• 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.

• International Journal of Industrial Entomology and Biomaterials
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• v.23 no.1
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• pp.137-141
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• 2011

A previous data was provided information for tissuespecific expression genes by means of whole-genome oligonucleotide microarray in the silkworm. We analyzed the tissue-specific expression patterns in the hemocyte tissue on 5 days of 5th instar larvae during the development of $B.$ $mori$. Total 5 candidates pick out from the $Bombyx$ $mori$ Microarray Database (BmMDB; http://silkworm.swu.edu.cn/microarray). To verify the hemocyte-specific expression, we analyzed by semi-quantitative and real-time quantitative RT-PCR using the highly expressed endogenous $Actin$ RNA as an intrinsic reference. In this study, we confirmed that one gene-sw17255- out of 5 candidates expressed in the hemocyte tissue, which was consistent with the previous data. Circulating hemocytes in the body fluid of the $B.$ $mori$ are most powerful target organ for producing biomaterials. We need further studies to find hemocyte-specific promoter region from sw17255 gene. Finally, this result can be applied in creating transgenic silkworms as a biomedical insect.

• Journal of Embryo Transfer
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• v.30 no.1
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• pp.17-21
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• 2015

Alteration in ion channel or transporter expression levels affects cell volume which is produced by movement of water and ion across the plasma membrane. In particular, aquaporin (AQP) channels among ion channels play a crucial role in movement of water across the cell membrane. This study was performed to identify whether AQP expression is changed in bovine follicular cystic follicles using microarray, RT-PCR and Western blotting analyses. In microarray data, AQP4 expression was decreased, whereas AQP7 was increased in cystic follicles. Additional experiments were focused on the AQP7 expression increased in cystic follicles. The microarray data was confirmed by semi-quantitative polymerase chain reaction (PCR) and Western blot analysis. AQP7 mRNA and protein expressions were significantly increased in the cystic follicles (p<0.05). Application of estrogen ($10{\mu}g/ml$) to bovine ovarian cells showed a trend of increase in AQP7 expression. From these results, we suggest that the increase in AQP7 expression in cystic follicles may play an important role in movement of water in bovine ovary. In addition, AQP7, a aquaglyceroporin permeating water and glycerol, could be a good target in development of methods for the cryopreservation of bovine ovary.

• Journal of Life Science
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• v.24 no.8
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• pp.843-850
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• 2014

In the current study, we prepared eighty-five different kinds of solvent fractions of rice wine lees and nuruk extracts and investigated their effects on cell viability and nitric oxide (NO) production in mouse RAW 264.7 cells. Among the treated solvent fractions, only three solvent fractions (KSD-E1-3, KSD-E2-3 and KSD-E4-3) significantly decreased NO production in LPS-activated RAW 264.7 cells without affecting cell viability. And, they also reduced the expression of pro-inflammatory genes such as COX-2, TNF-alpha and iNOS. To understand the molecular mechanisms involved in the inhibition of inflammation in (KSD-E4-3)-treated RAW 264.7 cells, we carried out oligo DNA microarray analysis using Agilent Mouse microarray. To confirm microarray data, 6 genes (IL-1F6, iNOS, IL-10, Fabp4, IL-1RN and CSF2) were selected and performed RT-PCR and quantitative real-time PCR analysis with gene specific primers. The results of RT-PCR and real-time PCR agreed with microarray data. Overall, our results suggest that rice wine lees can be a novel resource for the development of foods and drugs which possess anti-inflammatory activity.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.701-718
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• 2006

In cancer microarray experiments, the experimenter or patient which is nested in each experimenter often shows quite heterogeneous error variability, which should be estimated for identifying a source of variation. Our study describes a Bayesian method which utilizes clinical information for identifying a set of DE genes for the class of subtypes as well as assesses and examines the experimenter effect and patient effect which is nested in each experimenter as a source of variation. We propose a Bayesian multilevel mixed effect model based on analysis of covariance (ANACOVA). The Bayesian multilevel mixed effect model is a combination of the multilevel mixed effect model and the Bayesian hierarchical model, which provides a flexible way of defining a suitable correlation structure among genes.

• Molecules and Cells
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• v.21 no.1
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• pp.82-88
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• 2006

The global pattern of growth-dependent gene expression in Streptococcus pneumoniae strains was evaluated using a high-density DNA microarray. Total RNAs obtained from an avirulent S. pneumoniae strain R6 and a virulent strain AMC96-6 were used to compare the expression patterns at seven time points (2.5, 3.5, 4.5, 5.5, 6.0, 6.5, and 8.0 h). The expression profile of strain R6 changed between log and stationary growth (the Log-Stat switch). There were clear differences between the growth-dependent gene expression profiles of the virulent and avirulent pneumococcal strains in 367 of 1,112 genes. Transcripts of genes associated with bacterial competence and capsular polysaccharide formation, as well as clpP and cbpA, were higher in the virulent strain. Our data suggest that late log or early stationary phase may be the most virulent phase of S. pneumoniae.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.585-594
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• 2009

