Biomedical subjects

Sung-Hyun Kang

Publications and source records attributed to Sung-Hyun Kang.

3 recordsLinked to original sources

PubMed2006

Efficacy of protein A-HRP in an immunological study of black rockfish (Sebastes schlegeli Higendorf) humoral immune responses.

The efficacy of protein A-horse radish peroxidase (HRP), as compared to that of mouse polyclonal antibody raised against purified Ig, in detection of black rockfish (Sebastes schlegeli Higendorf) immunoglobulin (Ig) was examined. Protein A affinity chromatography successfully purified Ig from black rockfish serum; the purified-Ig could be visualised as two protein bands (MW 70 and 25kDa) following resolution with sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) under reducing conditions. In SDS-PAGE immunoblot profiles of the purified-Ig, the mouse polyclonal antibody recognised both the light chain and heavy chains of rockfish Ig, whereas protein A-HRP immunostained only the heavy chain of rockfish Ig. These results suggest that protein A-HRP may be used to detect rockfish antibody-antigen complexes in immunoassays. In a 2-DE immunoblot assay for exploring antigenic profiles of Lactococcus garvieae KG9408, protein A-HRP successfully detected specific antibodies to antigenic proteins of L. garvieae in the rockfish Ig. In addition, enzyme linked immunosorbent assay (ELISA) showed a high correlation between the results obtained for positivity of L. garvieae when protein A-HRP and the mouse polyclonal antibody-was used to analyse samples from 25 diseased rockfish. These results collectively indicate that protein A-HRP has a high affinity for Ig, and may be useful for new investigations into the humoral immune responses of rockfish.

Animals↗

PubMed2006

[Prevalence and associated factors of osteoporosis among postmenopausal women in Chuncheon: Hallym Aging Study (HAS)].

OBJECTIVES: A community-based, cross-sectional survey was conducted to determine theprevalence of osteoporosis and to evaluate the effects of body composition, health behaviors and reproductive history on bone density in postmenopausal women. METHODS: The study subjects were 362 postmenopausal women, aged 45 years old or over, who were invited to the hospital. Information on their socio-demographic characteristics and the potential risk factors such as their past medical history, smoking, alcohol intake, exercise, diet and menstrual/reproductive histories were collected by trained interviewers. Weight, height, the body mass index (kg/m2), and body composition variables were measured. Bone mineral density of the lumbar spine was measured by dual energy X-ray absorptiometry (DXA). RESULTS: The prevalence of osteoporosis was 30.6% in the 45-64 years old women, 52.5% in the elderly women aged 65-74, and 68.7% in the women aged 75 years or over. After adjustment for the effect of potential covariates, those women in the highest 25% (4th quartile) of the lean body mass are less likely to have osteoporosis (aOR=0.31, 95% CI=0.12-0.76), compared with the lowest quartile group. More parity also had significantly detrimental effects on osteoporosis. CONCLUSIONS: These findings suggest that the prevalence of osteoporosis in postmenopausal women increased with age from 46.3% of those aged 45-64 to 68.7% for those aged 75 and over. Lean body mass and parity appeared significant contributor to bone mineral density in postmenopausal women in this population.

Aged↗

PubMed2003

Evaluation of normalization methods for microarray data.

BACKGROUND: Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. This novel technique helps us to understand gene regulation as well as gene by gene interactions more systematically. In the microarray experiment, however, many undesirable systematic variations are observed. Even in replicated experiment, some variations are commonly observed. Normalization is the process of removing some sources of variation which affect the measured gene expression levels. Although a number of normalization methods have been proposed, it has been difficult to decide which methods perform best. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization. RESULTS: In this paper, we use the variability among the replicated slides to compare performance of normalization methods. We also compare normalization methods with regard to bias and mean square error using simulated data. CONCLUSIONS: Our results show that intensity-dependent normalization often performs better than global normalization methods, and that linear and nonlinear normalization methods perform similarly. These conclusions are based on analysis of 36 cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells. Simulation studies confirm our findings.

Analysis of Variance↗