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조인수,장경옥,박정식 한국정신지체아교육학회 2003 지적장애연구 Vol.5 No.-
21세기의 교육 사회의 변화에 발맞추어 특수교육에 있어서도 질적ㆍ양적으로 빠르게 발전하고 있다. 특히 지난 30여년간 양적으로 팽창되어온 특수학급은 특수교육 인구와 특수교육 기회의 저변확대의 도움과 영향에 커다란 의미를 지닌다. 하지만 특수학급 교육에서 양적인 팽창 못지 않게 질적인 변화를 도모하기 위해서는 일선 교육현장의 실태파악 및 문제점 도출에 힘써야 할 것이다. 이 연구는 중학교 특수학급에 자녀를 입급 시킨 학부모의 특수학급 교육여건, 교육내용, 교육운영에 대한 요구를 조사하여 분석함으로써 특수학급 교육의 문제점에 대한 개선방안을 모색하여, 보다 더 효율적인 특수학급 교육의 방안을 제시하고자 한다. The purpose of this study was to examine what parents required from secondary school special class education, in an effort to seek ways to resolve the problems with special class education and to discuss how it could be conducted better. Specifically, it's meant to find out parent needs for secondary school special class, educational condition, teaching contents and educational system. The following findings were acquired: First, regarding parent need for special classroom environment, the parents investigated found it necessary to prepare a separate space for individual guidance. Second, concerning what to teach, they demanded that students be assisted to be able to support themselves. Third, the parents considered it most necessary to prepare a sort of learning assistance room, which indicated that they called for integrated education environment. There are some suggestions: First, the subjects in this study were confined to the parents from south Gyeongsang province, but future research efforts need to examine a wide range of subjects nationwide. To meet the requirements of parents and students, sustained research is required. Second, the middle school special classes were investigated, but it's necessary to make studies of diverse approaches to find out what parents from high school needs and whether their needs are different according to the type of disability. Third, well-planned parent education should be provided to have parents pay more attention to physically different students and change their mind-set about them.
Jang, Kyeong-Su,Kim, Hong-Mo,Chung, Bong-Koo The Korean Society of Plant Pathology 2001 Plant Pathology Journal Vol.17 No.1
This study was undertaken to separate and identify antifungla substances produced by Gilocladium virens G1, a biocontrol agent used for the control of plant diseases caused by Rhizoctonea solani. The culture of G. virens G1 effectively inhibited the growth of R. solani, Colletotrichum gloeosporioides, and Phytophthora capsici, but less that of Fusarium oxysporum. The n-hexane extract of the G. virens culture, which was used for the purification of responsible substances, strongly inhibited R. solani and C. gloeosporioides, but not P. capsici, although the n-butanol extract was effective on all of the pathogens tested. An antifungal substance was purified using the n-hexane extract by Silica gel column chromatography and HPLC. The substance was examined for purity by HPLC and for nature by UV spectrometry, which differed from known antibiotic compounds such as gliotoxin, viridin and gliovirin. The antifungal substance was very liphophilic based on its solvent-solubility and Rf values on TLC, and more inhibitory to C. gloeosporioides than other fungal pathogens tested.
CDRgator: An Integrative Navigator of Cancer Drug Resistance Gene Signatures
Jang, Su-Kyeong,Yoon, Byung-Ha,Kang, Seung Min,Yoon, Yeo-Gha,Kim, Seon-Young,Kim, Wankyu Korean Society for Molecular and Cellular Biology 2019 Molecules and cells Vol.42 No.3
Understanding the mechanisms of cancer drug resistance is a critical challenge in cancer therapy. For many cancer drugs, various resistance mechanisms have been identified such as target alteration, alternative signaling pathways, epithelial-mesenchymal transition, and epigenetic modulation. Resistance may arise via multiple mechanisms even for a single drug, making it necessary to investigate multiple independent models for comprehensive understanding and therapeutic application. In particular, we hypothesize that different resistance processes result in distinct gene expression changes. Here, we present a web-based database, CDRgator (Cancer Drug Resistance navigator) for comparative analysis of gene expression signatures of cancer drug resistance. Resistance signatures were extracted from two different types of datasets. First, resistance signatures were extracted from transcriptomic profiles of cancer cells or patient samples and their resistance-induced counterparts for >30 cancer drugs. Second, drug resistance group signatures were also extracted from two large-scale drug sensitivity datasets representing ~1,000 cancer cell lines. All the datasets are available for download, and are conveniently accessible based on drug class and cancer type, along with analytic features such as clustering analysis, multidimensional scaling, and pathway analysis. CDRgator allows meta-analysis of independent resistance models for more comprehensive understanding of drug-resistance mechanisms that is difficult to accomplish with individual datasets alone (database URL: http://cdrgator.ewha.ac.kr).