• 한국환경보건학회:학술대회논문집
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• 한국환경보건학회 2002년도 춘계 국제 학술대회
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• pp.9-12
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• 2002

Diffusive transport of volatile organic compounds(VOCs) and their degradation by bacteria in unsaturated soils are couple by poorly understood mass transfer kinetics at the gas/water interface. Determination of the fate of VOCs in unsaturated soil is necessary to evaluate the feasibility of natural attenuation as a VOC remediation strategy. The objective of this study was to develop a mechanistically based mathematical model that would consider the interdependence of VOC transport, microbial activity, and sorptive interaction in a moist, unsaturated soil. Because the focus of the model was on description of natural attenuation, the advective VOC transport that is induced in engineered remediation processes such as vapor extraction was not considered. The utility of the model was assessed through its ability to describe experimental observations form diffusion experiments using toluene as a representative VOC in well-defined soil columns that contained a toluene degrading bacterium, Pseudomonas Putida, as the sole active microbial species. The coefficient for gas-liquid mass-transfer, K$\sub$LA/, was found to be a key parameter controlling the ability of bacteria to degrade VOCs. This finding indicates that soil size and geometry are likely to be important parameters in assessing the possible success of natural attenuation of VOCs in contaminated unsaturated soils.

• 환경위생공학
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• 제19권4호
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• pp.19-24
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• 2004

The objective of this study was to develop a mechanistically based mathematical model that would consider the interdependence of VOCs transport, microbial activity, and sorptive interactions in a moist, unsaturated soil. Because the focus of the model was on description of natural attenuation, the advective VOCs transport that is induced in engineered remediation processes such as vapor extraction was not considered. The utility of the model was assessed through its ability to describe experimental observations from diffusion experiments using toluene as a representative VOCs in well-defined soil columns that contained a toluene degrading bacterium, Pseudomonas putida G7 md Fl, as the sole active microbial species. The gas-liquid mass-transfer was found to be a key parameter controlling the ability of bacteria to degrade VOCs. This finding indicates that soil size and geometry are likely to be important parameters in assessing the possible success of natural attenuation of VOCs in contaminated unsaturated soils. Therefore we found that Pseudomonas putida G7 and Fl were very effective to remove of refractory pollutants such as toluene in soil by Bio-filter

• 한국발생생물학회지:발생과생식
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• 제26권4호
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• pp.145-153
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• 2022

The gut microbiota is involved in the maintenance of physiological homeostasis and is now recognized as a regulator of many diseases. Although germ-free mouse models are the standard for microbiome studies, mice with antibiotic-induced sterile intestines are often chosen as a fast and inexpensive alternative. Pathophysiological changes in the gut microbiome have been demonstrated, but there are no reports so far on how such alterations affect the bacterial composition of the uterus. Here we examined changes in uterine microbiota as a result of gut microbiome disruption in an antibiotics-based sterile-uterus mouse model. Sterility was induced in 6-week-old female mice by administration of a combination of antibiotics, and amplicons of a bacteria marker gene (16S rRNA) were sequenced to decipher bacterial community structures in the uterus. At the phylum-level, Proteobacteria, Firmicutes, and Actinobacteria were found to be dominant, while Ralstonia, Escherichia, and Prauserella were the major genera. Quantitative comparisons of the microbial contents of an antibiotic-fed and a control group revealed that the treatment resulted in the reduction of bacterial population density. Although there was no significant difference in bacterial community structures between the two animal groups, β-diversity analysis showed a converged profile of uterus microbiotain the germ-free model. These findings suggest that the induction of sterility does not result in changes in the levels of specific taxa but in a reduction of individual variations in the mouse uterus microbiota, accompanied by a decrease in overall bacterial population density.

• 한국물환경학회지
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• 제40권4호
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• pp.179-194
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• 2024

Biophysicochemical processes in water environments and treatment systems have been great concerns of engineers and scientists for controlling the fate and transport of contaminants. These processes are practically formulated as mathematical models written in coupled differential equations. However, because these process-based mathematical models consist of a large number of model parameters, they are complicated in analytical or numerical computation. Users need to perform substantial trials and errors to achieve the best-fit simulation to measurements, relying on arbitrary selection of fitting parameters. Therefore, this study adopted a Bayesian calibration method to estimate best-fit model parameters in a systematic way and evaluated the applicability of the calibration method to biophysicochemical processes of water environments and treatment systems. The Bayesian calibration method was applied to the microbial growth-decay kinetics and flocculation kinetics, of which experimental data were obtained with batch kinetic experiments. The Bayesian calibration method was proven to be a reasonable, effective way for best-fit parameter estimation, demonstrating not only high-quality fitness, but also sensitivity of each parameter and correlation between different parameters. This state-of-the-art method will eventually help scientists and engineers to use complex process-based mathematical models consisting of various biophysicochemical processes.

