• Journal of Ginseng Research
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• v.42 no.2
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• pp.218-224
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• 2018

Background: Compound K (CK) is a ginsenoside, a metabolite of Panax ginseng. There is interest both in increasing skin health and antiaging using natural skin care products. In this study, we explored the possibility of using CK as a cosmetic ingredient. Methods: To assess the antiaging effect of CK, RT-PCR was performed, and expression levels of matrix metalloproteinase-1, cyclooxygenase-2, and type I collagen were measured under UVB irradiation conditions. The skin hydrating effect of CK was tested by RT-PCR, and its regulation was explored through immunoblotting. Melanin content, melanin secretion, and tyrosinase activity assays were performed. Results: CK treatment reduced the production of matrix metalloproteinase-1 and cyclooxygenase-2 in UVB irradiated NIH3T3 cells and recovered type I collagen expression level. Expression of skin hydrating factors-filaggrin, transglutaminase, and hyaluronic acid synthases-1 and -2-were augmented by CK and were modulated through the inhibitor of ${\kappa}B{\alpha}$, c-Jun N-terminal kinase, or extracellular signal-regulated kinases pathway. In the melanogenic response, CK did not regulate tyrosinase activity and melanin secretion, but increased melanin content in B16F10 cells was observed. Conclusion: Our data showed that CK has antiaging and hydrating effects. We suggest that CK could be used in cosmetic products to protect the skin from UVB rays and increase skin moisture level.

• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.214-224
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• 2015

The economy of India and so also of many Asian countries depends on bamboos and their uses are not only in domestic items but also in rural housing and raw materials to several industries and germplasm characterization is an important link between the conservation and utilization of plant genetic resources. Classical taxonomic studies of the bamboos are based on floral morphology and growth habit, which can cause problems in identification due to erratic flowering coupled with different biotic agencies and environmental factors. Identification and genetic relationships among accessions of Thamnocalamus falconeri were investigated using morphology and random amplified polymorphic DNAs (RAPD) technique. Analysis started by using 51 vegetative characters and forty two 10-mer primers that allowed us to distinguish different genotypes hailing from different eco- zones of Garhwal Himalayas (India). The selected primers (12) were used for identification and for establishing a profiling system to estimate genetic diversity. A total of 79.33% polymorphism was estimated by using 12 selected primers. The genetic similar analysis was conducted based on binary digits i.e. presence (1) or absence (0) of bands, which revealed a wide range of variability among the species whereas genetic relatedness was quite high based on vegetative characters. Cluster analysis clearly showed two major clusters for both of the markers viz. morphology and RAPD belonging to 10 accessions of T. falconeri. Two major clusters were further divided into minor clusters. Cluster based on RAPD marker showed grouping of accessions of closed locality whereas analogy was reported for vegetative traits. The RAPD technique has the potential for use in species identification and genetic relationships studies of bamboo for breeding program.

• Korean Journal of Poultry Science
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• v.39 no.4
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• pp.279-282
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• 2012

Clinical-chemical traits are commonly used biomarkers to examine the health status of individuals. There is an appreciable range of normal variation in most clinical-chemical traits and the determining factors of this variation have been relatively uninvestigated in chickens. The aim of this study was to estimate the genetic parameters (i.e., heritability, genetic correlation) for 8 clinical-chemical traits (glucose, total protein, creatinine, high-density lipoprotein cholesterol, total cholesterol, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase and amylase) in an $F_1$ intercross established by purebred breeding among the 5 lines of Korean native chickens. Phenotypic data were collected from approximately 600 $F_1$ animals. The genetic parameters for the clinical-chemical traits estimated by a mixed animal model using the restricted maximum likelihood method were presented. Estimated heritabilities ranged from 8.9% (glucose) to 39.6% (high-density lipoprotein cholesterol). Interestingly, both the sign and the size of the genetic and phenotypic correlations were largely different between the same several pair of clinical-chemical traits. The findings in this study will provide useful information to address issues in both quantitative trait locus study and genetic management in Korean native chickens.

• The Plant Pathology Journal
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• v.33 no.3
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• pp.296-306
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• 2017

Sugarcane mosaic virus (SCMV) is one of the most damaging viruses infecting sugarcane, maize and some other graminaceous species around the world. To investigate the genetic diversity of SCMV in Iran, the coat protein (CP) gene sequences of 23 SCMV isolates from different hosts were determined. The nucleotide sequence identity among Iranian isolates was more than 96%. They shared nucleotide identities of 75.5-99.9% with those of other SCMV isolates available in GenBank, the highest with the Egyptian isolate EGY7-1 (97.5-99.9%). The results of phylogenetic analysis suggested five divergent evolutionary lineages that did not completely reflect the geographical origin or host plant of the isolates. Population genetic analysis revealed greater between-group than within-group evolutionary divergence values, further supporting the results of the phylogenetic analysis. Our results indicated that natural selection might have contributed to the evolution of isolates belonging to the five identified SCMV groups, with infrequent genetic exchanges occurring between them. Phylogenetic analyses and the estimation of genetic distance indicated that Iranian isolates have low genetic diversity. No recombination was found in the CP cistron of Iranian isolates and the CP gene was under negative selection. These findings provide a comprehensive analysis of the population structure and driving forces for the evolution of SCMV with implications for global exchange of sugarcane germplasm. Gene flow, selection and somehow homologous recombination were found to be the important evolutionary factors shaping the genetic structure of SCMV populations.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5957-5960
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• 2013

