• Journal of Ginseng Research
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• v.41 no.1
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• pp.1-9
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• 2017

Panax ginseng Meyer, belonging to the genus Panax of the family Araliaceae, is known for its human immune system-related effects, such as immune-boosting effects. Ginseng polysaccharides (GPs) are the responsible ingredient of ginseng in immunomodulation, and are classified as acidic and neutral GPs. Although GPs participate in various immune reactions including the stimulation of immune cells and production of cytokines, the precise function of GPs together with its potential receptor(s) and their signal transduction pathways have remained largely unknown. Animal lectins are carbohydrate-binding proteins that are highly specific for sugar moieties. Among many different biological functions in vivo, animal lectins especially play important roles in the immune system by recognizing carbohydrates that are found exclusively on pathogens or that are inaccessible on host cells. This review summarizes the immunological activities of GPs and the diverse roles of animal lectins in the immune system, suggesting the possibility of animal lectins as the potential receptor candidates of GPs and giving insights into the development of GPs as therapeutic biomaterials for many immunological diseases.

• Food Science and Biotechnology
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• v.17 no.6
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• pp.1261-1264
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• 2008

In the present study, a randomized, double-blind, placebo-controlled trial to determine the effect of conjugated linoleic acid (CLA) supplementation (50:50 ratio of cis-9, trans-11 and trans-10, cis-12 isomers) for 8 weeks on body composition and biochemical parameters in healthy overweight/obese (body mass index, BMI${\geq}23\;kg/m^2$) Korean subjects was performed, Thirty participants (3 males and 27 females) were randomized to receive placebo (2.4 g olive oil/day) or 2.4g/day CLA (mixture containing 36.9% of cis-9, trans-11 and 37.9% of trans-10, cis-12). Eight weeks of CLA supplementation significantly decreased body weight by -0.75kg, BMI by $-0.27\;kg/m^2$, and hip circumference by -1.11 cm. The reduction of body weight was ascribed to the reduction of body fat mass (-0.59 kg) and lean body mass (-0.18 kg), although these changes were not significant. No significant differences in serum lipid profiles, liver function enzyme activities, and protein concentration were observed in either the CLA or placebo groups. These results indicate that short tenn supplementation (8 weeks) with CLA (2.4 g/day) may decrease body weight in Korean overweight/obese subjects.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.79-82
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• 2010

Three types of leaf domatia; Pocket (P), Tufts (T) and Tufts-Pocket (TP) were observed in the five species of Cornus namely; Cornus kousa, C. controversa, C. officinalis, C. walteri and C. alba. In C. walteri no tufts were observed, the domatia was just a well developed pocket one. In C. officinalis and C. kousa, tufts domatia of brownish color were observed but C. officinalis developed denser tufts than those observed in C. kousa. Unlike in C. kousa where the domatia covered about only 1/2 of the axil, in the C. officinalis tufts covered almost 3/4 of the axil. In both species the tufts domatia were located in the inner side of the leaf axil. In C. controversa and C. alba whitish colored tufts were observed covering Pockets and hence the Tuft Pocket domatia. In C. controversa the tufts were more than in C. alba but in both species the tufts were short and were located in the inner sides of the axil. Thus, based on these physiological features it was concluded that C. officinalis and C. kousa are sister species likewise C. controversa and C. alba while C. walteri belong to another lineage. The advancement of domatia (absence of tufts) in C. walteri suggests that they are the most advanced while C. officinalis and C. kousa the most primitive due to their possession of highly developed tufts and C. controversa and C. alba the intermediates.

