• Applied Biological Chemistry
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• v.38 no.6
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• pp.507-511
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• 1995

In an attempt to improve the productivity of ${\beta}-galactosidase$ from Bacillus sp. A1, which was isolated from soil and has remarkably higher transgalactosylation activity than lactose hydrolysis activity, a chemical mutation procedure using N-methyl-N'-nitro-N-nitrosoguanidine followed by selection was conducted. The final selection, designated as Bacillus sp. A4442, turned out to show a substantially increased enzyme productivity. Catabolite repression by glucose and lactose requirement as an inducer for the enzyme biosynthesis, which were shown in the parent strain, was markedly diminished; instead it was found out that galactose acts as another inducer. Because pH of medium, one of the most important factors for cell growth as well as enzyme production, is closely related with the sugar concentration during culture, it was kept in the optimum range of $6.5{\sim}7.5$; for this the initial glucose concentration was adjusted to be 0.5% which was thereafter maintained by the controlled pumping-in of lactose using the pH-stat technique. By doing so, we were able to increase the productivity of ${\beta}-galactosidase$ with high transgalactosylation activity up to $44\;unit/m{\ell}-broth$.

• YAKHAK HOEJI
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• v.34 no.6
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• pp.401-406
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• 1990

The Pharmacokinetics of furosemide (5 mg/kg iv) was investigated in rabbits with folate (75 mg/kg, 150 mg/kg 300 mg/ug, iv) induced renal failure. The plasma concentration was increased and urinary excretion was decreased significantly compared with those of normal rabbits. ${\alpha},\;{\beta}\;and\;K_{12},\;K_{21},\;K_{10}$ were decreased, $t_{1/2}$ and AUC were increased significantly. Correlation of serum creatinine concentration and AUC, renal clearance have linear relationship respectively. In short, dosage regimen of furosemide is considered to be adjusted in the dose size and the dosing interval by degree of serum creatinine concentration.

• Mycobiology
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• v.29 no.4
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• pp.210-217
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• 2001

Seventy-three species and five varieties belonging to 36 genera were collected from leaf surfaces of banana plants on glucose and cellulose-Czapek's agar at $28^{\circ}C$. The results obtained from leaf surfaces(phyllosphere and phylloplane) were basically similar on the two types of media and the most common fungi were Alternaria, Aspergillus, Chaetomium, Cladosporium, Cochliobolus, Curvularia, Gibberella, Memnoniella, Mycosphaerella, Setosphaeria and Stachybotrys. The monthly counts of these fungi were irregularly fluctuated giving maxima at various months. Chaetomium globosum was in the top of fungi in producing both exo- and endo-$\beta$-l,4-glucanases among the 34 tested isolates obtained from leaves(phylloplane) on cellulose-Czapek's agar. Maximum production of these enzymes by C. globosum was 6 and 8 days after incubation at $25^{\circ}C$ with culture medium containing wheat bran as a carbon source and peptone as a nitrogen source and initially adjusted to pH 6.

• Mycobiology
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• v.36 no.1
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• pp.1-9
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• 2008

Sixty three species and 5 varieties belonging to 30 fungal genera were collected from 75 soil samples. Cultivated (29 genera and 58 species + 5 var.), desert (22 and 35 + 2 var.) and saline soil (21 and 41 + 1 var.) fungi were recovered on glucose-, cellulose- and 50% sucrose-Czapek's agar at $28^{\circ}C$. The most common genera were Alternaria, Aspergillus, Emerieella, Fusarium, Mycosphaerella, Nectria and Penicillium. The most prevalent species from the three types of soils on the three types of media were Alternaria alternata, Aspergillus flavus, A. fumigatus, A. niger, A. terreus, Emerieella nidulans, Fusarium oxysporum, Myeosphaerella tassiana, Nectria haematococca and Penicillium ehrysogenum. Chaetomium globosum was in the top of fungi in producing endo-$\beta$-1,4-glucanases among the 42 tested isolates obtained from soils on cellulose-Czapek's agar. Maximum production of this enzyme by C. globosum obtained after 6 days of incubation at $30^{\circ}C$ with culture medium containing maltose as a carbon source and ammonium nitrate as a nitrogen source and pH initially adjusted to 6.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05d
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• pp.82-87
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• 1996

