We present a novel methodology for biological interpretation of gene clusters. Our graph theoretic algorithm extracts common biological attributes of the genes within a cluster or a group of interest through the modified structure of gene ontology (GO) called GO tree. After genes are annotated with GO terms, the hierarchical nature of GO terms is used to find the representative biological meanings of the gene clusters. In addition, the biological significance of gene clusters can be assessed quantitatively by defining a distance function on the GO tree. Our approach has a complementary meaning to many statistical clustering techniques; we can see clustering problems from a different viewpoint by use of biological ontology. We applied this algorithm to the well-known data set and successfully obtained the biological features of the gene clusters with the quantitative biological assessment of clustering quality through GO Biological Process.

BackgroundThe prevalence of type 2 diabetes has reached epidemic proportions worldwide, and the incidence of life-threatening complications of diabetes through continued exposure of tissues to high glucose levels is increasing. Advances in genotyping technology have increased the scale and accuracy of the genotype data so that an association genetic study has expanded enormously. Consequently, it is difficult to search the published association data efficiently, and several databases on the association results have been constructed, but these databases have their limitations to researchers: some providing only genome-wide association data, some not focused on the association but more on the integrative data, and some are not user-friendly. In this study, a user-friend database of type 2 diabetes genetic association of manually curated information was constructed.DescriptionThe list of publications used in this study was collected from the HuGE Navigator, which is an online database of published genome epidemiology literature. Because type 2 diabetes genetic association database (T2DGADB) aims to provide specialized information on the genetic risk factors involved in the development of type 2 diabetes, 701 of the 1,771 publications in the type 2 Diabetes case-control study for the development of the disease were extracted.ConclusionsIn the database, the association results were grouped as either positive or negative. The gene and SNP names were replaced with gene symbols and rsSNP numbers, the association p-values were determined manually, and the results are displayed by graphs and tables. In addition, the study design in publications, such as the population type and size are described. This database can be used for research purposes, such as an association and functional study of type 2 diabetes related genes, and as a primary genetic resource to construct a diabetes risk test in the preparation of personalized medicine in the future.

Bioassay-guided fractionation of the root extract of Asarum sieboldii led to the isolation of the four active compounds (-)-sesamin (1), (2E,4E,8Z,10E)-N-(2-methylpropyl)dodeca-2,4,8,10-tetraenamide (2), kakuol (3), and '3,4,5-trimethoxytoluene' (=1,2,3-trimethoxy-5-methylbenzene; 4), in terms of inhibition of lipopolysaccharide (LPS)-induced nitric oxide (NO) production. Compounds 1-4 showed potent inhibition of NO production, with IC(50) values in the low nanomolar-to-micromolar range. Also isolated were the known compounds methylkakuol (5), '3,5-dimethoxytoluene', safrole, asaricin, methyleugenol, and (-)-asarinin, which were found to be inactive in the above assay. Among the ten known isolates, compounds 1, 2, and 5 were found for the first time in this plant.

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BackgroundPhysicians tend to overcorrect when applying the acellular dermal matrix for reconstructive option because of volume decrement problem after absorption comparing with initial volume. However, there are no studies on the exact volume decrement and absorption rate with commercial products in South Korea. To figure out absorption rate of acellular dermal matrix product in South Korea (Megaderm), authors designed this experiment.MethodsNine mice were used and randomly divided into three groups by the time with sacrificing. The implant (Megaderm) was tailored to fit a cuboid form (1.0 cm× 1.0 cm in length and width and 2.0 mm in thickness). A skin incision was made at anterior chest with blade #15 scalpel with exposing the pectoralis major muscle. As hydrated Megaderm was located upon the pectoralis major muscle, the skin was sutured with Ethilon #5-0. After the surgical procedure, each animal group was sacrificed at 4, 8, and 12 weeks, respectively, for biopsies and histological analysis of the implants. All samples were stained with routine hematoxylin and eosin staining and Masson’s trichrome staining and the thickness were measured. A measurements were analyzed using Friedman test. Statistically, the correlation between thicknesses of Megaderm before and after implantation was analyzed.ResultsAfter sacrificing the animal groups at postoperative 4, 8, 12 weeks, the mean tissue thickness values were 2.10± 1.03 mm, 2.17± 0.21 mm, and 2.40± 0.20 mm (p= 0.368), respectively. The remaining ratios after absorption comparing with after initial hydrated Megaderm were 82.7%, 85.4%, and 94.5%, respectively. In histopathological findings, neovascularization and density of collagenous fiber was increased with time.ConclusionAuthor’s hypothesis was absorption rate of implant would be increased over time. But in this experiment, there is no statistical significance between mean absorption thickness of implant and the time (p= 0.368). Also it can be affected by graft site, blood supply, and animals that were used in the experiment.

