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Jung Kyeongmin,Yoon Joohyun,Ahn Yeeun,Kim Soyeon,Shim Injeong,Ko Hyunwoong,Jung Sang-Hyuk,Kim Jaeyoung,Kim Hyejin,Lee Dong June,Cha Soojin,Lee Hyewon,Kim Beomsu,Cho Min Young,Cho Hyunbin,Kim Dan Say,K 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-
Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.
Anesthetic management for cesarean delivery in a Guillain-Barré syndrome patient -A case report-
Hyunbin Kim,유정희,Jung-Won Hwang,Sang-Hwan Do 대한마취통증의학회 2013 Korean Journal of Anesthesiology Vol.64 No.3
Guillain-Barré syndrome is an acute inflammatory demyelinating polyradiculopathy characterized by progressive motor weakness, areflexia, and ascending paralysis. Guillain-Barré syndrome is extremely rare in pregnant patients, and there are no established guidelines for delivery or safest anesthetic methods. We report a Cesarean delivery in the case of a 32-year old woman who was diagnosed with Guillain-Barré syndrome 18 weeks into gestation. Tracheostomy was performed due to progressive respiratory muscle weakness and respiratory failure, and ventilator support was required in the intensive care unit. The respiratory difficulty was exacerbated by the growth of the fetus, necessitating emergency Cesarean delivery. The delivery was successfully performed under general anesthesia, and the patient recovered without neurological sequelae.
Hyunbin Kim,Yeonjung Han,Yonggun Park,Sang-yun Yang,Hyunwoo Chung,Chang-deuk Eom,Hyun-mi Lee,Hwanmyeong Yeo 한국목재공학회 2017 목재공학 Vol.45 No.6
Predicting the amount and distribution of moisture content within wood allows calculating the various mechanical dynamics of the wood as well as determining the drying time. For boxed-heart wood with a large cross-section, since it is difficult to measure the moisture content of the interior, it is necessary to predict the moisture content distribution. This study predicted the moisture movement in boxed-heart red pine timber, during high temperature drying, by using the three-dimensional finite difference method for the efficient drying process. During drying for 72 h, the predicted and actual moisture content of the tested wood tended to decrease at a similar rate. In contrast, the actual moisture content at 196 and 240 h was lower than predicted because surface checking of the wood occurred from 72 h and excessive water emission was unexpectedly occurred from the checked and splitted surface.
N ‐(Biphenyl‐3‐ylmethyl)ethanamines as G protein‐biased agonists of 5‐HT 7 R
Kim Doyoung,Lee Jieon,Kwag Rina,Kim Hyunbin,Oh Hyunji,문봉진,Kim Hak Joong,Seong Jihye,Jeon Byungsun,Kang Taek,Choo Hyunah 대한화학회 2022 Bulletin of the Korean Chemical Society Vol.43 No.1
There has been much attention to biased ligands of G protein-coupled receptors (GPCRs) for potential pharmacological benefits. Recently, we reported N- ((6-chloro-2’-methoxy-[1,1’-biphenyl]-3-yl)methyl)ethanamine 1 as G proteinbiased agonist of 5-HT7R, which could be used as a chemical probe for the study on treatment discovery of autism spectrum disorder. Herein, we describe the synthesis of derivatives of the compound 1 and their biological evaluations in both G protein and β-arrestin signaling pathway. Total 16 compounds were synthesized and evaluated, and the compounds 3c, 3f, 3i, and 3p could be called as G protein-biased agonists like the compound 1. Among the four compounds, the compound 3c was the best in efficacy with an Emax value of 73% and the compound 3f was the most potent agonist with an EC50 value of 0.094 μM.