Background: Gliomas are the most common type of primary brain tumor in adults, and the X-ray repair complementing group 1 gene (XRCC1) is an important candidate gene influencing its risk. The objective of this study was to detect the influence of XRCC1 genetic polymorphisms on glioma risk. Materials and Methods: A total of 629 glioma patients and 641 cancer-free subjects were enrolled in this case-control study. The genotypes of the c.1471G>A genetic polymorphism were determined by created restriction site-polymerase chain reaction (CRS-PCR) and DNA sequencing methods. The influence of the XRCC1 genetic polymorphism on glioma risk was evaluated by association analysis. Results: Our data indicated that the alleles/genotype of this genetic variant was statistically associated with glioma risk. The AA genotype was statistically associated with the increased risk of glioma compared to the GG wild genotype (odds ratios (OR) = 1.89, 95% CI 1.25-2.87, P = 0.003). The allele-A may contribute to increased the susceptibility to glioma (OR = 1.23, 95% CI 1.04-1.46, P = 0.017). Conclusions: These preliminary findings indicate that the c.1471G>A genetic polymorphism of XRCC1 has the potential to influence glioma susceptibility, and might be used as molecular marker for assessing glioma risk.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.602-604
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• 2017

As human life span has increased, people have wanted to live healthier desires. Especially Korea has rapidly entered an aging society, leading to the burden of medical expenses to the increase of disease accompanying aging. To alleviate the burden of medical expenses, prediction and prevention are important rather than treatment of diseases. It is possible to predict and prevent diseases by measuring individual genetic information. In order to utilize individual's genetic information Korea's genetic information is grasped through SNP (800 thousand) and GWAS optimized for the discovery of genetic factors of phenotype and disease of Koreans, The genetic information of each individual is analyzed in the genetic (constitutional) characteristics of the individual. In this thesis we develop a classification index so that we can classify populations of specific chronic diseases (obesity, diabetes or cardiovascular system). Try to develop health care services to manage custom diet and exercise associated with chronic illness.

• Genomics & Informatics
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• v.16 no.4
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• pp.31.1-31.7
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• 2018

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.

• Animal Bioscience
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• v.34 no.1
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• pp.12-19
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• 2021

Objective: The objectives of the current study were to study the main environmental factors affecting birth weight (BW) and weaning weight (WW), estimate variance components, genetic parameters and genetic trend and to evaluate the variability and relationships among breeding value of BW and WW using principal components analysis (PCA). Methods: A total of 16,370 records were collected from 8,271 buffalo calves. Genetic parameters and breeding values were estimated using a bivariate animal model which includes direct, maternal and permanent maternal effects. These estimates were standardized and used in PCA. Results: The direct heritability estimates were 0.06 and 0.41 for BW and WW, respectively whereas direct maternal heritability values were 0.03 and 0.14, respectively. Proportions of variance due to permanent environmental effects of dam were 0.455 and 0.280 for BW and WW respectively. The genetic correlation between BW and WWs was weak approaching zero, but the maternal correlation was 0.26. The first two principal components (PC1 and PC2) were estimated utilizing the standardized breeding values according to Kaiser method. The total variance explained by the first two PCs was 71.17% in which 45.91% and 25.25% were explained by PC1 and PC2, respectively. The direct breeding values of BW were related to PC2 but those of WW and maternal breeding values of BW and WWs were associated with PC1. Conclusion: The results of genetic parameters and PCA indicate that BW and WWs were not genetically correlated and improving growth traits of Egyptian buffaloes could be achieved using WW without any adverse effect by BW.

• Journal of Plant Biotechnology
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• v.47 no.4
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• pp.298-308
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• 2020

Genetic diversity among Thaumatococcus daniellii populations in the southwestern region of Nigeria were assessed using morphometric and molecular markers to determine the population structure and existing genetic relationship for its improvement, conservation and sustainable utilisation. Populations from five locations in each of the six states were used for the study. Morphometric data were collected on folia characters and analysed for variability. Genome DNA was isolated from the plant leaf and amplified by polymerase chain reaction with inter-simple sequence repeat markers (ISSR) to determine the allelic polymorphism, marker effectiveness and genetic relationship of the population. The results showed significant variations in petiole length and leaf dimensions of the populations within and across the states. These morphometric traits are the major parameters that delimit the populations and they correlated significantly at P≤0.05. Analysis of the electrophoregram showed that the ISSR markers are effective for the diversity study. A total of 136 loci were amplified with an average of 7.16 loci per marker, 63.2% of the loci were polymorphic. The Principal Coordinate Analysis revealed that seven factors accounted for 81.6% of the variation and the dendrogram separated the populations into two major groups at a genetic distance of 10 (about 90% similarity) with sub-groups and clusters. Most populations within the state had a high degree of similarity, nonetheless, strong genetic relationship exists among populations from different states. The close relationship between populations across the states suggests a common progenitor, which are likely separated by ecological or geographical isolation mechanisms.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.