Biomedical subjects

Seo Young Kim

Publications and source records attributed to Seo Young Kim.

5 recordsLinked to original sources

PubMed2025

Rice E3 ligase OsRFPH2-16 acts as a negative regulator to mediate the degradation of OsPIP1;1 under salt stress.

Soil salinity has a significant negative effect on rice productivity. We characterized the Oryza sativa RING Finger Protein H2-type-16 gene (OsRFPH2-16), which plays a negative role in response to salinity. The transcript levels of OsRFPH2-16 decreased under saline conditions. OsRFPH2-16 was expressed in the ER and tonoplasts of rice protoplasts. In addition, OsRFPH2-16 exhibited E3 ligase activity in an in vitro ubiquitination assay, whereas the mutant OsRFPH2-16C188A E3 ligase did not exhibit any activity. We constructed OsRFPH2-16-overexpressing (OX-2 and OX-4) and CRISPR/Cas9-mediated OsRFPH2-16-knockout (KO-4 and KO-16) plants and evaluated their salt responses. Under salt stress, OsRFPH2-16-knockout plants exhibited improved salt tolerance, characterized by low Na+ accumulation, high non-antioxidant content, and dynamic changes in the expression levels of Na+ transporter genes, compared with wild-type and OsRFPH2-16-overexpression plants. The aquaporin OsPIP1;1, an interacting partner, was identified using yeast two-hybridization, bimolecular fluorescence complementation, and pull-down assays. Degradation of OsPIP1;1 by the E3 ligase OsRFPH2-16 via the 26S proteasome system was confirmed through an in vitro degradation assay with the inhibitor MG132. These findings support that the E3 ligase functions as a negative regulator, leading to reduced Na+ accumulation in salt stress responses.

Oryza↗

PubMed2006

Effect of data normalization on fuzzy clustering of DNA microarray data.

BACKGROUND: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. RESULTS: In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. CONCLUSION: Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods when samples have varying expression patterns or are noisy. In particular, the FCM method slightly outperformed the hard clustering methods when the expression patterns of genes overlapped and was advantageous in finding co-regulated genes. Thus, the FCM approach offers a convenient method for finding subsets of genes that are strongly associated to a given cluster.

Algorithms↗

PubMed2006

Comparison of various statistical methods for identifying differential gene expression in replicated microarray data.

DNA microarray is a new tool in biotechnology, which allows the simultaneous monitoring of thousands of gene expression in cells. The goal of differential gene expression analysis is to identify those genes whose expression levels change significantly by the experimental conditions. Although various statistical methods have been suggested to confirm differential gene expression, only a few studies compared the performance of the statistical tests. In our study, we extensively compared three types of parametric methods such as T-test, B-statistic and Bayes T-test and three types of non-parametric methods such as samroc, significance analysis of microarray and a modified mixture model using both the simulated datasets and the three real microarray experiments.

Gene Expression↗

PubMed2005

Management of aortic disease in Marfan Syndrome: a decision analysis.

BACKGROUND: Marfan syndrome is a relatively common heritable disorder of connective tissue that affects numerous organ systems, but the most severe complication is aortic aneurysm and dissection. A variety of medical and surgical approaches are available for managing the cardiovascular complications. Our objective was to compare elective composite graft surgery, elective valve-sparing surgery, and medical management for patients with both Marfan syndrome and thoracic aortic disease on the basis of life expectancy with differing diameters of the aortic root and rate of increase in the aortic root size. METHODS: A Markov decision analysis model was constructed to compare the 2 surgical options with watchful waiting with medical therapy. RESULTS: For our base-case analysis of a 20-year-old patient with Marfan syndrome and thoracic aortic aneurysm, the aortic valve-sparing option was preferred. It extended life expectancy to 73.8 years compared with the medical treatment option (71.4 years) and with the composite graft surgery (72.7 years). Our results show that there is a better outcome for a patient with an aortic root diameter between 3.0 and 3.5 cm with early prophylactic surgery than with deferred or emergency surgery. Medical treatment was preferred when the aortic root diameter was smaller than 3.0 cm. CONCLUSIONS: Although long-term follow-up data are not yet available, it appears that advances in the technique of valve-sparing surgery have made it the preferred option to composite graft, primarily to avoid the complications of anticoagulation. Our study indicates that patients who have an aortic root diameter of larger than 3.0 cm should be considered for prophylactic aortic surgery.

Adult↗

PubMed2004

Cytoplasmic fraction of Lactococcus lactis ssp. lactis induces apoptosis in SNU-1 stomach adenocarcinoma cells.

Lactic acid bacteria are known to have antitumor activity, but the underlying mechanisms remain unclear. Recently we showed that a cytoplasmic fraction - but not peptidoglycan - of Lactococcus lactis ssp. lactis (L.lac CF) had strong antiproliferative activity on SNU-1 human stomach adenocarcinoma cells. The present study investigated whether the antiproliferative activity of L.lac CF on SNU-1 is linked to the induction of apoptosis. Treatment of L.lac CF inhibited the proliferation of SNU-1 cells in a dose- and time-dependent manner. Furthermore, treatment of the cells with 50 microg/ml and 100 microg/ml L.lac CF resulted in DNA fragmentation and chromatin condensation, respectively. The results indicate that the inhibitory effect of L.lac CF on SNU-1 cell growth is mainly attributable to the induction of apoptosis.

Adenocarcinoma↗