• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제22권1호
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• pp.17-28
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• 2016

Purpose: The purpose of this paper is to analyze the spatial configurations of a sample of Korean regional emergency medical centers (REMCs) to explore its underlying genotypes and thus produce a base line data for the analysis and evaluations of future REMCs designs using space syntax theory. Methods: Space syntax analysis was used as a major tool for the analysis and exploration of Genotype. The measures of Integration(overall integration with exterior and without exterior as well as the integration of individual clinical spaces for each center), base difference factor (DF) and Space link ratio were calculated for a sample of seven Korean REMCs. Results: The result shows a strikingly similar pattern of Syntactic measures across the sample, the mean integration of sample ranges from 0.82-0.99 with exterior (while considering the exterior space as a root) and 0.81-1.01 without exterior (considering the connections of interior spaces only with no outside connection). The base difference factor (DF) of the sample varies from 0.60-0.81 with exterior and from 0.59-0.82 without exterior. Case number-1 was identified as non-genotype with differing order of Syntactic values. Although the genotype had different forms, layouts and even sizes, these results cannot be explained by Phenotypical comparisons. Implications: This study will contribute to the configurational analysis and evaluation of existing and future Korean REMCs design and practice of emergency healthcare delivery system in Korea.

• 대한치과교정학회지
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• 제51권5호
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• pp.337-345
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• 2021

Objective: To investigate the phenotypes and predominant skeletodental pattern in pre-adolescent patients with Pierre-Robin sequence (PRS). Methods: The samples consisted of 26 Korean pre-adolescent PRS patients (11 boys and 15 girls; mean age at the investigation, 9.20 years) treated at the Department of Orthodontics, Seoul National University Dental Hospital between 1998 and 2019. Dental phenotypes, oral manifestation, cephalometric variables, and associated anomalies were investigated and statistically analyzed. Results: Congenitally missing teeth (CMT) were found in 34.6% of the patients (n = 9/26, 20 teeth, 2.22 teeth per patient) with 55.5% (n = 5/9) exhibiting bilaterally symmetric missing pattern. The mandibular incisors were the most common CMT (n = 11/20). Predominant skeletodental patterns included Class II relationship (57.7%), posteriorly positioned maxilla (76.9%) and mandible (92.3%), hyper-divergent pattern (92.3%), high gonial angle (65.4%), small mandibular body length to anterior cranial base ratio (65.4%), linguoversion of the maxillary incisors (76.9%), and linguoversion of the mandibular incisors (80.8%). Incomplete cleft palate (CP) of hard palate with complete CP of soft palate (61.5%) was the most frequently observed, followed by complete CP of hard and soft palate (19.2%) and CP of soft palate (19.2%) (p < 0.05). However, CP severity did not show a significant correlation with any cephalometric variables except incisor mandibular plane angle (p < 0.05). Five craniofacial and 15 extra-craniofacial anomalies were observed (53.8% patients); this implicated the need of routine screening. Conclusions: The results might provide primary data for individualized diagnosis and treatment planning for pre-adolescent PRS patients despite a single institution-based data.

• Animal Bioscience
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• 제37권4호
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Asian Pacific Journal of Cancer Prevention
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• 제16권6호
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• pp.2465-2472
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• 2015

Background: The Quality Audit (BQA) program of the Breast Surgeons of Australia and New Zealand (NZ) collects data on early female breast cancer and its treatment. BQA data covered approximately half all early breast cancers diagnosed in NZ during roll-out of the BQA program in 1998-2010. Coverage increased progressively to about 80% by 2008. This is the biggest NZ breast cancer database outside the NZ Cancer Registry and it includes cancer and clinical management data not collected by the Registry. We used these BQA data to compare socio-demographic and cancer characteristics and survivals by ethnicity. Materials and Methods: BQA data for 1998-2010 diagnoses were linked to NZ death records using the National Health Index (NHI) for linking. Live cases were followed up to December $31^{st}$ 2010. Socio-demographic and invasive cancer characteristics and disease-specific survivals were compared by ethnicity. Results: Five-year survivals were 87% for Maori, 84% for Pacific, 91% for other NZ cases and 90% overall. This compared with the 86% survival reported for all female breast cases covered by the NZ Cancer Registry which also included more advanced stages. Patterns of survival by clinical risk factors accorded with patterns expected from the scientific literature. Compared with Other cases, Maori and Pacific women were younger, came from more deprived areas, and had larger cancers with more ductal and fewer lobular histology types. Their cancers were also less likely to have a triple negative phenotype. More of the Pacific women had vascular invasion. Maori women were more likely to reside in areas more remote from regional cancer centres, whereas Pacific women generally lived closer to these centres than Other NZ cases. Conclusions: NZ BQA data indicate previously unreported differences in breast cancer biology by ethnicity. Maori and Pacific women had reduced breast cancer survival compared with Other NZ women, after adjusting for socio-demographic and cancer characteristics. The potential contributions to survival differences of variations in service access, timeliness and quality of care, need to be examined, along with effects of comorbidity and biological factors.