An optimized method for determining beta-emitting $^{241}$ Pu in the presence of alpha-emitting nuclides was developed using a liquid scintillation counting system. PSA-level was setting using pulse-shape discrimination. The $^{241}$ Pu counting channel was adjusted for maximum value of FM using the $^{241}$ Pu standard source. The volume of scintillant was determined for the maximum value of counting efficiency. The optimized method of $^{241}$ Pu has been applied to environmental samples to measure concentration of $^{241}$ Pu in soils and mosses. Also it has been identified the origin of Pu deposited in Korea from the activity ratio $^{241}$ Pu / $^{239,240}$Pu.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.101-109
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• 2011

The Riemann's zeta function $\zeta(s)$ has been known as answer for a number of primes $\pi$(x) less than given number x. In prime number theorem, there are another approximation function $\frac{x}{lnx}$,Li(x), and R(x). The error about $\pi$(x) is R(x) < Li(x) < $\frac{x}{lnx}$. The logarithmic integral function is Li(x) = $\int_{2}^{x}\frac{1}{lnt}dt$ ~ $\frac{x}{lnx}\sum\limits_{k=0}^{\infty}\frac{k!}{(lnx)^k}=\frac{x}{lnx}(1+\frac{1!}{(lnx)^1}+\frac{2!}{(lnx)^2}+\cdots)$. This paper shows that the $\pi$(x) can be represent with finite Li(x), and presents generalized prime counting function $\sqrt{{\alpha}x}{\pm}{\beta}$. Firstly, the $\pi$(x) can be represent to $Li_3(x)=\frac{x}{lnx}(\sum\limits_{t=0}^{{\alpha}}\frac{k!}{(lnx)^k}{\pm}{\beta})$ and $Li_4(x)=\lfloor\frac{x}{lnx}(1+{\alpha}\frac{k!}{(lnx)^k}{\pm}{\beta})}k\geq2$ such that $0{\leq}t{\leq}2k$. Then, $Li_3$(x) is adjusted by $\pi(x){\simeq}Li_3(x)$ with ${\alpha}$ and error compensation value ${\beta}$. As a results, this paper get the $Li_3(x)=Li_4(x)=\pi(x)$ for $x=10^k$. Then, this paper suggests a generalized function $\pi(x)=\sqrt{{\alpha}x}{\pm}{\beta}$. The $\pi(x)=\sqrt{{\alpha}x}{\pm}{\beta}$ function superior than Riemann's zeta function in representation of prime counting.

• Journal of Preventive Medicine and Public Health
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• v.43 no.4
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• pp.301-308
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• 2010

Objectives: In most DEHP exposure assessment studies, single spot urine sample was used. It could not compare the exposure level among studies. Therefore, we are going to represent the necessity of selection of proper sampling time of spot urine for assessing the environmental DEHP exposure, and the association urinary DEHP metabolites with steroid hormones. Methods: We collected urine and plasma from 25 men. The urine sampling times were at the end of the shift (post-shift) and the next morning before the beginning of the shift (pre-shift). Three metabolites of DEHP {mono(2-ethylhexyl) phthalate [MEHP], mono-(2-ethyl-5-hydroxyhexyl)phthalate [MEHHP], and mono(2-ethyl-5-oxohexyl)phthalate [MEOHP]} in urine were analyzed by HPLC/MS/MS. Plasma luteinzing hormone, follicle stimulating hormone, testosterone, and $17{\beta}$- estradiol were measured at pre-shift using a ELISA kit. A log-transformed creatinine-adjusted urinary MEHP, MEHHP, and MEOHP concentration were compared between the post- and pre-shift. The Pearson’s correlation was calculated to assess the relationships between log-transformed urinary MEHP concentrations in pre-shift urine and hormone levels. Results: The three urinary metabolite concentrations at post-shift were significantly higher than the concentrations in the pre-shift (p<0.0001). The plasma hormones were not significantly correlated with log-transformed creatinine - adjusted DEHP metabolites. Conclusions: To assess the environmental DEHP exposure, it is necessary to select the urine sampling time according to the study object. There were no correlation between the concentration of urinary DEHP metabolites and serum hormone levels.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7078-7088
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• 2015