( Hyunbin Kim ),( Mingyu Kim ),( Yonggun Park ),( Sang-Yun Yang ),( Hyunwoo Chung ),( Ohkyung Kwon ),( Hwanmyeong Yeo ) 한국목재공학회 2019 목재공학 Vol.47 No.2
목재의 결점은 생장과정에서 또는 가공 중에 다양한 형태로 발생한다. 따라서 목재를 이용하기 위해서는 목재의 결점을 정확하게 분류하여 용도에 맞는 목재 품질을 객관적으로 평가할 필요가 있다. 하지만 사람에 의한 등급구분과 수종구분은 주관적 판단에 의해 차이가 발생할 수 있기 때문에 목재 품질의 객관적 평가 및 목재 생산의 고속화를 위해서는 컴퓨터 비전을 활용한 화상분석 자동화가 필요하다. 본 연구에서는 SIFT+k-NN 모델과 CNN 모델을 통해 옹이의 종류를 자동으로 구분하는 모델을 구현하고 그 정확성을 분석해보고자 하였다. 이를 위하여 다섯 가지 국산 침엽수종으로부터 다양한 형태의 옹이 이미지 1,172개를 획득하여 학습 및 검증에 사용하였다. SIFT+k-NN 모델의 경우, SIFT 기술을 이용하여 옹이 이미지에서 특성을 추출한 뒤, k-NN을 이용하여 분류를 진행하였으며, 최대 60.53%의 정확도로 분류가 가능하였다. 이 때 k-index는 17이었다. CNN 모델의 경우, 8층의 convolution layer와 3층의 hidden layer로 구성되어있는 모델을 사용하였으며, 정확도의 최대값은 1205 epoch에서 88.09%로 나타나 SIFT+k-NN 모델보다 높은 결과를 보였다. 또한 옹이의 종류별 이미지 개수 차이가 큰 경우, SIFT+k-NN 모델은 비율이 높은 옹이 종류로 편향되어 학습되는 결과를 보였지만, CNN 모델은 이미지 개수의 차이에도 편향이 심하지 않아 옹이 분류에 있어 더 좋은 성능을 보였다. 본 연구 결과를 통해 CNN 모델을 이용한 목재 옹이의 분류는 실용가능성에 있어 충분한 정확도를 보이는 것으로 판단된다. Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.
Simple and Complex Obstacle Detection Using an Overlapped Ultrasonic Sensor Ring
Sungbok Kim,Hyunbin Kim 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
This paper presents both simple and complex obstacle detection using an ultrasonic sensor ring with overlapped beam pattern. It is assumed that a set of ultrasonic sensors of the same type are arranged along a circle of non-zero radius at regular spacings with their beams overlapped. To assess the positional uncertainty of an overlapped ultrasonic sensor ring in obstacle detection, the obstacle distances of three adjacent ultrasonic sensors are compared. First, the positional uncertainty for single obstacle detection can be determined based on the combination of ultrasonic sensors detecting an obstacle. Second, the positional uncertainty for multiple obstacle detection can be determined based on the inequality relationship among three adjacent obstacle distances. Third, the positional uncertainty for omnidirectional obstacle detection can be determined by overlapping all the uncertainty arcs obtained for every three consecutive ultrasonic sensors.
Analysis on the Effect of Beam Overlap of a Low Directivity Ultrasonic Sensor Ring
Sungbok Kim,Hyunbin Kim 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
This paper presents the analysis on the effect of beam overlap of a low directivity ultrasonic sensor ring. It is assumed that a set of ultrasonic sensors of the same type are arranged along a circle of non-zero radius at regular spacings with their beams overlapped. Due to beam overlap of an ultrasonic sensor ring, the detection zone of each ultrasonic sensor can be divided into three smaller sub-zones, and also for a given obstacle distance, its uncertainty arc can be divided into three smaller sub-arcs. First, taking into account the range of sensing distance as well as the dead angle region, the entire range of obstacle detection of an overlapped ultrasonic sensor ring is specified. Second, the effective beam width of an overlapped ultrasonic sensor ring is assessed in terms of the lengths of uncertainty sub-arcs. Third, alternative assessment of effective beam width of an overlapped ultrasonic sensor ring is proposed in terms of the areas of detection sub-zones. Lastly, using a commercial low directivity ultrasonic sensors, the changes of the effective beam widths depending on the parameter of an overlapped ultrasonic sensor ring are examined
Development of Traveling Surface Characteristics Extraction Equipment Using Optical Mouse Array
Sungbok Kim,Hyunbin Kim,Minkyu Park 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
This paper presents the development of the traveling surface characteristics extraction equipment for accurate velocity estimation of a mobile robot using optical mice. In the traveling surface characteristics extraction equipment, a traveling surface sample is rotating relative to stationary optical mice, instead of a mobile robot equipped with optical mice traveling over a floor surface. First, the operational principle of the traveling surface characteristics extraction equipment is explained, Then, the mechanical design & construction, the hardware development, and the software development of the traveling surface characteristics extraction equipment are described in detail.