• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.6089-6094
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• 2013

Berberine, a common isoquinoline alkaloid, has been shown to possess anti-cancer activities. However, the underlying molecular mechanisms are still not completely understood. In the current study, we investigated the effects of berberine on cell growth, colony formation, cell cycle distribution, and whether it improved the anticancer efficiency of cisplatin and doxorubicin in human breast cancer estrogen receptor positive (ER+) MCF-7 cells and estrogen receptor negative (ER-) MDA-MB-231 cells. Notably, berberine treatment significantly inhibited cell growth and colony formation in the two cell lines, berberine in combination with cisplatin exerting synergistic growth inhibitory effects. Accompanied by decreased growth, berberine induced G1 phase arrest in MCF-7 but not MDA-MB-231 cells. To provide a more detailed understanding of the mechanisms of action of berberine, we performed genome-wide expression profiling of berberine-treated cells using cDNA microarrays. This revealed that there were 3,397 and 2,706 genes regulated by berberine in MCF-7 and MDA-MB-231 cells, respectively. Fene oncology (GO) analysis identified that many of the target genes were involved in regulation of the cell cycle, cell migration, apoptosis, and drug responses. To confirm the microarray data, qPCR analysis was conducted for 10 selected genes based on previously reported associations with breast cancer and GO analysis. In conclusion, berberine exhibits inhibitory effects on breast cancer cells proliferation, which is likely mediated by alteration of gene expression profiles.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3543-3549
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• 2015

Background: Bladder cancer is one of the most common cancers worldwide. Gene expression profiling using microarray technologies improves the understanding of cancer biology. The aim of this study was to determine the gene expression profile in Egyptian bladder cancer patients. Materials and Methods: Samples from 29 human bladder cancers and adjacent non-neoplastic tissues were analyzed by cDNA microarray, with hierarchical clustering and multidimensional analysis. Results: Five hundred and sixteen genes were differentially expressed of which SOS1, HDAC2, PLXNC1, GTSE1, ULK2, IRS2, ABCA12, TOP3A, HES1, and SRP68 genes were involved in 33 different pathways. The most frequently detected genes were: SOS1 in 20 different pathways; HDAC2 in 5 different pathways; IRS2 in 3 different pathways. There were 388 down-regulated genes. PLCB2 was involved in 11 different pathways, MDM2 in 9 pathways, FZD4 in 5 pathways, p15 and FGF12 in 4 pathways, POLE2 in 3 pathways, and MCM4 and POLR2E in 2 pathways. Thirty genes showed significant differences between transitional cell cancer (TCC) and squamous cell cancer (SCC) samples. Unsupervised cluster analysis of DNA microarray data revealed a clear distinction between low and high grade tumors. In addition 26 genes showed significant differences between low and high tumor stages, including fragile histidine triad, Ras and sialyltransferase 8 (alpha) and 16 showed significant differences between low and high tumor grades, like methionine adenosyl transferase II, beta. Conclusions: The present study identified some genes, that can be used as molecular biomarkers or target genes in Egyptian bladder cancer patients.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.637-647
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• 2010

Recent embedded systems are being more complicated due to their hierarchical software architecture including operating systems. The performance of such complicated software architecture could not be well analyzed through separate analysis of each software layer; the combined effect and the interactions among the whole software layers should be considered. In this paper, we show the design and implementation of a performance analysis framework that enables hierarchical analysis of performance of Linux-based embedded systems considering interactions among the software layers. By using the proposed framework, we can obtain useful run-time information about a hierarchical software structure which usually consists of user-defined function layer, library function layer, system call layer, and kernel events layer. Experimental results reveal that the proposed framework could accurately identify the performance bottlenecks with the corresponding software layers during executions of target applications through the accompanying sub-steps of the analysis: the actual execution paths, the execution time of each observed event in each software layer, and the control flows across the software layers.

• The Journal of Engineering Geology
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• v.4 no.2
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• pp.187-206
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• 1994

Through a computer model study, optimum system configuration and field parameters were determined for high-resolution marine reflection surveys. Characteristics of far-field signatures were analysed in both time and frequency domains for the six individual R/V Onnuri. The analysis shows that the cluster fired at the depth of 2m below the sea surface generates the most ideal far-field signatures among the above seismic sources. Compared with the 96-channel streamer on the R/V Onnuri, the 12-channel streamer is suitable for shallow reflection profiling due to its high resolution both in the vertical and horizontal directions despite its lower signal-to-noise ratio. Considering factors including target depth, frequency range, airgun volume, number of recording channels, and capacity of compressors, optimum values for record length, sample period, and shot interval are believed to be is, 1ms, and 3.125m or 6.25m, respectively.