This study examined effects of health behaviors and sleep related factor on cognitive function in the elderly hypertensive patients. Data were collected through a face to face interview survey with structured questionnaire form 140 elderly with hypertension ($age{\geq}65years$) from February 5 to May 1, 2013. Research instruments included Pittsburgh Sleep Quality Index(PSQI), Epworth Sleepiness Scale(ESS) and Korean version the Mini-Mental State Examination(MMSE-K). Cognitive function was negatively related to degradation in quality of sleep(r=-.29, p<.001). Sleep duration were negatively related to body mass index(r=-.18, p=.032) and degradation in quality of sleep(r=-.59, p<.001). Sleep duration was positively related to daytime sleepiness(r=.22, p=.008). Hierarchical multiple regression showed that age, education levels and living arrangement were associated with cognitive function(F=8.56, p<.001, Adjusted $R^2=.14$). After controlling for demographic characteristics and health behaviors, degradation in quality of sleep(${\beta}=-.27$, p=.008) was identified as significant predictors of cognitive function. This final model explained 17.0% of the cognitive function in the elderly hypertensive patients(F=4.09, p<.001). Therefore, as a strategy improving cognitive function of the elderly with hypertension, therapeutic intervention should be developed to improve quality of sleep considering age, education levels and living arrangement.

• Pediatric Infection and Vaccine
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• v.28 no.3
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• pp.149-159
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• 2021

Purpose: Antibiotic exposure during pregnancy may affect the fetus and newborn in many ways. This study investigated the impact of prenatal antibiotic exposure duration on neonatal outcomes in very preterm (VP) or very low birth weight (VLBW) infants. Methods: From September 2015 to December 2020, preterm infants with gestational age less than 32 weeks or with a BW less than 1,500 g who were admitted to the neonatal intensive care unit, and their mothers were enrolled. Prenatal antibiotic exposure was defined as antibiotics received by mothers before delivery, and the patients were categorized into the non-antibiotic group, short-duration (SD; ≤7 days) group, or long-duration (LD; >7 days) groups. Results: A total of 93 of 145 infants were exposed to prenatal antibiotics, among which 35 (37.6%) were in the SD group and 58 (62.4%) were in the LD group. Infants in the LD group had a significantly higher birth weight-for-gestational-age (BW/GA) Z-score than those in the non-antibiotic group, even after the adjustment for confounding factors (beta, 0.258; standard error, 0.149; P<0.001). Multivariate logistic regression analysis showed that prolonged prenatal antibiotic exposure was independently associated with death (adjusted odds ratio [aOR], 8.926; 95% confidence interval [CI], 1.482-53.775) and composite outcomes of death, necrotizing enterocolitis (NEC), and late-onset sepsis (LOS) (aOR, 2.375; 95% CI, 1.027-5.492). Conclusions: Prolonged prenatal antibiotic exposure could increase the BW/GA Z-score and the risk of death and composite outcomes of death, NEC, and LOS in VP or VLBW infants.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.573-579
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• 2019

The purpose of this study is predicted easily the entrance surface dose (ESD) in chest digital radiography. We used two detector type such as flat-panel detector (FP) and IP (Imaging plate detector). ESD was measured at each exposure condition combined tube voltage with tube current using dosimeter, after attaching on human phantom, it was repeated 3 times. Phantom images were evaluated independently by three chest radiologists after blinding image. Dose-area product (DAP) or exposure index (EI) was checked by Digital Imaging and Communications in Medicine (DICOM) header on phantom images. Statistical analysis was performed by the linear regression using SPSS ver. 19.0. ESD was significant difference between FP and IP($85.7{\mu}Gy$ vs. $124.6{\mu}Gy$, p=0.017). ESD was positively correlated with image quality in FP as well as IP. In FP, adjusted R square was 0.978 (97.8%) and linear regression model was $ESD=0.407+68.810{\times}DAP$. DAP was 4.781 by calculating the $DAP=0.021+0.014{\times}340{\mu}Gy$. In IP, adjusted R square was 0.645 (64.5%) and linear regression model was $ESD=-63.339+0.188{\times}EI$. EI was 1748.97 by calculating the $EI=565.431+3.481{\times}340{\mu}Gy$. In chest digital radiography, the ESD can be easily predicted by the DICOM header information.