• Journal of Nutrition and Health
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• v.41 no.5
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• pp.428-438
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• 2008

Choline is important for normal membrane function, acetylcholine synthesis and methyl group metabolism. In this study, 185 food items customarily eaten by Koreans were selected from the data of the 2001 Korean National Health and Nutrition Survey and analyzed on the total choline content of the foods using enzymatic method of choline oxidase. Foods with high choline concentration (mg/100 g) were listed in sequence of quail egg (476.04 mg), dried squid (452.42 mg), beef liver (427.16 mg), pork liver (424.92 mg), tuna canned in oil (414.44 mg), boiled and dried anchovy (381.30 mg), dried Alaskan pollack (378.88 mg), chicken egg (309.88 mg), chicken liver (259.38 mg), soybean (238.62 mg), French bread with garlic (193.18 mg) and barley (183.73 mg). From this result, it is shown that dried fishes, prepared fishes, livers, eggs, pulses and cereals might be categorized as high choline food. Citron tea and green tea showed low choline content below 1 mg. Vegetables and fruits were also categorized into low choline food. No choline was detected in red pepper powder, beer, soju, soybean oil and corn oil out of foods analyzed in this study. Further study is required for analytic procedure of the foods of which results are inconsistent with USDA's data such as rice and wheat flour.

• Korean Journal of Poultry Science
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• v.50 no.4
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• pp.261-266
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• 2023

The skeletal muscles of livestock play a crucial role as protein sources for humans, and the consumption of poultry meat is steadily increasing worldwide. Numerous genes, including myogenic regulatory factors, are involved in myogenesis, and precise regulation of them is essential. In this study, genes specifically expressed in muscles were selected, and their promoters were cloned and analyzed. The analysis of gene expression in various tissues of animals revealed that many genes exhibited specific expression patterns in skeletal muscles, with TNNT3, TNNC2, and MYF6 genes showing similar patterns in poultry. The promoter regions of three genes were amplified by polymerase chain reaction to sizes of 1.2 kb, 1.03 kb, and 1.43 kb, respectively. These fragments were then inserted at the front of the enhanced green fluorescent protein gene in vectors. It was confirmed that the sequences of three promoters closely matched the chicken genome sequences. Upon introducing vectors with each promoter into QM7 quail muscle cells, all three promoters successfully induced the expression of the green fluorescent protein. The brightness of the green fluorescence in each promoter was approximately seven times dimmer compared to the control, CMV-IE promoter. It is predicted that more than 230 transcription factors can bind to each promoter, especially various transcription factors expressed in muscles, including myogenic regulatory factors such as MYF5, MYOD, and MYOG. These promoters can be valuable for studying gene expression in poultry muscle cells, and further research is needed to precisely investigate the regulatory region of gene expression in promoters.

• Journal of Veterinary Clinics
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• v.29 no.4
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• pp.309-314
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• 2012

The study was undertaken to evaluate sensitivity and specificity of rapid Avian Influenza (AI) and Newcastle Disease virus (NDV) combo antigen kits from field samples of domestic (broiler and layer chicken, native chicken) and semi-domestic (duck, goose, pigeon and quail) birds of Bangladesh. Samples were collected from naturally infected AI suspected domestic and semi-domestic birds of five different outbreak areas in Bangladesh. From each area two birds were selected for sampling, and from each bird three types of samples (tracheal, cloacal and oro-nasal swabs) were collected. A total of 210 field samples from a total of 70 birds were collected and tested using AI and NDV combo antigen rapid diagnostic kits in the study. All three different samples from a bird showed similar pattern of reaction. Out of 210 samples, 15 samples (5 birds), 63 samples (21 birds) and 27 samples (9 birds) were positive for AIV, NDV and both for AIV and NDV, respectively; whereas the remaining birds were negative for either AIV or NDV in this screening test. Among the five AIV positive, a layer chicken from wet market in Mymensingh, Netrokona, Gibandha and Kurigram and a native chicken from wet market in Kurigram area was positive to AIV. The semi-domestic birds are either positive to NDV or free from both AIV and NDV. This study revealed that the AIV and NDV rapid diagnostic kits could be effectively use to diagnose the respective virus in trachea, oro-nasal and cloacal samples simultaneously. AIV-NDV combo Ag test result clearly indicates that the test kit designed for AIV and NDV could diagnose the disease rapidly with less effort and higher scientific know how which could be used for the detection of AIV and NDV using field samples in large scale.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.347-355
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• 2014

In this study, the detection method was developed using molecular biological technique to distinguish authenticity of animal raw materials. The genes for distinction of species about animals targeted at Cytochrome c oxidase subunit I (COI), Cytochrome b (Cytb), and 16S ribosomal RNA (16S rRNA) genes in mitochondrial DNA. The species-specific primers were designed by that Polymerase Chain Reaction (PCR) product size was around 200 bp for applying to processed products. The target 24 raw materials were 2 species of domestic animals, 6 species of poultry, 2 species of freshwater fishes, 13 species of marine fishes and 1 species of crustaceans. The results of PCR for Rabbit, Fox, Pheasant, Domestic Pigeon, Rufous Turtle Dove, Quail, Tree Sparrow, Barn Swallow, Catfish, Mandarin Fish, Flying Fish, Mallotus villosus, Pacific Herring, Sand Lance, Japanese Anchovy, Small Yellow Croaker, Halibut, Jacopever, Skate Ray, Ray, File Fish, Sea Bass, Sea Urchin, and Lobster raw materials were confirmed 113 bp ~ 218 bp, respectively. Also, non-specific PCR products were not detected in compare species by species-specific primers. The method using primers developed in this study may be applied to distinguish an authenticity of food materials included animal raw materials for various processed products.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.