• Journal of Microbiology and Biotechnology
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• v.31 no.4
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• pp.520-528
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• 2021

Plesiomonas shigelloides, a member of the family Vibrionaceae, is a gram-negative, rod-shaped, facultative anaerobic bacterium with flagella. P. shigelloides has been isolated from such sources as freshwater, surface water, and many wild and domestic animals. P. shigelloides contains 102 O-antigens and 51 H-antigens. The diversity of O-antigen gene clusters is relatively poorly understood. In addition to O1 and O17 reported by other laboratories, and the 12 O serogroups (O2, O10, O12, O23, O25, O26, O32, O33, O34, O66, O75, and O76) reported previously by us, in the present study, nine new P. shigelloides serogroups (O8, O17, O18, O37, O38, O39, O44, O45, and O61) were sequenced and annotated. The genes for the O-antigens of these nine groups are clustered together in the chromosome between rep and aqpZ. Only O38 possesses the wzm and wzt genes for the synthesis and translocation of O-antigens via the ATP-binding cassette (ABC) transporter pathway; the other eight use the Wzx/Wzy pathway. Phylogenetic analysis using wzx and wzy showed that both genes are diversified. Among the nine new P. shigelloides serogroups, eight use wzx/wzy genes as targets. In addition, we developed an O-antigen-specific PCR assay to detect these nine distinct serogroups with no cross reactions among them.

• Journal of Ginseng Research
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• v.43 no.1
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• pp.10-19
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• 2019

Background: Frequent overdose of paracetamol (APAP) has become the major cause of acute liver injury. The present study was designed to evaluate the potential protective effects of ginsenoside Rk1 on APAP-induced hepatotoxicity and investigate the underlying mechanisms for the first time. Methods: Mice were treated with Rk1 (10 mg/kg or 20 mg/kg) by oral gavage once per d for 7 d. On the 7th d, allmice treated with 250mg/kg APAP exhibited severeliverinjury after 24 h, and hepatotoxicitywas assessed. Results: Our results showed that pretreatment with Rk1 significantly decreased the levels of serum alanine aminotransferase, aspartate aminotransferase, tumor necrosis factor, and interleukin-$1{\beta}$ compared with the APAP group. Meanwhile, hepatic antioxidants, including superoxide dismutase and glutathione, were elevated compared with the APAP group. In contrast, a significant decrease in levels of the lipid peroxidation product malondialdehyde was observed in the ginsenoside Rk1-treated group compared with the APAP group. These effects were associated with a significant increase of cytochrome P450 E1 and 4-hydroxynonenal levels in liver tissues. Moreover, ginsenoside Rk1 supplementation suppressed activation of apoptotic pathways by increasing Bcl-2 and decreasing Bax protein expression levels, which was shown using western blotting analysis. Histopathological observation also revealed that ginsenoside Rk1 pretreatment significantly reversed APAP-induced necrosis and inflammatory infiltration in liver tissues. Biological indicators of nitrative stress, such as 3-nitrotyrosine, were also inhibited after pretreatment with Rk1 compared with the APAP group. Conclusion: The results clearly suggest that the underlying molecular mechanisms in the hepatoprotection of ginsenoside Rk1 in APAP-induced hepatotoxicity may be due to its antioxidation, antiapoptosis, anti-inflammation, and antinitrative effects.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.29-38
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• 2019

Microbial community and composition in stormwater runoff from mixed land use land cover (LULC) catchment with ongoing land development was diverse across the hydrological stage due different environmental parameters (hydrometeorological and physicochemical) and source of runoff. However, limited studies have been made for bacterial composition in this catchment. Therefore, this study aims to: (1) quantify the concentration of fecal indicator bacteria (FIB), stormwater quality and bacterial composition and structure according to hydrological stage; and (2) determine their correlation to environmental parameters. The 454 pyrosequencing was used to determine the bacterial community and composition; while Pearson's correlation was used to determine the correlation among parameters-FIB, stormwater quality, bacterial composition and structure-to environmental parameters. Results demonstrated that the initial and peak runoff has the highest concentration of FIB, stormwater quality and bacterial composition and structure. Proteobacteria, Bacteroidetes, Actinobacteria and Firmicutes were dominant bacteria identified in this catchment. Furthermore, the 20 most abundant genera were correlated with runoff duration, average rainfall intensity, runoff volume, runoff flow, temperature, pH, organic matter, nutrients, TSS and turbidity. An increase of FIB and stormwater quality concentration, diversity and richness of bacterial composition and structure in this study was possibly due to leakage from septic tanks, cesspools and latrines; feces of domestic and wild animals; and runoff from forest, destroyed septic system in land development site and urban LULC. Overall, this study will provide an evidence of hydrological stage impacts on the runoff microbiome environment and public health perspective.

