목적 : 뇌졸중 이후 우세손이 마비된 경우 기능회복 정도가 비우세손의 손상보다 더 높을 것이라는 관측이 존재하지만 이에 대한 국내 연구 자료는 부족하기 때문에 후향적 코호트 조사를 통해 우세손의 마비 유무에 따른 기능회복의 변화를 조사함으로써 작업치료 중재전략에 응용할 수 있는 자료를 제공하고자 한다. 연구방법 : 5개 의료기관에서 1차 대상자(n=205)를 모집한 후 일반적 특성 및 뇌졸중 관련 특성, 적용된 평가도구 등을 조사하고 발병일에서 초기평가일까지의 기간이 6개월 이내인 2차 대상자(n=122)를 선별하여 평가기록 자료를 수집하였다. 적용된 평가도구에 대한 빈도분석을 통하여 6개의 평가도구를 선정하였다(Modified Barthel Index; MBI, Maunual Function Test; MFT, Hand Strength Test; HST, Nine-Hole Pegboard test; NHP, Functional Independence Measure; FIM, Box and Block Test; BBT). 평가기록은 평가기간(초기, 3개월 후, 6개월 후)에 따라 자료를 수집한 후 통계학적 분석을 실시하였다. 결과 : HST, NHP, BBT에서 우세손 마비 유무에 따른 차이가 있었고(p<.001), MBI는 평가기간에 따른 차이만(p<.05) 보였으며 우세손 마비유무와 평가기간의 상호작용효과는 존재하지 않았다(p>.05). 우세손 마비 환자의 HST(lateral pinch, palmar pinch)와 BBT의 변화량은 비우세손 마비 환자보다 유의한 차이(p<.05)로 더 높았지만 그 외 평가결과에서는 통계학적 유의한 차이를 보이지 않았다(p>.05). 결론 : 본 연구를 통해 추후 뇌졸중으로 인한 편마비 환자의 다양한 작업치료 중재전략에 응용할 수 있을 것이라고 희망한다.

To understand molecular and cellular mechanisms of many gene products in the female reproductive organs including the ovary and uterine endometrium as well as during embryo development, researchers have developed and utilized many effective methodologies to analyze gene expression in cells, tissues and animals over the last several decades. For example, blotting techniques have helped to understand molecular functions at DNA, RNA and protein levels, and the reverse transcription-polymerase chain reaction (RT-PCR) method has been widely used in gene expression analysis. However, some conventional methods are not sufficient to understand regulation and function of genes expressed in very complex patterns in many organs. Thus, it is required to adopt more high-throughput and reliable techniques. Here, we describe several techniques used widely recently to analyze gene expression, including annealing control based-PCR, differential display-PCR, expressed sequence tag, suppression subtractive hybridization and microarray techniques. Use of these techniques will help to analyze expression pattern of many genes from small scale to large scale and to compare expression patterns of genes in one sample to another. In this review, we described principles of these methodologies and summarized examples of comparative analysis of gene expression in female reproductive organs with help of those methodologies.

Since the birth of Dolly using fully differentiated somatic cells as a nuclear donor, viable clones were generated successfully in many mammalian species. These achievements in animal cloning demonstrate developmental potential of terminally differentiated somatic cells. At the same time, the somatic cell nuclear transfer (SCNT) technique provides the opportunities to study basic and applied biosciences. However, the efficiency generating viable offsprings by SCNT remains extremely low. There are several explanations why cloned embryos cannot fully develop into viable animals and what factors affect developmental potency of reconstructed embryos by the SCNT technique. The most critical and persuasive explanation for inefficiency in SCNT cloning is incomplete genomic reprogramming, such as DNA methylation and histone modification. Numerous studies on genomic reprogramming demonstrated that incorrect DNA methylation and aberrant epigenetic reprogramming are considerably correlated with abnormal development of SCNT cloned embryos even though its mechanism is not fully understood. The SCNT technique is useful in cloning farm animals because pluripotent stem cells are not established in farm animal species. Therapeutic cloning combined with genetic manipulation will help to control various human diseases. Also, the SCNT technique provides a chance to overcome excessive demand for the organs by production of transgenic animals as xenotransplantation resources. Here, we describe the factors affecting the efficiency of generating cloned farm animals by the SCNT technique and discuss future directions of animal cloning by SCNT to improve the cloning efficiency.

Many researches and analyses have been focused on industrial accidents in order to predict and reduce them. As a similar endeavor, this paper is to develop an expert system for prevention of industrial accidents. Although various previous studies have been performed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. As an initial step for the purpose of this study, this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and Answer Tree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work was chosen from 10,536 data related to manufacturing industries during three years(2002~2004) in korea. The initial sample includes a range of different businesses including the construction and manufacturing industries, which are typically vulnerable to industrial accidents.

The consequences of rapid industrial advancement, diversified types of business and unexpected industrial accidents have caused a lot of damage to many unspecified persons both in a human way and a material way Although various previous studies have been analyzed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. The main objective of this study is to find an optimal algorithm for data analysis of industrial accidents and this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and AnswerTree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work chosen from 19,574 data related to construction industries during three years (2002~2004) in Korea.

Many researches have been focused on the analysis of industry disasters in order to reduce them. As a similar endeavor, this paper provides a propensity analysis of injured people from various industries using classification and regression tree(CART), a data mining algorithm. The sample for this work was chosen from 25,157data related to various industries during one year ( 2003.2~2004.1 ) at Kangwon-Do in Korea. For the purpose of this paper, eight independent variables (injured date, injured time, injured month, type of Injured person, continuous service period, sex, company size, age)are taken from injured person group. According to the analysis result, it is found that five out of the eight factors that are predicted as significant have salient effects. Factors of season, time/hour, day of the week, or month which disasters happened do not show any significant effect. This paper provides common features of injured people. The provided analysis result will be helpful as a starting point for root cause analysis and reduction of industry disasters and also for development of a guideline of safety management.