• Toxicological Research
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• v.22 no.4
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• pp.323-328
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• 2006

Global gene expression profile was analyzed by microarray analysis of rat liver RNA after acute acetaminophen (APAP) administration. A single dose of 1g/kg body weight of APAP was given orally, and the liver samples were obtained after 24, 48 h, and 2 weeks. Histopathologic and biochemical studies enabled the classification of the APAP effect into injury (24 and 48 h) and regeneration (2 weeks) stages. The expression levels of 4900 clones on a custom rat gene microarray were analyzed and 484 clones were differentially expressed with more than a 1.625-fold difference(which equals 0.7 in log2 scale) at one or more time points. Two hundred ninety seven clones were classified as injury-specific clones, while 149 clones as regeneration-specific ones. Characteristic gene expression profiles could be associated with APAP-induced gene expression changes in lipid metabolism, stress response, and protein metabolism. We established a global gene expression profile utilizing microarray analysis in rat liver upon acute APAP administration with a full chronological profile that not only covers injury stage but also later point of regeneration stage.

• Nutritional Sciences
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• v.8 no.1
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• pp.23-27
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• 2005

The major garlic component, Allicin [diallylthiosulfinate, or (R, S)-diallyldissulfid-S-oxide] is known for its medicinal effects, such as antihypertensive activity, microbicidal activity, and antitumor activity. Allicin and diallyldisulfide, which is a converted form of allicin, inhibited the cholesterol level in hepatocytes, in vivo and in vitro. The metabolism of allicin reportedly occurs in the microsomes of hepatocytes, predominantly with the contribution of cytochrome P-450. However, little is known about how allicin affects the genes involved in the activity of hepatocytes in vivo. In the present study, we used the short-term intravenous injection of allicin to examine the in vivo genetic profile of hepatocytes. Allicin up-regulate ten genes in the hepatocytes. For example, the interferon regulator 1 (IRF-I), the wingless-related MMTV (mouse mammary tumor virus) integration site 4 (wnt-4), and the fatty acid binding protein 1. However, allicin down-regulated three genes: namely, glutathione S-transferase mu6, a-2-HS glycoprotein, and the corticosteroid binding globulin of hepatocytes. The up-regulated wnt-4, IRF-1, and mannose binding lectin genes can enhance the growth factors, cytokines, transcription activators and repressors that are involved in the immune defense mechanism. These primary data, which were generated with the aid of the Atlas Plastic Mouse 5 K Microarray, help to explain the mechanism which enables allicin to act as a therapeutic agent, to enhance immunity, and to prevent cancer. The data suggest that these benefits of allicin are partly caused by the up-regulated or down-regulated gene profiles of hepatocytes. To evaluate the genetic profile in more detail, we need to use a more extensive mouse genome array.

• Korean Journal of Veterinary Research
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• v.39 no.6
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• pp.1091-1098
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• 1999

Antimicrobial susceptibility, plasmid profiles and distribution of toxA gene were investigated in Pasteurella multocida isolated from pneumonic lung lesions of swine. The bacteria were highly susceptible to norfloxacin, cabenicillin, enrofloxacin and chloramphenicol, but resistant to colistin, sulfamethoxawle/trimethoprime, bacitracin, streptomycin. Sixty percentage of the isolates was resistant more than 2 drugs used in this experiment and 21 strains (23.6%) were resistant more than 5 drugs. This phenomenon meant that they had highly multi-drugs resistance. In the analysis of plasmid profiles, nineteen strains (47.5%) of 40 P multocida isolates harbored plasmids, ranging from 53.3kb to 2.49kb in size and the plasmid profiles could be classified into 5 groups. However, there was no relationship between the size and the profile of plasmid and the resistance pattern of antimicrobial agents. Thirty strains of 39 P multocida isolates (77%) investigated by PCR harbored toxA gene. This result suggested involvement of the ToxA protein expressed from the gene in pneumonic pasteurellosis of swine.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5557-5563
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• 2015

Background: Cholelithiasis is associated in 54%-98% of patients with carcinoma of the gallbladder, and a high incidence among females suggests a role of female hormones in the etiology of the disease. Cytochrome $P450C17{\alpha}$ (CYP-17) is a key enzyme involved in estrogen metabolism and polymorphisms in CYP-17 are associated with altered serum levels of estrogens. Thus, we investigated whether the CYP-17 MspA1 gene polymorphism might impact on risk of gall bladder cancers or gallstones, as well as to determine if this gene polymorphism might be linked with estrogen serum levels and lipid profile among the North Indian gall bladder cancer or gallstone patients. Materials and Methods: CYP-17 gene polymorphisms (MspA1) were genotyped with PCR-RFLP in cancer patients (n=96), stone patients (n=102), cancer + stone patients (n=52) and age/sex matched control subjects (n= 256). Lipid profile was estimated using a commercial kit and serum estrogen was measured using ELISA. Results: The majority of the patients in all groups were females. The lipid profile and estrogen level were significantly higher among the study as compared to control groups. The frequency of mutant allele A2 of CYP17 MspA1 gene polymorphism was higher among cancer (OR=5.13, 95% CI+3.10-8.51, p=0.0001), stone (OR=5.69, 95%CI=3.46-9.37, p=0.0001) and cancer + stone (OR=3.54, 95%CI=1.90-6.60, p=0.0001) when compared with the control group. However there was no significant association between genotypes of CYP17 MspA1 gene polymorphism and circulating serum level of estrogen and lipid profile. Conclusions: A higher frequency of mutant genotype A1A2 as well as mutant allele A2 of CYP-17 gene polymorphism is significantly associated with risk of gallbladder cancer and stones. Elevated levels of estrogen and an altered lipid profile can be used as predictors ofgall bladder stones and cancer in post menopausal females in India.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.525-536
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• 2004

