• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

• Journal of Microbiology and Biotechnology
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• v.26 no.9
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• pp.1527-1532
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• 2016

Strain SPF4211, having hyaluronidase (HAase) inhibition activity, was isolated from P. davidiana (Carriere) Franch fruit (PrDF) sugar extract. The phenotypic and biochemical properties based on 16S rDNA sequencing and an API 50 CHB kit suggested that the organism was B. subtilis. To optimize the HAase inhibition activity of PrDF extract by fermentation of strain SPF4211, a central composite design (CCD) was introduced based on three variables: concentration of PrDF extract (X₁: 1-5%), amount of starter culture (X₂: 1-5%), and fermentation time (X₃: 0-7 days). The experimental data were fitted with quadratic regression equations, and the accuracy of the equations was analyzed by ANOVA. The statistical model predicted the highest HAase inhibition activity of 37.936% under the optimal conditions of X₁ = 1%, X₂ = 2.53%, and X₃ = 7 days. The optimized conditions were validated by observation of an actual HAase inhibition activity of 38.367% from extract of PrDF fermented by SPF4211. These results agree well with the predicted model value.

• Journal of Microbiology and Biotechnology
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• v.30 no.8
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• pp.1132-1141
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• 2020

Inflammatory bowel disease (IBD) is an increasing global burden and a predisposing factor to colorectal cancer. Although a number of treatment options are available, the side effects could be considerable. Studies on fecal microbiota transplantation (FMT) as an IBD intervention protocol require further validation as the underlying mechanisms for its attenuating effects remain unclear. This study aims to demonstrate the ameliorative role of FMT in an ulcerative colitis (UC) model induced by dextran sulfate sodium (DSS) and elucidate its relative mechanisms in a mouse model. It was shown that FMT intervention decreased disease activity index (DAI) levels and increased the body weight, colon weight and colon length of experimental animals. It also alleviated histopathological changes, reduced key cytokine expression and oxidative status in the colon. A down-regulated expression level of genes associated with NF-κB signaling pathway was also observed. The results of 16S rRNA gene sequencing showed that FMT intervention restored the gut microbiota to the pattern of the control group by increasing the relative abundance of Firmicutes and decreasing the abundances of Bacteroidetes and Proteobacteria. The relative abundances of the genera Lactobacillus, Butyricicoccus, Lachnoclostridium, Olsenella and Odoribacter were upregulated but Helicobacter, Bacteroides and Clostridium were reduced after FMT administration. Furthermore, FMT administration elevated the concentrations of SCFAs in the colon. In conclusion, FMT intervention could be suitable for UC control, but further validations via clinical trials are recommended.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.91-100
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• 2015

The present study was conducted to screen candidate probiotic strains for anti-inflammatory activity. Initially, a nitric oxide (NO) assay was used to test selected candidate probiotic strains for anti-inflammatory activity in cultures of the murine macrophage cell line, RAW 264.7. Then, the in vitro probiotic properties of the strains, including bile tolerance, acid resistance, and growth in skim milk media, were investigated. We also performed an in vitro hydrophobicity test and an intestinal adhesion assay using Caenorhabditis elegans as a surrogate in vivo model. From our screening, we obtained 4 probiotic candidate lactic acid bacteria (LAB) strains based on their anti-inflammatory activity in lipopolysaccharide (LPS)-stimulated RAW 264.7 cell cultures and the results of the in vitro and in vivo probiotic property assessments. Molecular characterization using 16S rDNA sequencing analysis identified the 4 LAB strains as Lactobacillus plantarum. The selected L. plantarum strains (CAU1054, CAU1055, CAU1064, and CAU1106) were found to possess desirable in vitro and in vivo probiotic properties, and these strains are good candidates for further investigations in animal models and human clinical studies to elucidate the mechanisms underlying their anti-inflammatory activities.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2811-2819
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• 2016

Multiple genetic and environmental factors have been reported to play key role in the development of nasopharyngeal carcinoma (NPC). Here, we investigated interactions of XRCC1 Arg399Gln and XRCC2 Arg188His polymorphisms and environmental factors in modulating susceptibility to NPC in Northeast India. One-hundred NPC patients, 90 first-degree relatives of patients and 120 controls were enrolled in the study. XRCC1 Arg399Gln and XRCC2 Arg188His polymorphisms were determined using PCR-RFLP, and the results were confirmed by DNA sequencing. Logistic regression (LR) and multifactor dimensionality reduction (MDR) approaches were applied for statistical analysis. The XRCC1 Gln/Gln genotype showed increased risk (OR=2.76; P<0.024) of NPC. However, individuals with both XRCC1 and XRCC2 polymorphic variants had 3.2 fold elevated risk (P<0.041). An enhanced risk of NPC was also observed in smoked meat (OR=4.07; P=0.004) and fermented fish consumers (OR=4.34, P=0.001), and tobacco-betel quid chewers (OR=7.00; P=0.0001) carrying XRCC1 polymorphic variants. However, smokers carrying defective XRCC1 gene showed the highest risk (OR = 7.47; P<0.0001). On MDR analysis, the best model for NPC risk was the five-factor model combination of XRCC1 variant genotype, fermented fish, smoked meat, smoking and chewing (CVC=10/10; TBA=0.636; P<0.0001); whereas in interaction entropy graphs, smoked meat and tobacco chewing showed synergistic interactions with XRCC1. These findings suggest that interaction of genetic and environmental factors might increase susceptibility to NPC in Northeast Indian populations.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5241-5243
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• 2012

