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Lee Woochan,Lee Seyoon,Yoon Jung-Ki,Lee Dakyung,Kim Yuri,Han Yeon Bi,Kim Rokhyun,Moon Sungjin,Park Young Jun,Park Kyunghyuk,Cha Bukyoung,Choi Jaeyong,Kim Juhyun,Ha Na-young,Kim Kwhanmien,Cho Sukki,Cho 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-
We present an in-depth single-cell atlas of in vitro multiculture systems on human primary airway epithelium derived from normal and diseased lungs of 27 individual donors. Our large-scale single-cell profiling identified new cell states and differentiation trajectories of rare airway epithelial cell types in human distal lungs. By integrating single-cell datasets of human lung tissues, we discovered immune-primed subsets enriched in lungs and organoids derived from patients with chronic respiratory disease. To demonstrate the full potential of our platform, we further illustrate transcriptomic responses to various respiratory virus infections in vitro airway models. Our work constitutes a single-cell roadmap for the cellular and molecular characteristics of human primary lung cells in vitro and their relevance to human tissues in vivo.
Yoo, Hyunjin,Park, Kyunghyuk,Lee, Jaehoon,Lee, Seunga,Choi, Yeonhee Korean Society for Molecular and Cellular Biology 2021 Molecules and cells Vol.44 No.8
DNA methylation is an important epigenetic mechanism affecting genome structure, gene regulation, and the silencing of transposable elements. Cell- and tissue-specific methylation patterns are critical for differentiation and development in eukaryotes. Dynamic spatiotemporal methylation data in these cells or tissues is, therefore, of great interest. However, the construction of bisulfite sequencing libraries can be challenging if the starting material is limited or the genome size is small, such as in Arabidopsis. Here, we describe detailed methods for the purification of Arabidopsis embryos at all stages, and the construction of comprehensive bisulfite libraries from small quantities of input. We constructed bisulfite libraries by releasing embryos from intact seeds, using a different approach for each developmental stage, and manually picking single-embryo with microcapillaries. From these libraries, reliable Arabidopsis methylome data were collected allowing, on average, 11-fold coverage of the genome using as few as five globular, heart, and torpedo embryos as raw input material without the need for DNA purification step. On the other hand, purified DNA from as few as eight bending torpedo embryos or a single mature embryo is sufficient for library construction when RNase A is treated before DNA extraction. This method can be broadly applied to cells from different tissues or cells from other model organisms. Methylome construction can be achieved using a minimal amount of input material using our method; thereby, it has the potential to increase our understanding of dynamic spatiotemporal methylation patterns in model organisms.
Park, Jin-Sup,Frost, Jennifer M.,Park, Kyunghyuk,Ohr, Hyonhwa,Park, Guen Tae,Kim, Seohyun,Eom, Hyunjoo,Lee, Ilha,Brooks, Janie S.,Fischer, Robert L.,Choi, Yeonhee National Academy of Sciences 2017 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.114 No.8
<P>The DEMETER (DME) DNA glycosylase initiates active DNA demethy-lation via the base-excision repair pathway and is vital for reproduction in Arabidopsis thaliana. DME-mediated DNA demethylation is preferentially targeted to small, AT-rich, and nucleosome-depleted euchromatic transposable elements, influencing expression of adjacent genes and leading to imprinting in the endosperm. In the female gametophyte, DME expression and subsequent genome-wide DNA demethylation are confined to the companion cell of the egg, the central cell. Here, we show that, in the male gametophyte, DME expression is limited to the companion cell of sperm, the vegetative cell, and to a narrow window of time: immediately after separation of the companion cell lineage from the germline. We define transcriptional regulatory elements of DME using reporter genes, showing that a small region, which surprisingly lies within the DME gene, controls its expression in male and female companion cells. DME expression from this minimal promoter is sufficient to rescue seed abortion and the aberrant DNA methylome associated with the null dme-2 mutation. Within this minimal promoter, we found short, conserved enhancer sequences necessary for the transcriptional activities of DME and combined predicted binding motifs with published transcription factor binding coordinates to produce a list of candidate upstream pathway members in the genetic circuitry controlling DNA demethylation in gamete companion cells. These data show how DNA demethylation is regulated to facilitate endosperm gene imprinting and potential transgenerational epigenetic regulation, without subjecting the germline to potentially deleterious transposable element demethylation.</P>
정수장 전염소 공정제어를 위한 침전지 잔류염소농도 예측 머신러닝 모형
김주환,이경혁,김수전,김경훈,Kim, Juhwan,Lee, Kyunghyuk,Kim, Soojun,Kim, Kyunghun 한국 수자원 학회 2022 한국수자원학회논문집 Vol.55 No.-
본 연구는 정수장의 수처리 공정에서 계측되고 있는 수량 및 수질데이터의 활용과 수처리 공정제어의 지능화를 위한 것으로 정수장에서 전염소 공정이 수반되는 처리공정에서 침전지 유출수 잔류염소농도 안정화를 위하여 이를 추정할 수 있는 모형을 구축하고자 하였다. 정수장 침전지 유출수의 잔류염소농도를 예측하기 위하여 중회귀모형과 인공지능 알고리즘 중 다층퍼셉트론 신경망, 랜덤포레스트 및 장단기기억(Long Short Term Memory; LSTM) 모형을 활용하였고 그 결과를 비교, 평가하였다. 모형의 입력변수로는 전염소 공정이 도입된 정수장에서의 잔류염소농도, 수온, 탁도, pH, 전기전도도, 유량, 알칼리도 등이 사용되었고 전염소에 따른 침전지의 안정적 운영을 위해 요구되는 침전지 잔류염소농도를 출력변수로 구성하였다. 적용 결과에서는 랜덤포레스트 모형이 가장 양호한 결과를 보여 주었으며 다음으로 LSTM, 다층퍼셈트론 신경망 순으로 나타났다. 수학적 모형인 중회귀모형은 적합도 측면에서 가장 낮은 결과를 보여 주었는데, 이는 수량과 수질데이터의 수치적인 규모나 차원의 차이뿐만 아니라 계절별 수질특성에 따라 염소소비 특성이 매우 다양하게 반응하기 때문으로 판단된다. 따라서 정수장 수처리 공정에서 인공지능 알고리즘의 적용을 위해서는 랜덤포레스트와 같이 의사결정 트리구조의 도입과 적용이 타당한 것으로 나타났다. 본 연구에서 분석된 결과를 근거로 전염소 공정이 도입된 정수장 수처리 공정에서 염소주입량을 실시간으로 예측 가능하게 함으로써 침전지 유출수에서 잔류염소농도를 일정하게 유지하는데 기여할 수 있을 것으로 기대된다. The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.
황우철(Woochul-Hwang),최현민(Hyunmin-Choi),이경혁(Kyunghyuk-Lee),김형태(Hyungtae-Kim),조진수(Jinsoo-Cho) 대한기계학회 2013 대한기계학회 춘추학술대회 Vol.2013 No.12
UV-disinfection technology has emerged over the recent years as drinking, waste and reuse water treatments methods for the inactivation of pathogenics. However design of UV-reactor is very complex task due to operating in water flow. The turbulent flow of water, UV light distribution and other related aspect should be considered. In this paper describes the procedure of full scale experiments for open channel type UV-reactor.