Researchers of microarray experiment transpose processed images of raw data to possible data of statistical analysis: it is preprocessing. Preprocessing of microarray has image filtering, imputation and normalization. There have been studied about several different methods of normalization and imputation, but there was not further study on the order of the procedures. We have no further study about which things put first on our procedure between normalization and imputation. This study is about the identification of differentially expressed genes(DEG) on the order of the preprocessing steps using two-dye cDNA microarray in colon cancer and gastric cancer. That is, we check for compare which combination of imputation and normalization steps can detect the DEG. We used imputation methods(K-nearly neighbor, Baysian principle comparison analysis) and normalization methods(global, within-print tip group, variance stabilization). Therefore, preprocessing steps have 12 methods. We identified concordance measure of DEG using the datasets to which the 12 different preprocessing orders were applied. When we applied preprocessing using variance stabilization of normalization method, there was a little variance in a sensitive way for detecting DEG.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.767-776
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• 2008

Microarray technology is extensively being used in experimental molecular biology field. Microarray experiments generate quantitative expression measurements for thousands of genes simultaneously, which is useful for the phenotype classification of many diseases. One of the two major problems in microarray data classification is that the number of genes exceeds the number of tissue samples. The other problem is that current methods generate classifiers that are accurate but difficult to interpret. Our paper addresses these two problems. We performed a direct integration of individual microarrays with same biological objectives by transforming an expression value into a rank value within a sample and generated rank-comparison decision rules with variable number of genes for cancer classification. Our classifier is an ensemble method which has k top scoring decision rules. Each rule contains a number of genes, a relationship among involved genes, and a class label. Current classifiers which are also ensemble methods consist of k top scoring decision rules. However these classifiers fix the number of genes in each rule as a pair or a triple. In this paper we generalized the number of genes involved in each rule. The number of genes in each rule is in the range of 2 to N respectively. Generalizing the number of genes increases the robustness and the reliability of the classifier for the class prediction of an independent sample. Also our classifier is readily interpretable, accurate with small number of genes, and shed a possibility of the use in a clinical setting.

• Journal of Embryo Transfer
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• v.25 no.1
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• pp.29-34
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• 2010

Follicular cystic ovary (FCO) is one of the major causes of reproductive failure in cattle. Genetic alterations affect the function of diverse cells and/or tissues, which could be present in cystic ovaries. A microarray analysis was performed to screen differential gene expressions in follicular cystic follicles of cattle. In this study, we hypothesized that follicular cysts may be induced by changes in ion- and transporter-related gene expression. Microarray data showed that fibrinogen-gamma (FGG) and low density lipoprotein receptor-related protein 8 (LRP8) were up-regulated, while choline transporter-like protein 4 (SLC44A4), very long-chain acyl-CoA synthetase homolog 2 (SLC27A5), annexin 8 (ANXA8), and aquaporin 4 were down-regulated in follicular cystic follicles. A semi-quantitative RT-PCR was carried out to validate DEGs altered in follicular cystic follicles. Of six DEGs, three DEGs (FGG, SLC44A4, and aquaporin 4) showed a positive correlation between microarray and semi-quantitative PCR data. We focused on FGG, among three DEGs, which was highly up-regulated in follicular cystic follicles. The FGG mRNA was upregulated by 8.4-fold and by 1.7-fold in the bovine follicular cystic follicles as judged by microarray and RT-PCR analysis, respectively. However, there was no significant changes in the expression level of FGG protein in both follicular cystic follicles and granulosa cells isolated from follicular cystic follicles by Western blot analysis. Although this study does not reveal a positive correlation between the mRNA and protein level, FGG appears to be an important biomarker in the discrimination of follicular cyst from normal ovary.

• The Korean Journal of Physiology and Pharmacology
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• v.10 no.5
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• pp.263-271
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• 2006

Since astrocytes were shown to play a central role in maintaining neuronal viability both under normal conditions and during stress such as ischemia, studies of the astrocytic response to stress are essential to understand many types of brain pathology. The micro array system permitted screening of large numbers of genes in biological or pathological processes. Therefore, the gene expression patterns in the in vitro model of astrocytes following exposure to oxygen-glucose deprivation (OGD) were evaluated by using the micro array analysis. Primary astrocytic cultures were prepared from postnatal Swiss Webster mice. The cells were exposed to OGD for 4 hrs at $37^{\circ}C$ prior to cell harvesting. From the cultured cells, we isolated mRNA, synthesized cDNA, converted to biotinylated cRNA and then reacted with GeneChips. The data were normalized and analyzed using dChip and GenMAPP tools. After 4 hrs exposure to OGD, 4 genes were increased more than 2 folds and 51 genes were decreased more than 2 folds compared with the control condition. The data suggest that the OGD has general suppressive effect on the gene expression with the exception of some genes which are related with ischemic cell death directly or indirectly. These genes are mainly involved in apoptotic and protein translation pathways and gap junction component. These results suggest that microarray analysis of gene expression may be useful for screening novel molecular mediators of astrocyte response to ischemic injury and making profound understanding of the cellular mechanisms as a whole. Such a screening technique should provide insights into the molecular basis of brain disorders and help to identify potential targets for therapy.