Background: Prostate cancer (Pca) is one of the most common complex and polygenic diseases in men. The X-ray repair complementing group 1 gene (XRCC1) is an important candidate in the pathogenesis of Pca. The purpose of this study was to evaluate the association between single nucleotide polymorphisms in the XRCC1 gene and susceptibility to Pca. Materials and Methods: XRCC1 gene polymorphisms and associations with susceptibility to Pca were investigated in 193 prostate patients and 188 cancer-free Chinese men. Results: The c.910A>G variant in the exon9 of XRCC1 gene could be detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and DNA sequencing methods. Significantly increased susceptibility to prostate cancer was noted in the homozygote comparison (GG versus AA: OR=2.95, 95% CI 1.46-5.42, ${\chi}^2$=12.36, P=0.001), heterozygote comparison (AG versus AA: OR=1.76, 95% CI 1.12-2.51, ${\chi}^2$=4.04, P=0.045), dominant model (GG/AG versus AA: OR=1.93, 95% CI 1.19-2.97, ${\chi}^2$=9.12, P=0.003), recessive model (GG versus AG+AA: OR=2.17, 95% CI 1.33-4.06, ${\chi}^2$=8.86, P=0.003) and with allele contrast (G versus A: OR=1.89, 95% CI 1.56-2.42, ${\chi}^2$=14.67, P<0.000). Conclusions: These findings suggest that the c.910A>G polymorphism of the XRCC1 gene is associated with susceptibility to Pca in Chinese men, the G-allele conferring higher risk.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.12
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• pp.1675-1681
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• 2016

The aim of this study was to detect positional candidate genes located within the support interval (SI) regions based on the results of red blood cell, mean corpuscular volume (MCV), and mean corpuscular hemoglobin quantitative trait locus (QTL) in Sus scrofa chromosome 13, and to verify the correlation between specific single-nucleotide polymorphisms (SNPs) located in the exonic region of the positional candidate gene and the three genetic traits. The flanking markers of the three QTL SI regions are SW38 and S0215. Within the QTL SI regions, 44 genes were located, and runt-related transcription factor 1, dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A (DYRK1A), and potassium inwardly-rectifying channel, subfamily J, member 15 KCNJ15-which are reported to be related to the hematological traits and clinical features of Down syndrome-were selected as positional candidate genes. The ten SNPs located in the exonic region of the three genes were detected by next generation sequencing. A total of 1,232 pigs of an $F_2$ resource population between Landrace and Korean native pigs were genotyped. To investigate the effects of the three genes on each genotype, a mixed-effect model which is the considering family structure model was used to evaluate the associations between the SNPs and three genetic traits in the $F_2$ intercross population. Among them, the MCV level was highly significant (nominal $p=9.8{\times}10^{-9}$) in association with the DYRK1A-SNP1 (c.2989 G$F_2$ intercross, our approach has limited power to distinguish one particular positional candidate gene from a QTL region.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5361-5365
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• 2013

The objective of this study was to evaluate the influence of a genetic variant in the multidrug resistance 1 gene (MDR1) on hepatocellular carcinoma (HCC) risk. This case-control study was conducted in a Chinese population of 645 HCC cases and 658 cancer-free controls. The genotype of the c.3751G>A genetic variant in the MDR1 gene was investigated by created restriction site-polymerase chain reaction (CRS-PCR) and DNA sequencing methods. Our data demonstrated significantly differences detected in the allelic and genotypic frequencies between HCC cases and those of cancer-free controls. Association analyses indicated that there were statistically increased risk of HCC in the homozygote comparison (AA versus (vs.) GG: OR=2.22, 95% CI 1.51-3.27, ${\chi}^2$=16.90, P<0.001), dominant model (AA/GA vs. GG: OR=1.25, 95% CI 1.00-1.55, ${\chi}^2$=3.98, P=0.046), recessive model (AA vs. GA/GG: OR=2.14, 95% CI 1.47-3.09, ${\chi}^2$=16.68, P<0.001) and allele comparison (A vs. G: OR=1.33, 95% CI 1.13-1.57, ${\chi}^2$=11.66, P=0.001). The allele-A and genotype-AA may contribute to HCC susceptibility. These preliminary findings suggest that the c.3751G>A genetic variant in the MDR1 gene is potentially related to HCC susceptibility in a Chinese Han population, and might be used as a molecular marker for evaluating HCC susceptibility.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.673-680
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• 2011

The aim of this study was to identify the polymorphism on fatty acid binding protein (FABP4) gene promoter region and its association with carcass traits in Hanwoo. We performed PCR-direct sequencing of FABP4 promoter region to identify single nucleotide polymorphism (SNPs) using unrelated 24 Hanwoo bulls. Four SNPs (-298A>G, -472A>G, -887A>G, -862A>G) were detected in the promoter region and genotyped on 583 Hanwoo steers. A linear mixed model revealed an association of three SNPs (-298A>G, -472A>G and -862A>G) with carcass weight and marbling score in dominance model (P<0.05). The animals with AA genotypes for the three SNPs were heavier carcass weight (5 kg) than animals with GG genotypes in the statistical analysis. For the marbling score, the AA genotype was lower effect of marbling score (0.21) than GG genotypes. In conclusion, this study indicates an important role for three SNPs detected in promoter region of FABP4 in determining carcass weight and marbling score in Hanwoo.