http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Oh Yeonji,Lee Tae‐gum,Kim Mi Kyoung,Chong Youhoon 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.10
Investigations into tau-targeting diagnosis of Alzheimer’s disease are currently underway, and the development of tau-selective molecular probes is urgently required. In this study, the donor-π-acceptor architecture of the previously reported tau-selective fluorescence probe was modified into thiophene-π-cyanoacetamides. While the fluorescence properties of the prepared probes were not influenced by the thiophene substituents, intense and tau-selective turn-on fluorescence in the near infrared region was observed only in the probes with unsubstituted phenyl or p-methylphenyl cyanoacetamides in the acceptor functionality. Compared with the parent compound, the newly identified probes showed 1.5 4.1 times increase in tau-selectivity over Aβ fibrils and 3.5 4.7 times increase in fluorescence intensity. The tau-selective fluorescence properties of the title probes were further demonstrated in the cellular milieu, and the green and red fluorescence emitted by GFP and tau-bound probes, respectively, were shown to be nicely colocalized in the SH-SY5Y cells stably expressing GFP-tagged tau
Yeonji Kim,Kyungyeon Lee,Uran Oh 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.2
It is difficult for non-experts to build machine learning (ML) models at the level that satisfies their needs. Deep learning models are even more challenging because it is unclear how to improve the model, and a trial-and-error approach is not feasible since training these models are time-consuming. To assist these novice users, we examined how interactive and explainable feedback while training a deep learning network can contribute to model performance and users’ satisfaction, focusing on the data preparation process. We conducted a user study with 31 participants without expertise, where they were asked to improve the accuracy of a deep learning model, varying feedback conditions. While no significant performance gain was observed, we identified potential barriers during the process and found that interactive and explainable feedback provide complementary benefits for improving users’ understanding of ML. We conclude with implications for designing an interface for building ML models for novice users.
Bacterial diversity and its relationship to growth performance of broilers
Bae, Yeonji,Koo, Bonsang,Lee, Seungbaek,Mo, Jongsuk,Oh, Kwanghyun,Mo, In Pil The Korean Society of Veterinary Science 2017 大韓獸醫學會誌 Vol.57 No.3
The microbial community is known to have a key role during the rearing period of broilers. In this study, gut microbial composition and diversity were examined to evaluate the relationships between these factors and broiler growth performance. By applying 454-pyrosequencing of the V1-V3 regions of bacterial 16S rRNA genes, six fecal samples from four- and 28-day-old chickens from three broiler farms and 24 intestinal samples of broilers with heavy and light body weights were analyzed. Microbial composition assessment revealed Firmicutes to be the most prevalent phylum at farm A, while Proteobacteria were predominant at farms B and C. Fecal microbial richness and diversity indices gradually increased from four to 28 days at all three farms. Microbial diversity assessment revealed that small intestine microbial diversity was lower in heavy birds than in light birds. In light birds, the Firmicutes proportion was lower than that in heavy birds. In conclusion, each broiler farm revealed a specific microbial profile which varied with the age of the birds. The microbial communities appeared to affect growth performance; therefore, gut microbial profiles can be utilized to monitor growth performance at broiler farms.
Kim, Yeonji,Lee, Kyungyeon,Oh, Uran The Institute of Internet 2020 International journal of advanced smart convergenc Vol.9 No.2
It is difficult for non-experts to build machine learning (ML) models at the level that satisfies their needs. Deep learning models are even more challenging because it is unclear how to improve the model, and a trial-and-error approach is not feasible since training these models are time-consuming. To assist these novice users, we examined how interactive and explainable feedback while training a deep learning network can contribute to model performance and users' satisfaction, focusing on the data preparation process. We conducted a user study with 31 participants without expertise, where they were asked to improve the accuracy of a deep learning model, varying feedback conditions. While no significant performance gain was observed, we identified potential barriers during the process and found that interactive and explainable feedback provide complementary benefits for improving users' understanding of ML. We conclude with implications for designing an interface for building ML models for novice users.
Kang, Sohi,Yang, Wonjun,Oh, Hanseul,Bae, Yeonji,Ahn, Meejung,Kang, Min Chul,Ko, Ryeo Kyeong,Kim, Gi Ok,Lee, Jun Hwa,Hyun, Jin Won,Moon, Changjong,Shin, Taekyun The Korean Society of Veterinary Science 2011 大韓獸醫學會誌 Vol.51 No.4
Several compounds and extracts isolated from a brown alga, Ishige (I.) okamurae, exhibit anti-oxidant and anti-inflammatory effects. The present study investigated whether the ethyl acetate (EtOAc) fraction of I. okamurae (EFIO) could ameliorate carbon tetrachloride ($CCl_{4}$)-induced hepatotoxicity in rats. Sprague-Dawley rats were intraperitoneally (i.p.) administered with EFIO at 10 or 50 mg/kg per day for 2 consecutive days before $CCl_{4}$ injection (3.3 mL/kg, i.p.). Twenty four hours later, the rats were anesthesized with diethyl ether and dissected. Pretreatment with EFIO significantly reduced the increased serum levels of alanine aminotransferase and aspartate aminotransferase in $CCl_{4}$-treated rats. Pretreatment with EFIO also significantly inhibited the reduced activities of superoxide dismutase and catalase in the $CCl_{4}$-injured liver. Histopathological evaluations showed that hemorrhage, hepatocyte necrosis, inflammatory cell infiltration, and fatty degeneration induced by $CCl_{4}$ treatment were ameliorated by the administration of EFIO. Additionally, liver immunohistochemical analyses revealed the marked reduction in ED1-positive monocyte-like macrophages in EFIO-pretreated rats given $CCl_{4}$. These results suggest that EFIO ameliorates $CCl_{4}$-induced liver injury, possibly through the inhibition of oxidative stress.