• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1544-1557
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• 2020

Objective: Genomic selection (GS) is becoming popular in animals' genetic development. We, therefore, investigated the single-step genomic best linear unbiased prediction (ssGBLUP) as tool for GS, and compared its efficacy with the traditional pedigree BLUP (pedBLUP) method. Methods: A total of 9,952 males born between 1997 and 2018 under Hanwoo proven-bull selection program was studied. We analyzed body weight at 12 months and carcass weight (kg), backfat thickness, eye muscle area, and marbling score traits. About 7,387 bulls were genotyped using Illumina 50K BeadChip Arrays. Multiple-trait animal model analyses were performed using BLUPF90 software programs. Breeding value accuracy was calculated using two methods: i) Pearson's correlation of genomic estimated breeding value (GEBV) with EBV of all animals (r_M1) and ii) correlation using inverse of coefficient matrix from the mixed-model equations (r_M2). Then, we compared these accuracies by overall population, info-type (PHEN, phenotyped-only; GEN, genotyped-only; and PH+GEN, phenotyped and genotyped), and bull-types (YBULL, young male calves; CBULL, young candidate bulls; and PBULL, proven bulls). Results: The r_M1 estimates in the study were between 0.90 and 0.96 among five traits. The r_M1 estimates varied slightly by population and info-type, but noticeably by bull-type for traits. Generally average r_M2 estimates were much smaller than r_M1 (pedBLUP, 0.40 to0.44; ssGBLUP, 0.41 to 0.45) at population level. However, r_M2 from both BLUP models varied noticeably across info-types and bull-types. The ssGBLUP estimates of r_M2 in PHEN, GEN, and PH+ GEN ranged between 0.51 and 0.63, 0.66 and 0.70, and 0.68 and 0.73, respectively. In YBULL, CBULL, and PBULL, the r_M2 estimates ranged between 0.54 and 0.57, 0.55 and 0.62, and 0.70 and 0.74, respectively. The pedBLUP based r_M2 estimates were also relatively lower than ssGBLUP estimates. At the population level, we found an increase in accuracy by 2.0% to 4.5% among traits. Traits in PHEN were least influenced by ssGBLUP (0% to 2.0%), whereas the highest positive changes were in GEN (8.1% to 10.7%). PH+GEN also showed 6.5% to 8.5% increase in accuracy by ssGBLUP. However, the highest improvements were found in bull-types (YBULL, 21% to 35.7%; CBULL, 3.3% to 9.3%; PBULL, 2.8% to 6.1%). Conclusion: A noticeable improvement by ssGBLUP was observed in this study. Findings of differential responses to ssGBLUP by various bulls could assist in better selection decision making as well. We, therefore, suggest that ssGBLUP could be used for GS in Hanwoo proven-bull evaluation program.

• Journal of Preventive Medicine and Public Health
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• v.36 no.2
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• pp.93-100
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• 2003

Objectives : Because shipyard workers are involved with various manufacturing process, they are exposed to many kinds of hazardous materials. Welders especially, are exposed to bisphenol-A (BPA) during the welding and flame cutting of coated steel, This study was conducted to assess the exposure status of the endocrine disrupter based on the job-exposure matrix. The effects of the genetic polymorphism of xenobiotic enzyme metabolisms involved in the metabolism of BPA on the levels of urinary metabolite were investigated. Methods : The study population was recruited from a shipyard company in the f province. A total of 84 shipbuilding workers 47 and 37 in the exposed and control groups, respectively, were recruited for this study. The questionnaire variables included, age, sex, use of personal protective equipment, smoking, drinking and work duration. The urinary metabolite was collected in the afternoon and correction made for the urinary creatinine concentration. The of the CYP1A1, CYP2E1 and UGT1A6 genotypes were investigated using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) methods with the DNA extracted from venous blood. Results : The urinary BPA level in the welders group was significantly higher than in the control group (p<0.05). The urinary BPA concentration with the wild type UGT1A6 was higher than the other UGT1A6 genotypes, but with no statistical significant. From themultiple regression analysis of the urinary BPA, the regression coefficient for job grade was statistically significant (p<0.05). Conclusions : The grade of exposure to BPA affected the urinary BPA concentration was statistically significant. However, the genetic polymorphisms of xenobiotics enzyme metabolism were not statistically significant. Further investigation of the genetic polymorphisms with a larger sample size is needed.

