• Molecules and Cells
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• v.24 no.2
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• pp.200-209
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• 2007

We generated gene expression data from the tissues of 50 gastric cancer patients, and applied meta-analysis and gene set analysis to this data and three other stomach cancer gene expression data sets to define the gene expression changes in gastric tumors. By meta-analysis we identified genes consistently changed in gastric carcinomas, while gene set analysis revealed consistently changed biological themes. Genes and gene sets involved in digestion, fatty acid metabolism, and ion transport were consistently down-regulated in gastric carcinomas, while those involved in cellular proliferation, cell cycle, and DNA replication were consistently up-regulated. We also found significant differences between the genes and gene sets expressed in diffuse and intestinal type gastric carcinoma. By gene set analysis of cytogenetic bands, we identified many chromosomal regions with possible gross chromosomal changes (amplifications or deletions). Similar analysis of transcription factor binding sites (TFBSs), revealed transcription factors that may have caused the observed gene expression changes in gastric carcinomas, and we confirmed the overexpression of one of these, E2F1, in many gastric carcinomas by tissue array and immunohistochemistry. We have incorporated the results of our meta- and gene set analyses into a web accessible database (http://human-genome.kribb.re.kr/stomach/).

• Bulletin of the Korean Chemical Society
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• v.32 no.1
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• pp.201-207
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• 2011

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the $PPAR\gamma$ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to $PPAR\gamma$ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.

• Journal of Society of Preventive Korean Medicine
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• v.21 no.2
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• pp.1-13
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• 2017

Objectives : This paper serves to explore current trends of systems biology in Traditional Chinese Medicine (TCM) and examine how it may influence the Traditional Korean medicine. Methods : Literature review method was collectively used to classify Introduction to systems biology, diagnosis and syndrome classification of systems biology in TCM perspective, physiotherapy including acupuncture, herbs and formula functions, TCM systems biology, and directions of academic development. Results : The term 'Systems biology' is coined as a combination of systems science and biology. It is a field of study that tries to understand living organism by establishing a theory based on an ideal model that analyzes and predicts the desired output with understanding of interrelationships and dynamics between variables. Systems biology has an integrated and multi-dimensional nature that observes the interaction among the elements constructing the network. The current state of systems biology in TCM is categorized into 4 parts: diagnosis and syndrome, physical therapy, herbs and formulas and academic development of TCM systems biology and its technology. Diagnosis and syndrome field is focusing on developing TCM into personalized medicine by clarifying Kidney yin deficiency patterns and metabolic differences among five patterns of diabetes and analyzing plasma metabolism and biomarkers of coronary heart disease patients. In the field of physical therapy such as acupuncture and moxibustion, researchers discovered the effect of stimulating acupoint ST40 on gene expression and the effects of acupuncture on treating functional dyspepsia and acute ischemic stroke. Herbs and formulas were analyzed with TCM network pharmacology. The therapeutic mechanisms of Si Wu Tang and its series formulas are explained by identifying potential active substances, targets and mechanism of action, including metabolic pathways of amino acid and fatty acid. For the academic development of TCM systems biology and its technology, it is necessary to integrate massive database, integrate pharmacokinetics and pharmacodynamics, as well as systems biology. It is also essential to establish a platform to maximize herbal treatment through accumulation of research data and diseases-specific, or drug-specific network combined with clinical experiences, and identify functions and roles of molecules in herbs and conduct animal-based studies within TCM frame. So far, few literature reviews exist for systems biology in traditional Korean medicine and they merely re-examine known efficacies of simple substances, herbs and formulas. For the future, it is necessary to identify specific mechanisms of working agents and targets to maximize the effects of traditional medicine modalities. Conclusions : Systems biology is widely accepted and studied in TCM and already advanced into a field known as 'TCM systems biology', which calls for the study of incorporating TCM and systems biology. It is time for traditional Korean medicine to acknowledge the importance of systems biology and present scientific basis of traditional medicine and establish the principles of diagnosis, prevention and treatment of diseases. By doing so, traditional Korean medicine would be innovated and further developed into a personalized medicine.

• Animal Bioscience
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• v.35 no.1
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• pp.115-125
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• 2022

Objective: Intramuscular fat (IMF) is a critical economic indicator of pork quality. Studies on IMF among different pig breeds have been performed via high-throughput sequencing, but comparisons within the same pig breed remain unreported. Methods: This study was performed to explore the gene profile and identify candidate long noncoding RNA (lncRNAs) and mRNAs associated with IMF deposition among Laiwu pigs with different IMF contents. Based on the longissimus dorsi muscle IMF content, eight pigs from the same breed and management were selected and divided into two groups: a high IMF (>12%, H) and low IMF group (<5%, L). Whole-transcriptome sequencing was performed to explore the differentially expressed (DE) genes between these two groups. Results: The IMF content varied greatly among Laiwu pig individuals (2.17% to 13.93%). Seventeen DE lncRNAs (11 upregulated and 6 downregulated) and 180 mRNAs (112 upregulated and 68 downregulated) were found. Gene Ontology analysis indicated that the following biological processes played an important role in IMF deposition: fatty acid and lipid biosynthetic processes; the extracellular signal-regulated kinase cascade; and white fat cell differentiation. In addition, the peroxisome proliferator-activated receptor, phosphatidylinositol-3-kinase-protein kinase B, and mammalian target of rapamycin pathways were enriched in the pathway analysis. Intersection analysis of the target genes of DE lncRNAs and mRNAs revealed seven candidate genes associated with IMF accumulation. Five DE lncRNAs and 20 DE mRNAs based on the pig quantitative trait locus database were identified and shown to be related to fat deposition. The expression of five DE lncRNAs and mRNAs was verified by quantitative real time polymerase chain reaction (qRT-PCR). The results of qRT-PCR and RNA-sequencing were consistent. Conclusion: These results demonstrated that the different IMF contents among pig individuals may be due to the DE lncRNAs and mRNAs associated with lipid droplets and fat deposition.