• Journal of Ecology and Environment
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• v.44 no.4
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• pp.229-240
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• 2020

Background: Genus Quercus is a successful group that has occupied the largest area of forest around the world including South Korea. The acorns are an important food source for both wild animals and humans. Although the reproductive characteristics of this genus are highly variable, it had been rarely studied in South Korea. Therefore, in Seoraksan and Odaesan National Parks (i) we measured the acorn production of Quercus mongolica, an overwhelmingly dominant species in South Korea, for 3 years (2017-2019), (ii) evaluated the spatial-temporal variation of acorn production, and (iii) analyzed the effects of oak- and site-related variables on the acorn production. Results: The annual acorn production of Q. mongolica increased 36 times from 1.2 g m-2 in 2017 to 43.2 g m-2 in 2018, and decreased to 16.7 g m-2 in 2019, resulting in an annual coefficient of variation of 104%. The coefficient of spatial variation was high and reached a maximum of 142%, and the tree size was the greatest influencing factor. That is, with an increase in tree size, acorn production increased significantly (2018 F = 16.3, p < 0.001; 2019 F = 8.2, p < 0.01). Elevation and slope also significantly affected the production in 2019. However, since elevation and tree size showed a positive correlation (r = 0.517, p < 0.001), the increase in acorn production with increasing elevation was possibly due to the effect of tree size. The acorn production of Odaesan for 3 years was 2.2 times greater than that of Seoraksan. This was presumed that there are more distribution of thick oak trees and more favorable site conditions such as deep soil A-layer depth, high organic matter, and slower slopes. Conclusion: As reported for other species of the genus Quercus, the acorn production of Q. mongolica showed large spatial and annual variations. The temporal variability was presumed to be a weather-influenced masting, while the spatial variability was mainly caused by oak tree size.

• Korean Journal of Veterinary Research
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• v.61 no.4
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• pp.39.1-39.6
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• 2021

The classification of the bone pieces excavated from Gasan-ri archaeological site 1 in Jinju, presumed to be relics was investigated macroscopically. The remains of the animal bone were 3 classes (Mammalia, Aves, Amphibia), 5 orders (Carnivora, Artiodactyla, Galliformer, Rodentia, Salientia), and 6 species (Sus scrofa, Cervidae sp., Nyctereutes procyonides, Phasianidae, Rattus norvegicus caraco, Rana nigromaculata). The total weight of the animal bone remains was 1,002.80 g, with the identified bones comprising 975.30 g and an identification rate of 97.26%. A total of 447 animal bone fragments were identified, including 204 bone pieces of S. scrofa (468.00 g, 47.99%), 102 bone pieces of Cervidae sp. (453.79 g, 46.53%), 68 bone pieces of R. nigromaculata (4.69 g, 0.48%), 59 bone pieces of N. procyonides (47.14 g, 4.83%), 9 bone pieces of Phasianidae (0.98 g, 0.10%), and 5 bone pieces of Rattus norvegicus caraco (0.70 g, 0.07%). The bone pieces of the animal relics consisted of 81 skull (18.12%), 161 axial skeleton (36.02%), 64 forelimb (14.32%), and 141 hindlimb (31.54%) fragments. The archaeological significance of the animal bones excavated in this investigation was that wild boars and deer were presumed to have been mainly used animals in the Gasan-ri area of Jinju during the Three Kingdoms period.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.3
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• pp.165-171
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• 2022