• Applied Microscopy
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• v.31 no.1
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• pp.71-83
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• 2001

Laminin, a kind of multidomain glycoproteins, is mainly localized in the basement membranes of various tissues. It is known that laminin plays an important part in mammalian lung morphogenesis. The authors have undertaken this study to investigate the changes in the distribution of laminin, and to find out cells which synthesize laminin during the organogenesis and differentiation of the lung. The fetal and neoantal rats (Sprague-Dawley strain) were used as experimental animals. The immunohisto-chemical methods were employed for detection of laminin within the developing lung tissue and the immunegold cytochemical methods were performed for detection of cells which synthesize laminin according to each stage of development. The results are as follows; 1. During fetal life, strong immunoreactivity for laminin is maintained in the basement membranes of the blood vessels and the bronchioles, the extracellular matrix of the mesenchyme, and basal lamina of the alveolar septum in the fetal rat lung. 2. After birth, laminin immunoreactivity at the alveolar septum is gradually reduced. 3. During fetal life, laminin is mainly detected within the cytoplasm of the mesenchymal cells, the endothelial cells of blood vessels and the fibroblasts in fetal rat lung. 4. According to the differentiation of type I and type II pneumocyte after birth, laminin is detected within cytoplasm of the type I pneumocytes, type II pneumocytes and fibroblasts. It is consequently suggested that laminin is largely expressed in the developing lung and laminin may be also synthesized by the type II pneumonocytes at early newborn stages.

• Korean Journal of Optics and Photonics
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• v.16 no.3
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• pp.182-190
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• 2005

The fiber Raman amplifier(FRA) is a distinctly advantageous technology. Due to its wider, flexible gain bandwidth, and intrinsically lower noise characteristics, FRA has become an indispensable technology of today. Various FRA modeling methods, with different levels of convergence speed and accuracy, have been proposed in order to gain valuable insights for the FRA dynamics and optimum design before real implementation. Still, all these approaches share the common platform of coupled ordinary differential equations(ODE) for the Raman equation set that must be solved along the long length of fiber propagation axis. The ODE platform has classically set the bar for achievable convergence speed, resulting exhaustive calculation efforts. In this work, we propose an alternative, highly efficient framework for FRA analysis. In treating the Raman gain as the perturbation factor in an adiabatic process, we achieved implementation of the algorithm by deriving a recursive relation for the integrals of power inside fiber with the effective length and by constructing a matrix formalism for the solution of the given FRA problem. Finally, by adiabatically turning on the Raman process in the fiber as increasing the order of iterations, the FRA solution can be obtained along the iteration axis for the whole length of fiber rather than along the fiber propagation axis, enabling faster convergence speed, at the equivalent accuracy achievable with the methods based on coupled ODEs. Performance comparison in all co-, counter-, bi-directionally pumped multi-channel FRA shows more than 102 times faster with the convergence speed of the Average power method at the same level of accuracy(relative deviation < 0.03dB).

• Korean Journal of Crystallography
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• v.7 no.1
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• pp.8-19
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• 1996

Cholestryl Methyl and Propyl Carbonate(CH3OCOOC27H45, C3H7OCOOC27H45) are monoclinic, space group P21, with a=17.014(1), b=7.682(1), c=10.612(1)Å, β=103.05(1)°, Z=2, V=1351.16Å3, Dc=1.09 g/cm3 for methyl carbonate, and with a=13.683(1), b=11.864(2), c=18.904(2)Å, β=106.30(1)°, Z=4, V=2945.4Å3, Dc=1.06 g/cm3, Dm=1.06 g/cm3 for propyl carbonate. The intensity data were collected on an Enraf-Nonius CAD-4 diffractometer with a graphite monochromated Cu-Kα radiation. The structure was solved by direct methods and refined by full matrix least-squares methods. The final R factor was 0.051 for 2323 observed reflections for methyl carbonate and 0.074 for 3323 observed reflections for propyl carbonate. Compared with other cholesteryl derivatives, the cholesteryl ring and tail region of the molecules are normal. The molecules are stacked in clearly separated layers. At center of the layer, there are cholesteryl-C(17) side chain interactions. The interface region between layers is occupied by the loosely packed methyl carbonate chains. The structure of cholesteryl propyl carbonates have two propyl carbonates have two molecules(A, B) that are not related by crystal symmetry and have their tetracyclic system almost parallel to each other. Cholesteryl-cholesteryl interactions between symmetry related A-molecules, and cholesteryl-C(17) side chain interactions between symmetry related B-molecules occur at the center of the layers and these molecules stack along 2₁ screw axes. There are also C(17)chain-carbonate chain and C(17)chain-C(17)chain interactions in the interface region between layers. There is efficient packing between cholesteryl ring systems in propyl carbonates. Temperature ranges of cholesteric mesophases of cholesteryl alkyl cargonates are narrow for methyl, pentyl and hexyl carbonates, and rather broader for ethyl and propyl carbonates. Cholesteryl-isotropic transitions change very little with chain length.