BackgroundUltraviolet A (UVA) rays reach the dermal skin layer and generate oxidative stress, DNA damage, and cell inflammation, which in turn lead to photo-aging and photo-carcinogenesis. While there have been many studies about the beneficial effects of topical epidermal growth factor (EGF) treatment in the healing of wounds, the effect of EGF on UVA-induced skin irritation remains unknown. To clarify the effects of EGF on UVA-induced skin damage, it was investigated whether EGF signaling can affect intracellular reactive oxygen species (ROS) and DNA damages in UVA-irradiated human dermal fibroblasts.Materials and methodsFibroblasts cultured with or without rhEGF were UVA-irradiated at 40 mJ/cm2 twice per day for 5 days. After the irradiation, the intracellular ROS levels and expression of catalase and superoxide dismutase-1 (SOD-1) in the fibroblasts were ascertained. Further investigation to determine the effects of EGF on UVA-induced DNA damage, including a single cell gel electrophoresis assay and an enzyme-linked immunosorbent assay (ELISA), was carried out. Moreover, the NF-κB activity was ascertained in order to investigate the effects of EGF on UVA-irradiated fibroblasts.ResultsAs a result, it was revealed that recombinant human EGF (rhEGF) inhibited UVA- increased intracellular ROS in the fibroblasts and increased the expression of catalase and SOD-1. Moreover, in UVA-irradiated fibroblasts, the longest DNA-damaged tails were observed, but this phenomenon was not detected in cells cotreated with both UVA and rhEGF. Also, it was observed that DNA damage induction, including that of cyclobutene pyrimidine dimers, pyrimidine (6-4) pyrimidone photoproducts, and 8-hydroxy-2-deoxyguanosine, was caused by UVA irradiation. Similar to previous results, it was downregulated by rhEGF. Furthermore, rhEGF also inhibited NF-κB gene expression and the NF-κB p65 protein level in the nucleus induced by UVA irradiation.ConclusionThese results suggest that EGF might be a useful material for preventing or improving photo-aging.

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Recently, many state-of-the-art omics technologies are being applied to systems toxicology research because evaluation of toxicity in pre-clinical trials is a big issue in the pharmaceutical industry. Now, genetic polymorphisms are also considered in systems toxicology because polymorphism information can be used to explain individual-specific toxicity and/ or side effects. However, in spite of its importance, no well-organized database for individual toxicity has been reported to date. To address this issue, we first extracted toxicity-related human gene information from the CTD, and then, using comparative genomics techniques and retrieving information from animal databases, we gathered the corresponding genes from the mouse and rat. The CTD (Comparative Toxicogenomics Database), dbSNP, RGD (Rat Genome Database), MGI (Mouse Genome Informatics), NHGRI Genome-Wide Association Studies, JMDBASE (Japan Metabolic Disease Database) and GAD (Genetic Association Database) were used as original information sources. The dbSNP was used as a major polymorphism data source, and other related databases were also used to find disease-and/or toxicity-related SNPs. The MS-SQL server was used as a database management system and ASP was used to construct a database-web interface. The result of our efforts is TOXPO (TOXicogenomics knowledgebase for inferring toxicity based on POlymorphism), the first database managing toxicogenomics information based on genomic variation. This database is freely available on website http://163. 180.41.43/toxpo.