• Journal of Korean Society of Environmental Engineers
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• v.30 no.3
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• pp.302-313
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• 2008

The purposes of this study are to investigate the concentration levels of fine particles, so called PM$_{2.5}$, to identify the affecting sources, and to estimate quantitatively the source contributions of PM$_{2.5}$. Ambient air sampling was seasonally carried out at two sites in Pohang(a residential and an industrial area) during the period of March to December 2003. PM$_{2.5}$ samples were collected by high volume air samplers with a PM$_{10}$ Inlet and an impactor for particle size segregation, and then determined by gravimetric method. The chemical species associated with PM$_{2.5}$ were analyzed by inductively coupled plasma spectrophotometery(ICP) and ion chromatography(IC). The results showed that the most significant season for PM$_{2.5}$ mass concentrations appeared to be spring, followed by winter, fall, and summer. The annual mean concentrations of PM$_{2.5}$ were 36.6 $\mu$g/m$^3$ in the industrial and 30.6 $\mu$g/m$^3$ in the residential area, respectively. The major components associated with PM$_{2.5}$ were the secondary aerosols such as nitrates and sulfates, which were respectively 4.2 and 8.6 $\mu$g/m$^3$ in the industrial area and 3.7 and 6.9 $\mu$g/m$^3$ in the residential area. The concentrations of chemical component in relation to natural emission sources such as Al, Ca, Mg, K were generally higher at both sampling sites than other sources. However, the concentrations of Fe, Mn, Cr in the industrial area were higher than those in the residential area. Based on the principal component analysis and stepwise multiple linear regression analysis for both areas, it was found that soil/road dust and secondary aerosols are the most significant factors affecting the variations of PM$_{2.5}$ in the ambient air of Pohang. The source apportionments of PM$_{2.5}$ were conducted by chemical mass balance(CMB) modeling. The contributions of PM$_{2.5}$ emission sources were estimated using the CMB8.0 receptor model, resulting that soil/road dust was the major contributor to PM$_{2.5}$, followed by secondary aerosols, vehicle emissions, marine aerosols, metallurgy industry. Finally, the application and its limitations of chemical mass balance modeling for PM$_{2.5}$ was discussed.

• Journal of Chest Surgery
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• v.40 no.8
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• pp.552-557
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• 2007

Background: B-type natriuretic peptide (BNP) is a cardiac hormone that is primarily synthesized by the ventricular cardiac myocytes. Increased plasma BNP levels have been observed in patients suffering with congestive heart failure, ventricular hypertrophy and myocaridits and also during heart transplantation rejection. We investigated the serum BNP level as a predictive marker for rejection after heart transplantation. Material and Method: To test the usefulness of measuring the BNP level in cardiac transplant patients, consecutive blood samplings for BNP, right ventricular endomyocardial biopsies, hemodynamic measurements and transthoracic echocardiogram were all done in 10 such patients between January 2004 and August 2005 at the Department of Thoracic and Cardiovascular Surgery in Asan Medical Center. Two groups were identified with using the median value: the low BNP group (n=28, BNP: ${\le}290$ pg/mL) and the high BNP group (n=29, BNP: >290 pg/mL). We retrospectively analyzed rejection, the ejection fraction, tricuspid regurgitation, left ventricular hypertrophy, the pulmonary capillary wedge pressure and the right atrial pressure between the 2 groups. Result: There were no differences in age, gender, rejection, the ejection fraction, tricuspid regurgitation, left ventricular hypertrophy and the right atrial pressure between the 2 groups (p>0.05). However, a higher pulmonary capillary wedge pressure and a higher mean pulmonary atrial pressure were observed in the high BNP group (p<0.05). Further, BNP has linear correlation with the pulmonary capillary wedge pressure (r=0.590, p<0.001). Using the cut-off value of 620 pg/mL, the BNP predicted a high PCWP (>12 mmHg) with a sensitivity of 83.3% and a specificity of 91.1% (AUC: $0.900{\pm}0.045$, p<0.001). Conclusion: The BNP level after heart transplantation does not show any significant correlation with rejection, yet it might be a predictive marker of ventricular diastolic dysfunction.

• Journal of Life Science
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• v.20 no.7
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• pp.1012-1018
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• 2010

The aim of this study was to determine whether Alzheimer's amyloid precursor protein (APP) is dysregulated in adipose tissues of C57BL/6 male mice by high-fat diet (HFD) induced obesity, aging, or streptozotocin (STZ)-induced diabetes. APP mRNA expression was examined by quantitative real-time PCR (QPCR) in subcutaneous (SAT) and epididymal adipose tissues (EAT) from mice in 8 different condition groups. By combining conditions of age (16 weeks/26 weeks of age), diet (normal diet (ND)/high-fat diet), and induction of diabetes (non-diabetic/diabetic), 88 mice were divided into 8 different groups. QPCR demonstrated that APP expression in SAT was significantly increased by about two-fold in HFD-induced obese mice compared to both 16 week-old and 26 week-old mice in the ND group (16 weeks p=0.001; 26 weeks p<0.0001), but no changes in EAT was found. Particular effects of aging on APP gene expression were not observed in either adipose tissue depots. Significantly decreased APP expression was found in SAT in STZ-induced diabetic mice fed on ND or HFD at 16 weeks of age (ND p<0.05; HFD p<0.01). Linear regression analysis demonstrated that APP expression levels correlated with body weight in both the non-diabetic group (R=0.657, p<0.0001, n=39) and the diabetic group (R=0.508, p=<0.0001, n=49), but did not correlate with plasma glucose levels, which suggests that decreased APP expression in STZ-induced diabetic mice is most likely due to weight loss rather than hyperglycemia. These data confirm APP dysregulation by weight changes in humans and suggest a possible role linking midlife obesity with the later development of amyloidogenesis in the brain of older patients with Alzheimer's disease.