• 한국컴퓨터정보학회논문지
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• 제10권1호
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• pp.93-100
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• 2005

본 연구는 신규 임상병리사로 하여금 보다 정확한 의사결정과 효율적인 교육에 이용할 수 있는 지식 및 내용 기반 의료 세균화상 검색 시스템을 설계 및 구현하는 것이다. 이를 위해, 먼저 알고리듬방식의 검색 이전에 경험적 지식을 바탕으로 세균동정단계 중 가장 빠른 경로를 탐색하여 원인균 동정에 소요되는 시간을 줄일 수 있도록 룰 베이스를 근거로 유연성 있는 탐색경로를 설정하여 전체적인 추론을 수행한다. 다음으로, 색상 모델 중에서 HSV 컬러 모델을 이용하여 세균화상 중에서도 특히 세균화상으로부터 시각정보의 색상 특징 벡터를 추출할 수 있는 색상 특징 추출방법을 제안한다. 아울러 대용량 세균화상 데이터베이스를 기반으로 보다 빠른 검색 성능을 위해, 배지, 검체, 부서, 세균명과 같은 단순속성들에 대해서는 B+-트리, 세균화상에 대한 부가적인 설명 정보로부터 추출한 키워드들에 대해서는 역화일기법, 그리고 화상으로부터 추출한 고차원 색상 특징벡터에 대해서는 스캔-기반 필터링(Scan-Based Filtering:SBF) 기법을 결합한 통합 색인기법을 기술한다. 마지막으로 구현된 시스템은 시각적인 내용 자체의 정보와 지식을 이용하여 효과적으로 복잡한 세균화상을 검색 및 관리할 수 있는 가능성을 보인다. 아울러 구현한 지식 및 내-용기반 세균화상 검색 시스템을 통해 임상분야의 지식을 잘 구조화함으로써 초보적인 임상병리사의 학습기간을 현저히 단축시킬 수 있을 것으로 기대된다.

• KSBB Journal
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• 제24권4호
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• pp.397-402
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• 2009

본 연구에서는 몇 가지 생물공학 기반 기술로서 이미 한방 화장품의 소재로 사용되고 있는 쇠비름 에탄올 추출액의 tyrosinase 저해, collagen 합성, 항염증 기대 효과, 항노화 대한 효능을 알아보기 위하여 B16F10 mouse melanoma cell, NIH3T3 mouse embryonic fibroblast, MCF-7 human breast adenocarcinoma cell에 쇠비름 추출액을 처리하여 실험하였다. 실험 결과, 쇠비름 에탄을 추출액 (0.5mg/mL)은 tyrosinase 발현을 억제하여 멜라닌 합성을 억제하며, 농도 의존적으로 NIH3T3 mouse fibroblast 세포의 collagen 합성을 촉진시켰다. 또한 2.0 mg/mL 농도의 쇠비름 추출액은 목단피보다 더욱 효과적으로 cytokine (TNF-$\alpha$)에 의한 NF-${\kappa}B$ 활성을 억제시켰다. Doxorubicin에 의한 과노화에서도 효과적인 항노화 작용을 하는 것으로 나타났다. Tyrosinase 합성을 억제하므로 미백에 대한 효과와 세포의 생장을 도와 collagen 합성을 촉진함으로서 노화방지에 효과적인 것으로 사료되며, TNF-$\alpha$에 의한 NF-${\kappa}B$의 활성화를 저해함으로서 염증반응 억제 효과도 기대 할 수 있다.

