actin cytoskeleton were shown. Promoter analysis results indicated distinguishing sequence patterns and transcription factors in response to the co-expression of downregulated or upregulated differentially expressed genes. MNB1A, c-ETS, GATA2 and Prrx2 potentially regulate the transcription of the downregulated gene set, while Arnt-Ahr, ZNF42, Ubx and TCF11-MafG might co-regulate the upregulated genes. Conclusions: This multiple bioinformatic analysis helps provide a comprehensive understanding of the roles of fascin after its knockdown in ESCC.