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Sumin Oh,Yang-Hyun Baek,Sungju Jung,Sumin Yoon,Byeonggeun Kang,Su-hyang Han,Gaeul Park,Je Yeong Ko,Sang-Young Han,Jin-Sook Jeong,Jin-Han Cho,Young-Hoon Roh,Sung-Wook Lee,Gi-Bok Choi,Yong Sun Lee,Won K 대한간학회 2024 Clinical and Molecular Hepatology(대한간학회지) Vol.30 No.2
Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.
Jeong, Sumin,Kim, Suk Chan Elsevier 2018 Digital signal processing Vol.78 No.-
<P><B>Abstract</B></P> <P>Underwater time synchronisation is required to use the latest communication technologies. Because propagation time should be estimated to improve time synchronisation accuracy, node mobility is an important factor. In the subaqueous environment, furthermore, it is impossible to exclude the influence of the node movement occurred by environmental factors and underwater nodes could have self-mobility. Conventional time synchronisations have considered node mobility but have an unrealistic assumption of node movement and high computational complexity. In this paper, however, our novel method, Low-complexity time synchronisation for 3-dimensional underwater communications environment using estimated instantaneous node velocity based (V-Sync), shows high accuracy with low complexity and short processing latency. In this paper, it is supposed that mobile nodes could know their instantaneous speeds when they receive the synchronising messages. Time synchronisation errors, skew and offset, are estimated by the instantaneous speeds. The performance and analysis of V-Sync in the underwater mobile environment is demonstrated by simulation results.</P>
열효율 향상을 위한 xGnP가 혼합된 SSPCM 제조 및 평가
정수광(Jeong, Su-Gwang),김석환(Kim, Sughwan),이정훈(Lee, Jeong-Hun),임재한(Lim, Jae-Han),김수민(Kim, Sumin) 한국건축친환경설비학회 2012 한국건축친환경설비학회 학술발표대회 논문집 Vol.2012 No.10
This paper deals with the thermal performances of Shape-Stabilized Phase Change Materials (SSPCM) for energy saving in various fields. This study enhanced thermal properties of SSPCM by using exfoliated graphite nanoplatelets (xGnP). SSPCM, which contains the xGnP, was prepared by mixing and melting techniques for high dispersibility, thermal conductivity and latent heat storage. In the experiment, we used hexadecane, octadecane and paraffin as Phase Change Materials (PCMs), and they have 254.7J/g, 247.6J/g and 144.6J/g of latent heat capacity, and melting points of 20.84?C, 30.4?C and 57.09?C, respectively. The characteristics of SSPCMs were determined by using SEM, DSC, FTIR,and TGA.