• Korean Journal of Environmental Agriculture
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• v.41 no.2
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• pp.82-94
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• 2022

BACKGROUND: Spiropidion and its metabolite are tetramic acid insecticide and require the establishment of an official analysis method for the safety management because they are newly registered in Korea. Therefore, this study was to determine the analysis method of residual spiropidion and its metabolite for the five representative agricultural products. METHODS AND RESULTS: Three QuEChERS methods (original, AOAC, and EN method) were applied to optimize the extraction method, and the EN method was finally selected by comparing the recovery test and matrix effect results. Various adsorbent agents were applied to establish the clean up method. As a result, the recovery of spiropidion was reduced when using the dispersive-SPE method with MgSO₄, primary secondary amine (PSA), graphitized carbon black (GCB) and octadecyl (C₁₈) in soybean. Color interference was minimized by selecting the case including GCB and C18 in addition to MgSO₄. This method was established as the final analysis method. LC-MS/MS was used for the analysis by considering the selectivity and sensitivity of the target pesticide and the analysis was performed in MRM mode. The results of the recovery test using the established analysis method and inter laboratory validation showed a valid range of 79.4-108.4%, with relative standard deviation and coefficient of variation were less than 7.2% and 14.4%, respectively. CONCLUSION(S): Spiropidion and its metabolite could be analyzed with a modified QuEChERS method, and the established method would be widely available to ensure the safety of residual insecticides in Korea.

• Tuberculosis and Respiratory Diseases
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• v.56 no.1
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• pp.51-66
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• 2004

Objectives : The matrix metalloproteinases (MMPs) that participate in the extracellular matrix metabolism play a important role in the progression of pulmonary fibrosis. The effects of the MMPs are regulated by several factors including Th-1 cytokines, $interferon-{\gamma}$ ($IFN-{\gamma}$). Up to now, $IFN-{\gamma}$ is known to inhibit pulmonary fibrosis, but little is known regarding the exact effect of $IFN-{\gamma}$ on the regulation of the MMPs. This study investigated the effects of $interferon-{\gamma}$ on the pulmonary fibrosis and the expression of the lung MMP-2,-9, TIMP-1,-2, and Th-2 cytokines in aa rat model of bleomycin induced pulmonary fibrosis. Materials and methods : Male, specific pathogen-free Sprague-Dawley rats were subjected to an intratracheal bleomycin instillation. The rats were randomized to a saline control, a bleomycin treated, and a bleomycin+$IFN-{\gamma}$ treated group. The bleomycin+$IFN-{\gamma}$ treated group was subjected to an intramuscular injection of $IFN-{\gamma}$ for 14 days. At 3, 7, 14, and 28 days after the bleomycin instillation, the rats were sacrificed and the lungs were harvested. In order to evaluate the effects of the $IFN-{\gamma}$ on lung fibrosis and inflammation, the lung hydroxyproline content, inflammation and fibrosis score were measured. Western blotting, zymography and reverse zymography were performed at 3, 7, 14, 28 days after bleomycin instillation in order to evaluate the MMP-2,-9, and TIMP-1,-2 expression level. ELISA was performed to determine the IL-4 and IL-13 level in a lung homogenate. Results : 1. 7 days after bleomycin instillation, inflammatory changes were more severe in the bleomycin+$IFN-{\gamma}$ group than the bleomycin group (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$2.08{\pm}0.15:2.74{\pm}0.29$, P<0.05), but 28 days after bleomycin instillation, lung fibrosis was significantly reduced as a result of the $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$3.94{\pm}0.43:2.64{\pm}0.13$, P<0.05). 2. 28 days after bleomycin instillation, the lung hydroxyproline content was significantly reduced as a result of $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$294.04{\pm}31.73{\mu}g/g:194.92{\pm}15.51{\mu}g/g$, P<0.05). 3. Western blotting showed that the MMP-2 level was increased as a result of the bleomycin instillation and highest in the 14 days after bleomycin instillation. 4. In zymography, the active forms of MMP-2 were significantly increased as a result of the $IFN-{\gamma}$ treatment 3 days after the bleomycin instillation, bleomycin+$IFN-{\gamma}$ group (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$209.63{\pm}7.60%:407.66{\pm}85.34%$, P<0.05), but 14 days after the bleomycin instillation, the active forms of MMP-2 were significantly reduced as a result of the $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$159.36{\pm}20.93%:97.23{\pm}12.50%$, P<0.05). 5. The IL-4 levels were lower in the bleomycin and bleomycin+$IFN-{\gamma}$ groups but this was not significant, and the IL-13 levels showed no difference between the experiment groups. Conclusion : The author found that lung inflammation was increased in the early period but the pulmonary fibrosis was inhibited in the late stage as a result of $IFN-{\gamma}$. The inhibition of pulmonary fibrosis by $IFN-{\gamma}$ appeared to be associated with the inhibition of MMP-2 activation by $IFN-{\gamma}$. Further studies on the mechanism of the regulation of MMP-2 activation and the effects of MMP-2 activation on pulmonary fibrosis is warranted in the future.