• 생명과학회지
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• 제31권8호
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• pp.761-770
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• 2021

본 연구에서는 반응표면분석법을 이용하여 전통발효식품인 막걸리로부터 분리한 Bacillus amyloliquefaciens SRCM115785 균주에 대하여 protease 생산량을 증가시키기 위한 배지의 최적 농도를 확립하고자 하였다. 선정한 11개의 배지 성분 중 각 성분이 protease 생산에 미치는 영향에 대한 분석을 위해 Plackett-Burman design (PBD)를 설계하여 통계분석한 결과 glucose, yeast extract, beef extract를 protease 생산 향상을 위한 요인으로 최종 선별하였다. 선별된 3개의 성분에 대해 protease 생산을 위한 각 성분별 최적 농도를 결정하기 위해 central composite design (CCD)분석을 설계하여 protease 최대 생산을 위한 각 배지조성별 농도는 glucose 6.75 g/l, yeast extract 12.42 g/l, beef extract 17.48 g/l로 예측되었다. ANOVA 분석을 통해 실험모델의 적합성을 증명하였고, 설계한 최적배지에서 반복실험을 진행하여 protease 생산량을 측정한 결과 예측값과 매우 유사한 값을 나타냄을 확인하였다. 최종적으로 일반 배지에 비해 137% 환이 증가하였으며, 추가로 정량 분석 결과 기존 25.72 U/ml 대비 59.28 U/ml로 230.47% 증가함을 확인하였다. 본 연구를 통해 protease 생산량 증가를 위한 배지 성분의 최적화를 확립하였고, 이를 바탕으로 산업용 효소로서 protease의 효율적인 활용방안에 대한 기초자료로서 활용될 수 있을 것으로 기대된다.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.575-587
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• 2015

The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

• 한국농공학회논문집
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• 제55권3호
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• pp.105-111
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• 2013

Probability distribution of microbes in wastewater is a crucial factor to be determined for microbial risk assessment associated with its reuse. The objective of this study was to investigate probability distribution of an indicator microorganism in wastewater. Daily total coliform counts measured from nationwide wastewater treatment plants in 2010 by the Ministry of Environment were used for statistical analysis. Basic statistics and probability distributions were estimated in the three different spatial scales using the MS Excel software and FARD2006 model. Overall, wastewater from manure and livestock treatment plants demonstrated greater median coliform counts than from sewage and village treatment plants. Generalized logistic (GLO) and 2-parameter Weibull (WBU2) appeared to be the two probability distributions that fitted best for total coliform numbers in wastewater. The study results of microbial statistics and probability distributions would provide useful data for quantitative assessment of microbial risk from agricultural wastewater reuse.

• Asian-Australasian Journal of Animal Sciences
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• 제29권8호
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• pp.1188-1196
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• 2016

This study evaluated the risk of Clostridium perfringens (C. perfringens) foodborne illness from natural and processed cheeses. Microbial risk assessment in this study was conducted according to four steps: hazard identification, hazard characterization, exposure assessment, and risk characterization. The hazard identification of C. perfringens on cheese was identified through literature, and dose response models were utilized for hazard characterization of the pathogen. For exposure assessment, the prevalence of C. perfringens, storage temperatures, storage time, and annual amounts of cheese consumption were surveyed. Eventually, a simulation model was developed using the collected data and the simulation result was used to estimate the probability of C. perfringens foodborne illness by cheese consumption with @RISK. C. perfringens was determined to be low risk on cheese based on hazard identification, and the exponential model ($r=1.82{\times}10^{-11}$) was deemed appropriate for hazard characterization. Annual amounts of natural and processed cheese consumption were $12.40{\pm}19.43g$ and $19.46{\pm}14.39g$, respectively. Since the contamination levels of C. perfringens on natural (0.30 Log CFU/g) and processed cheeses (0.45 Log CFU/g) were below the detection limit, the initial contamination levels of natural and processed cheeses were estimated by beta distribution (${\alpha}1=1$, ${\alpha}2=91$; ${\alpha}1=1$, ${\alpha}2=309$)${\times}$uniform distribution (a = 0, b = 2; a = 0, b = 2.8) to be -2.35 and -2.73 Log CFU/g, respectively. Moreover, no growth of C. perfringens was observed for exposure assessment to simulated conditions of distribution and storage. These data were used for risk characterization by a simulation model, and the mean values of the probability of C. perfringens foodborne illness by cheese consumption per person per day for natural and processed cheeses were $9.57{\times}10^{-14}$ and $3.58{\times}10^{-14}$, respectively. These results indicate that probability of C. perfringens foodborne illness by consumption cheese is low, and it can be used to establish microbial criteria for C. perfringens on natural and processed cheeses.