Gene expression profile is numerical data of gene expression level from organism, measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify disease with gene expression profile. Because all genes are not related to disease, it is needed to select related genes that is called feature selection, and it is needed to classify selected genes properly. This paper Proposes GA based method for searching optimal ensemble of feature-classifier pairs that are composed with seven feature selection methods based on correlation, similarity, and information theory, and six representative classifiers. In experimental results with leave-one-out cross validation on two gene expression Profiles related to cancers, we can find ensembles that produce much superior to all individual feature-classifier fairs for Lymphoma dataset and Colon dataset.

• KSBB Journal
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• v.16 no.4
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• pp.381-388
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• 2001

A program for integrated gene expression profile analysis such as hierarchical clustering, K-means, fuzzy c-means, self-organizing map(SOM), principal component analysis(PCA), and singular value decomposition(SVD) was made for DNA chip data anlysis by using Matlab. It also contained the normalization method of gene expression input data. The integrated data anlysis program could be effectively used in DNA chip data analysis and help researchers to get more comprehensive analysis view on gene expression data of their own.

• BMB Reports
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• v.39 no.4
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• pp.457-463
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• 2006

Insulin resistance is commonly observed in patients prior to the development of type 2 diabetes and may predict the onset of the disease. We tested the hypothesis that impairment in insulin stimulated glucose-disposal in insulin resistant patients would be reflected in the gene expression profile of skeletal muscle. We performed gene expression profiling on skeletal muscle of insulin resistant and insulin sensitive subjects using microarrays. Microarray analysis of 19,000 genes in skeletal muscle did not display a significant difference between insulin resistant and insulin sensitive muscle. This was confirmed with real-time PCR. Our results suggest that insulin resistance is not reflected by changes in the gene expression profile in skeletal muscle.

• Molecular & Cellular Toxicology
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• v.2 no.4
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• pp.273-278
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• 2006

95 squamous cell lung carcinoma samples (normal tissue: 40 samples, tumor: 55 samples) were analyzed with 8 K cDNA microarray. 1-way ANOVA test was employed to select differentially expressed genes in tumor with FDR<0.01. Among the selected 1,655 genes, final 212 genes were chosen according to the expression fold change and used for following analysis. The expression of up-regulated 64 genes was verified with Reverse Transcription PCR and 10 genes were identified as candidates for SCC markers. In our opinion, those candidates can be exploited as diagnostic or therapeutic purposes. Gene Ontology (GO) based analysis was performed using those 212 genes, and following categories were revealed as significant biological processes: Immune response (GO: 0006955), antigen processing (GO: 0030333), inflammatory response (GO: 0006954), Cell adhesion (GO: 0007155), and Epidermis differentiation (GO: 0008544). Gene set enrichment analysis (GSEA) also carried out on overall gene expression profile with 522 functional gene sets. Glycolysis, cell cycle, K-ras and amino acid biosynthesis related gene sets were most distinguished. These results are consistent with the known characteristics of SCC and may be interconnected to rapid cell proliferation. However, the unexpected results from ERK activation in squamous cell carcinoma gripped our attention, and further studies are under progress.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.161-164
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• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• Journal of Life Science
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• v.22 no.1
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• pp.110-116
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• 2012

Nuruk plays a significant role in the flavor and quality of Takju and Yakju, which are produced through saccharification and alcohol fermentation by various microorganisms. In this study, we identified microbial strains isolated from a plate count and PCR-denaturing gradient gel electrophoresis (DGGE) analysis targeting the 16S and 28S rRNA genes, in order to characterize bacterial and fungal diversity in Sansung Nuruk. The numbers of bacteria and fungi in Nuruk were $1.5{\times}10^9$ CFU/g and $2.2{\tims}10^8$ CFU/g, respectively. The 16S rRNA gene sequence indicated that the predominant bacteria in the isolates and PCR-DGGE profile of Nuruk were Kocuria spp., Pantoea spp., Lactobacillus spp., Pediococcus spp., Weissella spp., Staphylococcus spp., endophytic bacterium, uncultured Gamma-proteobacteria, uncultured Cyanobacteria, and Actinobacteria. Dominant bacteria from the PCR-DGGE profile were Pediococcous pentosaceus and uncultured Cyanobacteria. The 28S rRNA gene sequence indicated the predominant fungi in the isolates and PCR-DGGE profile to be Trichomonascus spp. Pichia spp., Torulaspora spp., Wickerhamomyces spp., Sacharomycopsis spp., Lichtheimia spp., Mucor spp., Rhizopus spp. Aspergillus spp., and Cladosporium spp. Dominant fungi from the PCR-DGGE profile were Pichia kudriavzevii and Aspergillus oryzae. The PCR-DGGE technique was used for the first time in this study to assess a microbial community in Nuruk and proved to be an effective protocol for profiling microbial diversity.