• Radiation Oncology Journal
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• v.19 no.2
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• pp.171-180
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• 2001

Purpose : Expression of TIMP, intrinsic inhibitor of MMP, is regulated by signal transduction in response to genotoxins and is likely to be an important step in metastasis, angiogenesis and wound healing after ionizing radiation. Therefore, we studied radiation mediated TIMP expression and its mechanism in head and neck cancer cell lines. Materials and Methods : Human head and neck cancer cell lines established at Asan Medical Center were used and radiosensitivity $(D_0)$, radiation cytotoxicity and metastatic potential were measured by clonogenic assay, n assay and invasion assay, respectively. The conditioned medium was prepared at 24 hours and 48 hours after 2 Gy and 10 Gy irradiation and expression of TIMP protein was measured by Elisa assay with specific antibodies against human TIMP. hTIMP1 promoter region was cloned and TIMP1 luciferase reporter vector was constructed. The reporter vector was transfected to AMC-HN-1 and -HN-9 cells with or without expression vector Ras, then the cells were exposed to radiation or PMA, PKC activator. EMSA was peformed with oligonucleotide (-59/-53 element and SP1) of TIMP1 promoter. Results : $D_0$ of HN-1, -2, -3, -5 and -9 cell lines were 1.55 Gy, 1.8 Gy, 1.5 Gt, 1.55 Gy and 2.45 Gy respectively. n assay confirmed cell viability, over $94\%$ at 24hrs, 48hrs after 2 Gy irradiation and over 73% after 10 Gy irradiation. Elisa assay confirmed that cells secreted TIMP1, 2 proteins continuously. After 2 Gy irradiation, TIMP2 secretion was decreased at 24hrs in HN-1 and HN-9 cell lines but after 10 Gy irradiation, it was increased in all cell lines. At 48hrs after irradiation, it was increased in HN-1 but decreased in HN-9 cells. But the change in TIMP secretion by RT was mild. The transcription of TIMP1 gene in HN-1 was induced by PMA but in HN-9 cell lines, it was suppressed. Wild type Ras induced the TIMP-1 transcription by 20 fold and 4 fold in HN-1 and HN-9 respectively. The binding activity to -59/-53, AP1 motif was increased by RT, but not to SP1 motif in both cell lines. Conclusions : We observed the difference of expression and activity of TIMPs between radiosensitive and radioresistant cell line and the different signal transduction pathway between in these cell lines may contribute the different radiosensitivity. Further research to investigate the radiation response and its signal pathway of TIMPs is needed.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.