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Optimization of DNA Microarray Biosensors Enables Rapid and Sensitive Detection
황병희,신화희,차형준 한국생물공학회 2017 Biotechnology and Bioprocess Engineering Vol.22 No.4
DNA microarray biosensors are essential tools for analyzing transcriptome expression levels and single nucleotide polymorphisms in disease pathology and diagnostics. Since rapid and quantitative detection is necessary for these applications, optimization of the experimental conditions is essential. Here, experimental conditions for DNA microarray biosensors were optimized using an artificial target strategy without reaction or purification bias. Most importantly, hybridization time was reduced to one hour for rapid and homogeneous detection of target DNA. High and low concentrations of capture probe are appropriate for optimizing the limit of detection and dynamic range, respectively. Bleaching effects can be minimized by measuring fluorescence intensity at night. These conditions enable quantitative and precise detection of target DNA and offer experimental guidelines for genobiosensors in general.
박지웅,강봉근,신화희,신준근,Park, Jeewoong,Kang, Bong Keun,Shin, Hwa Hui,Shin, Jun Geun 대한의용생체공학회 2021 의공학회지 Vol.42 No.3
The POCT (point-of-care test) sensing that has been a fast-developing field is expected to be a next generation technology in health care. The POCT sensors for the detection of proteins, small molecules and especially nucleic acids have lately attracted considerable attention. According to the World Health Organization (WHO), the POCT methods are required to follow the ASSURED guidelines (Affordable, Sensitive, Specific, User- friendly, Robust and rapid, Equipment-free, Deliverable to all people who need the test). Recently, several CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) based diagnostic techniques using the sensitive gene recognition function of CRISPR have been reported. CRISPR/Cas (Cas, CRISPR associated protein) systems based detection technology is the most innovative gene analysis technology that is following the ASSURED guidelines. It is being re-emerged as a powerful diagnostic tool that can detect nucleic acids due to its characteristics that enable rapid, sensitive and specific analyses of nucleic acid. The first CRISPR-based diagnosis begins with the discovery of the additional function of Cas13a. The enzymatic cleavage occurs when the conjugate of Cas protein and CRISPR RNA (crRNA) detect a specific complementary sequence of the target sequence. Enzymatic cleavage occurs on not only the target sequence, but also all surrounding non-target single-stranded RNAs. This discovery was immediately utilized as a biosensor, and numerous sensor studies using CRISPR have been reported since then. In this review, the concept of CRISPR, the characteristics of the Cas protein required for CRISPR diagnosis, the current research trends of CRISPR diagnostic technology, and some aspects to be improved in the future are covered.
민지영,문효정,신화희,이용찬 한국재활복지공학회 2023 재활복지공학회논문지 Vol.17 No.4
본 논문은 손 재활 로봇에 대한 연구 동향과 발전 방향을 이해하기 위해 조사하고 요약하는 것을 목표로한다. 최근 손 재활의 수요가 증가함에 따라 손 재활 로봇에 대한 연구는 활발하게 수행되고 있다. 손 재활은 다른 부위에 비해 높은 자유도와 복잡성을 가지며, 이를 효과적으로 치료하기 위해 다양한 형태의 로봇과 손 재활 방법이 연구되고 있다. 다양한 형태의 손 재활 로봇 분석을 위해 착용 형태, 사용자 의도 파악방식, 구동 방식으로 분류하여 정리하였다. 또, 손 재활 방법의 이해를 위해 제어 알고리즘, 재활 동작, 사용자-로봇 상호작용 내용으로 분류하였다. 결과적으로 손 재활 로봇의 최고 수준과 각 시스템의 성능을 분석하고 생체 데이터의 딥러닝, 재활 시스템에 인공지능 적용 등 향후 연구 방향을 제시하고자 한다. This paper aims to investigate and summarize to understand the research trends and development directions for hand rehabilitation robots. Recently, as the demand for hand rehabilitation increases, research on hand rehabilitation robots is being actively conducted. Hand rehabilitation has a higher degree of freedom and complexity compared to other parts, and various types of robots and hand rehabilitation methods are being studied to treat this effectively. To analyze various types of hand rehabilitation robots, they were categorized and organized into wearing type, user intention identification method, and driving method. In addition, to understand the hand rehabilitation method, it was classified into control algorithm, rehabilitation movement, and user-robot interaction content. As a result, we want to analyze the state-of-the-art of hand rehabilitation robots and the performance of each system and suggest future research directions, such as deep learning of biometric data and application of artificial intelligence to rehabilitation systems.