• Applied Biological Chemistry
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• v.21 no.1
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• pp.11-15
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• 1978

Alloisoleucine from the plasma of maple syrup disease affected patients was separated from isolecine and identified by gas liquid chromatography and mass spectrometry.

• Parasites, Hosts and Diseases
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• v.50 no.2
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• pp.103-111
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• 2012

Intestinal giant-cystic disease (IGCD) of the Israel carp (Cyprinus carpio nudus) has been recognized as one of the most serious diseases afflicting inland farmed fish in the Republic of Korea, and Thelohanellus kitauei has been identified as the causative agent of the disease. Until now, studies concerning IGCD caused by T. kitauei in the Israel carp have been limited to morphological and histopathological examinations. However, these types of diagnostic examinations are relatively time-consuming, and the infection frequently cannot be detected in its early stages. In this study, we cloned the full-length 18S rRNA gene of T. kitauei isolated from diseased Israel carps, and carried out molecular identification by comparing the sequence with those of other myxosporeans. Moreover, conventional PCR and real-time quantitative PCR (qPCR) using oligonucleotide primers for the amplification of 18S rRNA gene fragment were established for further use as methods for rapid diagnosis of IGCD. Our results demonstrated that both the conventional PCR and real-time quantitative PCR systems applied herein are effective for rapid detection of T. kitauei spores in fish tissues and environmental water.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.480-489
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• 2018

Bitter rot caused by Colletotrichum species is a common fruit rotting disease of apple and one of the economically important disease in worldwide. In 2015 and 2016, distinct symptoms of bitter rot disease were observed in apple orchards in five regions of South Korea. In the present study, infected apples from these regions were utilized to obtain eighteen isolates of Colletotrichum spp. These isolates were identified and characterized according to their morphological characteristics and nucleotide sequence data of internal transcribed spacer regions and glyceraldehyde-3-phosphate-dehydrogenase. Molecular analyses suggested that the isolates of Colletotrichum causing the bitter rot disease in South Korea belong to 4 species: C. siamense; C. fructicola; C. fioriniae and C. nymphaeae. C. siamense and C. fructicola belonged to Musae Clade of C. gloeosporioides complex species while C. fioriniae and C. nymphaeae belonged to the Clade 3 and Clade 2 of C. acutatum complex species, respectively. Additionally, we also found that the isolates of C. gloeosporioides species-complex were more aggressive than those in the C. acutatum species complex via pathogenicity tests. Taken together, our results suggest that accurate identification of Colletotrichum spp. within each species complex is required for management of bitter rot disease on apple fruit in South Korea.

• The Plant Pathology Journal
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• v.39 no.4
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• pp.319-334
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• 2023

Plant disease is an important factor affecting crop yield. With various types and complex conditions, plant diseases cause serious economic losses, as well as modern agriculture constraints. Hence, rapid, accurate, and early identification of crop diseases is of great significance. Recent developments in deep learning, especially convolutional neural network (CNN), have shown impressive performance in plant disease classification. However, most of the existing datasets for plant disease classification are a single background environment rather than a real field environment. In addition, the classification can only obtain the category of a single disease and fail to obtain the location of multiple different diseases, which limits the practical application. Therefore, the object detection method based on CNN can overcome these shortcomings and has broad application prospects. In this study, an annotated apple leaf disease dataset in a real field environment was first constructed to compensate for the lack of existing datasets. Moreover, the Faster R-CNN and YOLOv3 architectures were trained to detect apple leaf diseases in our dataset. Finally, comparative experiments were conducted and a variety of evaluation indicators were analyzed. The experimental results demonstrate that deep learning algorithms represented by YOLOv3 and Faster R-CNN are feasible for plant disease detection and have their own strong points and weaknesses.

• The Journal of Internal Korean Medicine
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• v.43 no.1
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• pp.1-21
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• 2022

Purpose: The standard tool for the pattern identification is used for identifying patterns in patients using a questionnaire. The purpose of this study is to reorganize the standard tool for the pattern identification of gastroesophageal reflux disease (GERD) developed in 2017 and to analyze the reliability and validity of the standard tool for pattern identification by applying it to GERD patients. Methods: To reorganize the standard tool for the pattern identification of GERD developed in the previous study, we searched the literature in the main databases, OASIS (Oriental Medicine Advanced Searching Integrated System) and CNKI (China National Knowledge Infrastructure). We added the search results to the data used in the previous study and went through the reorganizing courses, such as evaluating the validity of the translation, the Delphi technique, and a small survey. After reorganization, the patients who visited the Kyunghee University Korean Medicine Center for GERD symptoms were provided the questionnaire, including the reorganized standard tool for pattern identification. We analyzed the survey results to evaluate their reliability and validity. Results: Fifty patients completed the questionnaire. Reliability analysis results showed a pattern identification match rate of 86%, Cronbach's α coefficient of 0.834, and intraclass correlation coefficient of 0.907. The Mann - Whitney U test and logistic regression were implemented to check the relations between the survey questions and pattern identification results; the Pearson correlation, compared with other scales, showed a moderate score. Conclusion: We reorganized the standard tool for the pattern identification of GERD to be updated on current issues and so that it is easily used. The analysis results of the questionnaire showed that the reorganized standard tool had high reliability and moderate validity.