• Genomics & Informatics
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• v.19 no.2
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• pp.15.1-15.7
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• 2021

The direction of evolution can estimate based on the variation among nonsynonymous to synonymous substitution. The simulative study investigated the nucleotide sequence of closely related strains of respiratory syndrome viruses, codon-by-codon with maximum likelihood analysis, z selection, and the divergence time. The simulated results, dN/dS > 1 signify that an entire substitution model tends towards the hypothesis's positive evolution. The effect of transition/transversion proportion, Z-test of selection, and the evolution associated with these respiratory syndromes, are also analyzed. Z-test of selection for neutral and positive evolution indicates lower to positive values of dN-dS (0.012, 0.019) due to multiple substitutions in a short span. Modified Nei-Gojobori (P) statistical technique results also favor multiple substitutions with the transition/transversion rate from 1 to 7. The divergence time analysis also supports the result of dN/dS and imparts substantiating proof of evolution. Results conclude that a positive evolution model, higher dN-dS, and transition/transversion ratio significantly analyzes the evolution trend of severe acute respiratory syndrome coronavirus 2, severe acute respiratory syndrome coronavirus, and Middle East respiratory syndrome coronavirus.

• Genomics & Informatics
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• v.18 no.3
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• pp.30.1-30.7
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• 2020

The novel coronavirus pandemic that has originated from China and spread throughout the world in three months. Genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) predecessor, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) play an important role in understanding the concept of genetic variation. In this paper, the genomic data accessed from National Center for Biotechnology Information (NCBI) through Molecular Evolutionary Genetic Analysis (MEGA) for statistical analysis. Firstly, the Bayesian information criterion (BIC) and Akaike information criterion (AICc) are used to evaluate the best substitution pattern. Secondly, the maximum likelihood method used to estimate of transition/transversions (R) through Kimura-2, Tamura-3, Hasegawa-Kishino-Yano, and Tamura-Nei nucleotide substitutions model. Thirdly and finally nucleotide frequencies computed based on genomic data of NCBI. The results indicate that general times reversible model has the lowest BIC and AICc score 347,394 and 347,287, respectively. The transition/transversions bias for nucleotide substitutions models varies from 0.56 to 0.59 in MEGA output. The average nitrogenous bases frequency of U, C, A, and G are 31.74, 19.48, 28.04, and 20.74, respectively in percentages. Overall the genomic data analysis of SARS-CoV-2, SARS-CoV, and MERS-CoV highlights the close genetic relationship.

• Quantitative Bio-Science
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• v.36 no.1
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• pp.23-31
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• 2017

Datasets from DNA microarray experiments, which are in the form of large matrices of expression levels of genes, often have missing values. However, the existing statistical methods including the principle components analysis (PCA) and Hotelling's t-test are not directly applicable for the datasets having missing values due to the fact that they assume the observed dataset is complete in general. Many methods have been proposed in previous literature to impute the missing in the observed data. Troyanskaya et al. [1] study the k-nearest neighbor (kNN) imputation, Kim et al. [2] propose the local least squares (LLS) method and Rubin [3] propose the multiple imputation (MI) for missing values. To identify differentially expressed genes, we propose a new testing procedure when the missing exists in the observed data. The proposed procedure uses the Stouffer's z-scores and combines the test results of individual imputed samples, which are dependent to each other. We numerically show that the proposed test procedure based on MI performs better than the existing test procedures based on single imputation (SI) by comparing their ROC curves. We apply the proposed method to analyzing a public microarray data.

• Genomics & Informatics
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• v.17 no.2
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• pp.17.1-17.3
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• 2019

Text mining has become an important research method in biology, with its original purpose to extract biological entities, such as genes, proteins and phenotypic traits, to extend knowledge from scientific papers. However, few thorough studies on text mining and application development, for plant molecular biology data, have been performed, especially for rice, resulting in a lack of datasets available to solve named-entity recognition tasks for this species. Since there are rare benchmarks available for rice, we faced various difficulties in exploiting advanced machine learning methods for accurate analysis of the rice literature. To evaluate several approaches to automatically extract information from gene/protein entities, we built a new dataset for rice as a benchmark. This dataset is composed of a set of titles and abstracts, extracted from scientific papers focusing on the rice species, and is downloaded from PubMed. During the 5th Biomedical Linked Annotation Hackathon, a portion of the dataset was uploaded to PubAnnotation for sharing. Our ultimate goal is to offer a shared task of rice gene/protein name recognition through the BioNLP Open Shared Tasks framework using the dataset, to facilitate an open comparison and evaluation of different approaches to the task.