• Genomics & Informatics
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• v.5 no.3
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• pp.102-106
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• 2007

Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.2
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• pp.315-321
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• 2012

In this study, the product attributes that give customers the estimated benefits and products that can predict the customer's choice conjoint analysis techniques to identify the restaurant affinity markets a new dining concept was to develop. Questionnaire for this study of 400 non-response is negative and insincere characters, except for the final analysis, the questionnaire Part 309 was the target. Conjoint model used in this study Pearson's R is 0.928 ($p$<0.000), Kendall's tau is 0.750 ($p$<0.000) with an orthogonal plan was well suited for profiling attributes are extracted 16. Part of the relative importance of the value of the property to determine the result of analyzing the properties that are most important at the level of the respondents of the induct (38.46%), and followed by price (30.52%), Atmosphere (18.28%), and Exclusive space (12.73%) was followed. Portion of the property value for each analysis among industry preference for the Italian food was highest, a nature-friendly interior atmosphere had the highest affinity Average per price at 10,000 won~30,000 won or less than the amount of affinity was higher location of the restaurant alone, showed that space preferred. Through simulation in a virtual seafood restaurant nature-friendly image, average price per person ranging from 10,000 to 30,000won at an exclusive restaurant was most preferred.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.478-483
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• 2015

Decontamination of biological agents utilizes hydrogen peroxide($H_2O_2$) for its effectiveness and safeness. Bacillus anthracis is a major target for $H_2O_2$ decontamination. To assess the effect of $H_2O_2$ on B. anthracis and identify biomarkers for decontamination, whole transcriptomic profiling of $H_2O_2$-treated B. anthracis was performed. Here we identified deregulation in stress response genes, transcription factors and cellular homeostasis genes. We also found that expression of antisense RNAs increased in B. anthracis during decontamination. We postulate that B. anthracis prioritizes survival and adaptation in response to $H_2O_2$ treatment by changing its gene expression pattern.

• International Journal of Oral Biology
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• v.43 no.4
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• pp.223-230
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• 2018

Exosomes are Nano-sized lipid vesicles secreted from mammalian cells containing diverse cellular materials such as proteins, lipids, and nucleotides. Multiple lines of evidence indicate that in saliva, exosomes and their contents such as microRNAs (miRNAs) mediate numerous cellular responses upon delivery to recipient cells. The objective of this study was to characterize the different expression profile of exosomal miRNAs in saliva samples, periodically isolated from a single periodontitis patient. Unstimulated saliva was collected from a single patient over time periods for managing periodontitis. MicroRNAs extracted from each phase were investigated for the expression of exosomal miRNAs. Salivary exosomal miRNAs were analyzed using Affymetrix miRNA arrays and prediction of target genes and pathways for its different expression performed using DIANA-mirPath, a web-based, computational tool. Following the delivery of miRNA mimics (hsa-miR-4487, -4532, and -7108-5p) into human gingival fibroblasts, the expression of pro-inflammatory cytokines and activation of the MAPK pathway were evaluated through RT-PCR and western blotting. In each phase, 13 and 43 miRNAs were found to be differently expressed $({\mid}FC{\mid}{\geq}2)$. Among these, hsa-miR-4487 $({\mid}FC{\mid}=9.292005)$ and has-miR-4532 $({\mid}FC{\mid}=18.322697)$ were highly up-regulated in the clinically severe phase, whereas hsa-miR-7108-5p $({\mid}FC{\mid}=12.20601)$ was strongly up-regulated in the clinically mild phase. In addition, the overexpression of miRNA mimics in human gingival fibroblasts resulted in a significant induction of IL-6 mRNA expression and p38 phosphorylation. The findings of this study established alterations in salivary exosomal miRNAs which are dependent on the severity of periodontitis and may act as potential candidates for the treatment of oral inflammatory diseases.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.10
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• pp.1483-1490
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• 2019

Objective: To explore the molecular mechanisms of fat metabolism and deposition in pigs, an experiment was conducted to identify hepatic mRNAs and miRNAs expression and determine the potential interaction of them in two phenotypically extreme pig breeds. Methods: mRNA and miRNA profiling of liver from 70-day Jinhua (JH) and Landrace (LD) pigs were performed using RNA sequencing. Blood samples were taken to detect results of serum biochemistry. Bioinformatics analysis were applied to construct differentially expressed miRNA-mRNA network. Results: Serum total triiodothyronine and total thyroxine were significantly lower in Jinhua pigs, but the content of serum total cholesterol (TCH) and low-density lipoprotein cholesterol were strikingly higher. A total of 467 differentially expressed genes (DEGs) and 35 differentially expressed miRNAs (DE miRNAs) were identified between JH and LD groups. Gene ontology analysis suggested that DEGs were involved in oxidation-reduction, lipid biosynthetic and lipid metabolism process. Interaction network of DEGs and DE miRNAs were constructed, according to target prediction results. Conclusion: We generated transcriptome and miRNAome profiles of liver from JH and LD pig breeds which represent distinguishing phenotypes of growth and metabolism. The potential miRNA-mRNA interaction networks may provide a comprehensive understanding in the mechanism of lipid metabolism. These results serve as a basis for further investigation on biological functions of miRNAs in the porcine liver.