• The Journal of the Society of Stroke on Korean Medicine
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• v.13 no.1
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• pp.33-42
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• 2012

Object : The aim of this study was to assess the clinical indicators related to Pattern-Identification(PI) in acute cerebral infarction patients. Methods : We studied hospitalized patients within 30days after ictus, who admitted at Korean Medicine Center of Kyung-Hee University from January 2010 to October 2012.(n=290) Two Traditional Korean Medicine(TKM) physicians evaluated the patients independently and diagnosed PI. Inter-rater reliability was measured using simple percentage agreement and the Cohen's kappa(κ) coefficient. To assess the clinical indicators closely related to each PI, we analysed average score of each indicator in each group. Results : Simple percentage agreement of PI between raters was 64.83% and Cohen's kappa(κ) coefficient was 0.526(95% CI: 0.451-0.600). Inter-rater reliability level was fair to good. We analysed the clinical indicators in each group. Significant indicators for Fire-Heat Pattern(FHP) were reddened complexion and strong pulse power, and meaningful indicators for FHP were halitosis and thick tongue fur. Significant indicator for Dampness-Phlegm Pattern(DPP) was overweight and there was no meaningful indicator. Significant indicator for Yin-Deficiency Pattern(YDP) was dry tongue fur and meaningful indicator for YDP was thirst. There was no significant indicator for Qi-Deficiency Pattern(QDP) and pale complexion and faint low voice were meaningful indicators for QDP. Conclusions : This study reveals the significant and meaningful clinical indicators related to each Pattern-Identification in acute cerebral infarction patients. It will contribute to standardization of Korean Medical Diagnosis and Treatment in acute cerebral infarction patients.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.2
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• pp.124-130
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• 2016

The aim of this study was to suggest the future direction of diagnostic and evaluative pattern identification questionnaire (PIQ) by reviewing the state of development and utilization of PIQ according to Korean classification of disease-U (KCD-U). We surveyed the database of OASIS, NDSL, KISS, DBPIA, and Pub-med to know the kinds of developed and developing PIQ of Korean medicine. We used 'Pattern Identification' and 'Questionnaire' to find suitable papers. The inclusion criteria met 47 cases. The number of PIQ before 2000yrs, between 2001 to 2005, 2006-2010, 2011-2015 were 2, 5, 18, 22cases. The number of PIQ belonged to the disease of Korean medicine, the pathological symptom of korean medicine, the Sasang constitutional pattern identification and etc according to KCD-U were 20(42.6%), 8(17%), 9(19.1%) and 10(21.3%). Twenties among forty seven PIQ were validated, and the rest of them were not validated. The distribution of the numbers of PIQ were significantly different according to KCD-U (p=0.003). The direction of Utilization of PIQ was 36 questionnaires in diagnosing PI, 14 cases in evaluating health state, 4cases in evaluating effects of a treatment and 8 ones in diagnosing Sasang constitutional types. This study reveals the status on validated and non-validated PIQ of Korean medicine and suggests the basic information for the direction of developing PIQ in the future.

• Journal of Microbiology and Biotechnology
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• v.25 no.10
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• pp.1606-1613
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• 2015

Porcine pleuropneumonia is an infectious disease caused by Actinobacillus pleuropneumoniae. The identification of A. pleuropneumoniae genes, specially expressed in vivo, is a useful tool to reveal the mechanism of infection. IVIAT was used in this work to identify antigens expressed in vivo during A. pleuropneumoniae infection, using sera from individuals with chronic porcine pleuropneumonia. Sequencing of DNA inserts from positive clones showed 11 open reading frames with high homology to A. pleuropneumoniae genes. Based on sequence analysis, proteins encoded by these genes were involved in metabolism, replication, transcription regulation, and signal transduction. Moreover, three function-unknown proteins were also indentified in this work. Expression analysis using quantitative real-time PCR showed that most of the genes tested were up-regulated in vivo relative to their expression levels in vitro. IVI (in vivo-induced) genes that were amplified by PCR in different A. pleuropneumoniae strains showed that these genes could be detected in almost all of the strains. It is demonstrated that the identified IVI antigen may have important roles in the infection of A. pleuropneumoniae.

• 대한상한금궤의학회지
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• v.13 no.1
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• pp.145-153
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• 2021

Objective : This study aimed to report the improvement of a patient with anorexia by treatment with Jinmu-tang (Hyunmu-tang) based on the disease pattern identification diagnostic system (DPIDS) of the Shanghanlun provisions. Methods : We evaluated the progress of symptoms, patient compliance, and presence of side effects after the patient was administered Jinmu-tang. The clinical response was estimated according to the number of meals a day, the size of meals, the number of complaints of abdominal pain in a week, and a Likert scale. Results : According to the DPIDS, the patient was diagnosed according to provision 316 with soyinbing. After administration of Jinmu-tang for 45 days, the number of meals a day and the size of meals increased, the number of complaints of abdominal pain in a week decreased, and the Likert scale score decreased from 3 to 0. Conclusions : This case report suggests that the word "腹痛" (abdominal pain) in the 316th Shanghanlun provision indicates anxiety about abdominal pain, which affected anorexia in this case.

• BMB Reports
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• v.37 no.1
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• pp.11-27
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• 2004

The introduction of molecular markers in genetic analysis has revolutionized medicine. These molecular markers are genetic variations associated with a predisposition to common diseases and individual variations in drug responses. Identification and genotyping a vast number of genetic polymorphisms in large populations are increasingly important for disease gene identification, pharmacogenetics and population-based studies. Among variations being analyzed, single nucleotide polymorphisms seem to be most useful in large-scale genetic analysis. This review discusses approaches for genetic analysis, use of different markers, and emerging technologies for large-scale genetic analysis where millions of genotyping need to be performed.