The Chinese crested tern (Thalasseus bersteini) is one of the most globally endangered species, listed as "Critically Endangered (CE)" on the IUCN Red List, with only approximately 30-49 individuals surviving in the wild. Chinese crested terns were discovered to breed in South Korea for the first time in 2016 while conducting a census on uninhabited islands. The Ministry of Environment has declared the breeding habitat of the Chinese crested terns as "Specified Island" to protect this CE species. However, brown rats (Rattus norvegicus) inhabiting the breeding grounds of the Chinese crested terns and Black-tailed gulls may potentially pose a threat to the breeding of these avian species. Therefore, we conducted a study on the feeding behavior of brown rats involving stable isotope analysis to determine their food sources. Fecal analysis showed that brown rats mainly fed on plants, whereas they scarcely fed on animals, such as insects. In addition, the stable isotope analysis showed that the δ¹³C values of brown rats, insects, and Indian goosegrasses were approximately -16 to -11‰, whereas the δ¹³C value of Chinese crested terns that obtained their food from the marine ecosystem was approximately -22 to -18‰. Hence, we conclude that the source of carbon for brown rats on this island is the terrestrial ecosystem. We ruled out the possibility of any direct prey-predator interaction between the brown rat and the Chinese crested tern or Black-tailed gull.

• Journal of People, Plants, and Environment
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• v.24 no.1
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• pp.95-105
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• 2021

Background and objective: A biosphere reserve is a complex concept that combines the preservation of biodiversity and the sustainable development with the region, outstanding ecosystems with worth conserving in worldwide. The purpose of this study is to suggest the way of zoning that can perform the functions of conservation, development, and logistics support of biosphere reserves. Methods: To meet the purpose of this study, the designation criteria, restrictions, and permissions of the protected area specified in the law for domestic protected areas were reviewed to classify the functions of a biosphere reserve. Results: Through this classification, 10 domestic protected areas with high ecological protection value, such as the natural beauty of the ecosystem, biodiversity, and habitats for wild animals and plants were derived as the core areas of the biosphere reserves. Also, a total of 21 protected zones that can function as a buffer to protect the core of the natural ecosystem from indiscriminate development such as resource protection, recovery, pollution prevention, and improvement were derived as appropriate sites for a buffer. In the review process, issues such as different behavioral restrictions and ranges of permission due to the application of different laws were identified, if two or more protected areas exist within one of the protected areas, there is a protected area that does not meet the criteria for designating use zone, or where behavior restrictions do not meet the zoning criteria of biosphere reserve, under the laws of domestic protected areas. Conclusion: Although this study was not able to carefully review most of the laws on domestic protected areas that are linked to other laws, it was able to categorize appropriate domestic protected areas that can act as the core and buffer zones of biosphere reserves.

• Journal of Veterinary Science
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• v.21 no.2
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• pp.14.1-14.10
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• 2020

African swine fever (ASF) is a highly contagious disease of domestic pigs and wild boars (WBs). Without a vaccine, early antibody and antigen detection and rapid diagnosis are crucial for the effective prevention of the disease and the employment of control measures. In Sardinia, where 3 different suid populations coexisted closely for a long time, the disease persists since 1978. The recent ASF eradication plan involves more stringent measures to combat free-ranging pigs and any kind of illegality in the pig industry. However, critical issues such as the low level of hunter cooperation with veterinary services and the time required for ASF detection in the WBs killed during the hunting season still remain. Considering the need to deliver true ASF negative carcasses as early as possible, this study focuses on the evaluation and validation of a duplex pen-side test that simultaneously detects antibodies and antigens specific to ASF virus, to improve molecular diagnosis under field conditions. The main goal was to establish the specificity of the two pen-side tests performed simultaneously and to determine their ability to detect the true ASF negative carcasses among the hunted WBs. Blood and organ samples of the WBs hunted during the 2018/2019 hunting seasons were obtained. A total of 160 animals were tested using the pen-side kit test; samples were collected for virological and serological analyses. A specificity of 98% was observed considering the official laboratory tests as gold standards. The new diagnostic techniques could facilitate faster and cost-effective control of the disease.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.99-106
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• 2022

In this paper, We propose a method for identifying objects by setting inscriptions and landmarks of dogs. The phenomenon of abandoning dogs is on the rise, and the number of abandoned individuals is also rapidly increasing. These abandoned dogs are becoming wild animals, causing a lot of damage to people's daily life, causing serious problems. As a solution to this problem, the animal registration system is being implemented, but there is a phenomenon that some dog owners avoid the registration method that inserts a chip, so the complete registration system is not settled. When registering a dog, removing the avoidance of dog owners will help establish the companion animal registration system. In this paper, we present a technique to identify objects by setting inscriptions and landmarks of dogs so that dog owners can register their dogs in a friendly way to eliminate this avoidance phenomenon.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.