• Genomics & Informatics
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• v.16 no.4
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• pp.23.1-23.5
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• 2018

Virus taxonomy was initially determined by clinical experiments based on phenotype. However, with the development of sequence analysis methods, genotype-based classification was also applied. With the development of genome sequence analysis technology, there is an increasing demand for virus taxonomy to be extended from in vivo and in vitro to in silico. In this study, we verified the consistency of the current International Committee on Taxonomy of Viruses taxonomy using an in silico approach, aiming to identify the specific sequence for each virus. We applied this approach to norovirus in Caliciviridae, which causes 90% of gastroenteritis cases worldwide. First, based on the dogma "protein structure determines its function," we hypothesized that the specific sequence can be identified by the specific structure. Firstly, we extracted the coding region (CDS). Secondly, the CDS protein sequences of each genus were annotated by the conserved domain database (CDD) search. Finally, the conserved domains of each genus in Caliciviridae are classified by RPS-BLAST with CDD. The analysis result is that Caliciviridae has sequences including RNA helicase in common. In case of Norovirus, Calicivirus coat protein C terminal and viral polyprotein N-terminal appears as a specific domain in Caliciviridae. It does not include in the other genera in Caliciviridae. If this method is utilized to detect specific conserved domains, it can be used as classification keywords based on protein functional structure. After determining the specific protein domains, the specific protein domain sequences would be converted to gene sequences. This sequences would be re-used one of viral bio-marks.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.335-348
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• 2019

Cell segmentation and counting represent one of the most important tasks required in order to provide an exhaustive understanding of biological images. Conventional features suffer the lack of spatial consistency by causing the joining of the cells and, thus, complicating the cell counting task. We propose, in this work, a cascade of networks that take as inputs different versions of the original image. After constructing a Gaussian pyramid representation of the microscopy data, the inputs of different size and spatial resolution are given to a cascade of deep convolutional autoencoders whose task is to reconstruct the segmentation mask. The coarse masks obtained from the different networks are summed up in order to provide the final mask. The principal and main contribution of this work is to propose a novel method for the cell counting. Unlike the majority of the methods that use the obtained segmentation mask as the prior information for counting, we propose to utilize the hidden latent representations, often called the high-level features, as the inputs of a neural network based regressor. While the segmentation part of our method performs as good as the conventional deep learning methods, the proposed cell counting approach outperforms the state-of-the-art methods.

• Genomics & Informatics
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• v.19 no.1
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• pp.7.1-7.13
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• 2021

Levodopa (L-DOPA) therapy is normally practised to treat motor pattern associated with Parkinson disease (PD). Additionally, several inhibitory drugs such as Entacapone and Opicapone are also cosupplemented to protect peripheral inactivation of exogenous L-DOPA (~80%) that occurs due to metabolic activity of the enzyme catechol-O-methyltransferase (COMT). Although, both Entacapone and Opicapone have U.S. Food and Drug Administration approval but regular use of these drugs is associated with high risk of side effects. Thus, authors have focused on in silico discovery of phytochemicals and evaluation of their effectiveness against human soluble COMT using virtual screening, molecular docking, drug-like property prediction, generation of pharmacophoric property, and molecular dynamics simulation. Overall, study proposed, nine phytochemicals (withaphysalin D, withaphysalin N, withaferin A, withacnistin, withaphysalin C, withaphysalin O, withanolide B, withasomnine, and withaphysalin F) of plant Withania somnifera have strong binding efficiency against human COMT in comparison to both of the drugs i.e., Opicapone and Entacapone, thus may be used as putative bioenhancer in L-DOPA therapy. The present study needs further experimental validation to be used as an adjuvant in PD treatment.