• 한국정보과학회논문지:데이타베이스
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• 제41권4호
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• pp.249-255
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• 2014

유전체 단위 반복 변이(CNV)는 유전적 구조변이의 하나로서, 암을 포함하는 인간의 질병과 밀접한 연관성이 있는 것으로 알려져 있다. 암 유전자를 규명하기 위하여, 연구자는 특정 암 환자의 대규모 유전체 데이터를 분석하여 CNV를 찾아내야하며, 동시에 대규모 유전/임상 데이터를 연계 분석하여야 한다. 본 연구는 NGS 데이터로부터 CNV를 추출하고, 추출된 CNV와 관련된 유전/임상 정보를 체계적으로 연계 분석하는 기능을 제공하는 새로운 분석 툴 CNVDAT를 제안한다. CNV 추출 모듈은 스케일 스페이스 필터링 기법을 이용하여 CNV를 추출하며, 리드 데이터에 잡음이 포함된 경우에도 CNV의 타입/위치를 정확히 추출해낸다. 또한 시퀀스 분석 모듈은 변이 영역의 브라우징 및 상호 비교를 지원하는 사용자 친화적 프로그램으로서, 암/정상 샘플의 변이 영역의 동시 분석 기능과 refGene, OMIM DB를 기반으로 하는 CNV-유전자-표현형 매핑의 연관성 분석 기능을 제공한다. 본 프로그램의 소스 코드와 샘플프로그램은 http://dblab.hallym.ac.kr/CNVDAT/에서 다운 받을 수 있다.

• 정보처리학회논문지D
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• 제15D권6호
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• pp.767-776
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• 2008

마이크로어레이 기술은 최근 실험적 분자생물학 분야에서 활발히 사용되고 있는 기술이다. 마이크로어레이 데이터는 한 번의 실험으로 수 만개의 유전자에 대한 발현값을 얻을 수 있으므로, 여러 질병의 발현형질을 연구하는데 매우 유용하게 사용된다. 마이크로어레이 데이터의 문제점은 참여하는 유전자의 수에 비해 참여하는 샘플(생물조직샘플)의 수가 매우 적고, 분류분석 기법을 사용하여 얻어진 분류자의 해석이 어렵다는 점이다. 본 연구에서는 위의 문제점을 해결하고자, 샘플 내 순위를 이용하여 동일한 생물학적 목적으로 수행된 공개 마이크로어레이 데이터를 통합하고, 순위 비교를 기반으로 하는 다양한 유전자 개수로 이루어진 암 분류 결정 규칙들로 이루어진 분류자를 제안한다. 본 분류자는 k개의 규칙으로 이루어진 앙상블 방법을 기반으로 하며, 하나의 규칙은 최대N개의 유전자, 관련유전자간의 순위비교 관계식, 판별클래스로 이루어져 있다. 하나의 규칙에 참여하는 유전자의 수를 다양하게 함으로써 좀더 신뢰성 높은 분류자를 생성할 수 있다. 또한 본 분류자는 생물학적 해석이용이하며, 분류자를 구성하는 유전자를 명확히 식별할 수 있고, 총 개수가 많지 않으므로 임상환경에서의 사용가능성도 생각해 볼 수 있다.

• 농업생명과학연구
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• 제50권3호
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• pp.99-117
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• 2016

ssGBLUP을 이용한 전장 유전체 연관분석(ssGWAS)을 수행하기 위하여 이용한 표현형 자료는 2010년도부터 2015년까지 농협중앙회 한우개량사업소에서 후대 검정한 한우 거세우 총 1,829두의 부분육수율자료를 이용하였다. 유전체 자료는 Illumina Bovine 50K Beadchip을 활용하였으며 표현형 자료와 매칭이 되는 개체는 674두였다. 먼저 안심, 등심, 채끝 및 갈비수율의 유전체 육종가(GEBV)를 구하고 이를 통해 SNP 표지인자에 대한 효과와 SNP 표지인자의 분산을 계산하여 형질별 전체 유전분산 대비 SNP 표지인자의 효과를 추정한 후, QTL일 가능성이 있는 효과가 높은 SNP 좌위에 대한 결과를 주요하게 조사하였다. 안심수율의 경우, 상위 20개의 전체 유전분산 대비 SNP 표지인자의 효과에서 10번 염색체에서의 효과가 가장 높았는데 12,812,193 ~ 12,922,313bp 영역에서 전체 유전분산 대비 7.32 ~ 7.34%의 효과를 나타냈다. 채끝수율은 전체 유전분산에 대한 설명력이 가장 높은 SNP 표지인자를 포함하는 염색체는 24번 염색체로 38,158,543 ~ 38,347,278bp 영역이 약 8.36 ~ 8.56%의 전체 유전분산 대비 효과를 나타내었다. 등심수율은 다른 부분육 조사형질보다 낮은 SNP 표지인자의 효과를 나타내었다. 따라서 등심의 경우 보통 크기의 효과와 작은 효과를 갖는 많은 유전자들에 의해서 형질이 발현되는 것으로 사료된다.

• Journal of Microbiology
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• 제45권6호
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• pp.558-565
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• 2007

Using microarray analysis, we determined those Salmonella genes induced at the entry of stationary phase, and subsequently discovered that uncharacterized yliH was induced most dramatically. We set out to establish the molecular mechanism underlying the stationary phase induction of yliH under the standard culture condition, LB with vigorous aeration, by analyzing its promoter activity in various mutant backgrounds, lacking stationary phase ${\sigma}$, $RpoS^-$, or stringent signal molecules ppGpp, ${\Delta}relA$ ${\Delta}spoT$. It was found that the stationary phase induction of yliHp was partially dependent on rpoS but entirely dependent on ppGpp. DNA sequence analysis revealed that the Salmonella yliH gene is composed of 381 base-pair nucleotides, with overall amino acid sequence revealing 76.38% amino acid identity and 88.98% similarity with Escherichia coli yliH, although no motif from data base was noted for its possible role. Recently however, it has been reported that yliH in E. coli was implicated in biofilm formation and motility by repressing these activities (Domka et al., 2006). We have constructed a mutant Salmonella deleting yliH gene by allele replacement and examined its phenotype, and found that the yliH in Salmonella more or less affects motility and adherence by enhancing these activities. The effect on biofilm formation in Salmonella was uncertain. Moreover, addition of cloned yliH of E. coli into Salmonella did not reduce motility or adherence. Taken together, it appears that the pathways implicating yliH for biofilm formation and motility in E. coli and in Salmonella are somewhat different.

• International Journal of Oral Biology
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• 제34권4호
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• pp.177-183
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• 2009

Human mesenchymal stem cell (hMSCs) isolated from human adult bone marrow have self-renewal capacity and can differentiate into multiple cell types in vitro and in vivo. A number of studies have now demonstrated that MSCs can differentiate into various neuronal populations. Due to their autologous characteristics, replacement therapy using MSCs is considered to be safe and does not involve immunological complications. The basic helix-loop-helix (bHLH) transcription factor Olig2 is necessary for the specification of both oligodendrocytes and motor neurons during vertebrate embryogenesis. To develop an efficient method for inducing neuronal differentiation from MSCs, we attempted to optimize the culture conditions and combination with Olig2 gene overexpression. We observed neuron-like morphological changes in the hMSCs under these induction conditions and examined neuronal marker expression in these cells by RTPCR and immunocytochemistry. Our data demonstrate that the combination of Olig2 overexpression and neuron-specific conditioned medium facilitates the neuronal differentiation of hMSCs in vitro. These results will advance the development of an efficient stem cell-mediated cell therapy for human neurodegenerative diseases.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2221-2224
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• 2013

The glutathione S-transferases (GSTs) are a family of enzymes involved in the detoxification of a wide range of chemicals, including important environmental carcinogens, as well as chemotherapeutic agents. In the present study 294 acute leukemia cases, comprising 152 of acute lymphocytic leukemia (ALL) and 142 of acute myeloid leukemia, and 251 control samples were analyzed for GSTM1 and GSTT1 polymorphisms through multiplex PCR methods. Significantly increased frequencies of GSTM1 null genotype (M0), GSTT1 null genotype (T0) and GST double null genotype (T0M0) were observed in the both ALL and AML cases as compared to controls. When data were analyzed with respect to clinical variables, increased mean levels of WBC, Blast %, LDH and significant reduction in DFS were observed in both ALL and AML cases with T0 genotype. In conclusion, absence of both GST M & GST T might confer increased risk of developing ALL or AML. The absence of GST enzyme might lead to oxidative stress and subsequent DNA damage resulting in genomic instability, a hallmark of acute leukemia. The GST enzyme deficiency might also exert impact on clinical prognosis leading to poorer DFS. Hence GST genotyping can be made mandatory in management of acute leukemia so that more aggressive therapy such as allogenic stem cell transplantation may be planned in the case of patients with a null genotype.