Identification of Thermoduric Leuconostoc mesenteroides BD5H That Can Grow at Over 42℃

권오식,이삼빈 계명대학교 자연과학연구소 2017 Quantitative Bio-Science Vol.36 No.1

Lactic acid bacteria was isolated from Chonggak and Baechu kimchi and characterized by a sugar fermentation analysis. Leuconostoc strains (1B12, BD5H and CH5H) growing at 40℃ were isolated and compared with L. mesenteroides subsp. mesenteroides KCTC 3722 grown at a mesophilic temperature (30℃). Among these, L. mesenteroides BD5H could grow at 42℃ (pH 4.70±0.02) and could still grow at 43℃ (pH 5.51±0.04), which indicates that is a thermoduric bacterial strain. In the fermentation of pentose, all strains had exactly the same patterns of fermentation, except L. mesenteroides CH5H, which could not ferment ribose (pH 5.92±0.04). These strains had significantly different abilities to ferment galactose, with only L. mesenteroides BD5H capable of active galactose fermentation (pH 4.94±0.03). All strains failed to ferment rhamnose compared to other hexoses (p<0.001). L. mesenteroides BD5H could ferment cellobiose (4.42± 0.02), while the remaining strains could not. L. mesenteroides BD5H could ferment raffinose (pH 4.66±0.07), but not melezitose. These fermentation characteristics are typical of L. mesenteroides. Interestingly L. mesenteroides BD5H could ferment amygdalin (pH 4.82±0.04), while other strains could not (p<0.001). Furthermore L. mesenteroides BD5H could ferment salicin (pH 4.77±0.15), while the other strains could not. According to 16S rRNA sequence analysis using primers 785F and 907R, all tested strains were L. mesenteroides, with 99~100% identity. Significant differences were observed between these strains in their ability to ferment carbohydrates, which enabled better differentiation than that afforded by 16S rRNA sequence analysis. Carbohydrate fermentation analysis allowed for subspecies-level identification of L. mesenteroides isolated from Baechu and Chonggak kimchi.

1,6-Disubstituted-1H-benzo[d]imidazol-2(3H)-one Derivatives as PIM Kinase Inhibitors

추현승,정승익,Hong, Victor Sukbong,이진호 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

PIM proteins, which are proto-oncogenic serine/threonine kinases that are highly expressed in hematological malignancies and solid cancers, are potential molecular targets for anticancer drugs. 1H-Benzo[d]imidazol-2(3H)-one is a key structure in drug discovery, and several of its analogues have been developed as therapeutics. 1,6-Disubstituted-1H- benzo[d]imidazol-2(3H)-one derivatives were synthesized and evaluated in terms of their inhibitory activities against all three PIM kinases. Systematic structural modifications of benzo[d]imidazol-2-one at the 1- and 6-positions led to the discovery of pan-PIM inhibitors represented by 9. The binding modes of the synthesized compounds and the effects of the substituents on the selectivities among the PIM kinase isoforms were studied to confirm 1,6-disubstituted-1H- benzo[d]imidazol-2(3H)-one as a scaffold for use in the discovery of PIM kinase inhibitors.

Integrated Analytic Methodology Using Visual Image and Meta-Data for Product Recommendation

이용학,오재훈,양승민,김성환 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

Because the big data industry holds a significant position nowadays, Meta-Data has been adopted rapidly in various fields. In this paper, we introduce a model that exploits Meta-Data consisting of numerous production data to extract features using a pretrained deep learning model with image and text information. Thus, we can build a relational model between the production data to realize a recommendation system. Regarding the dataset, we determined that combining both image and text data is better than using one type of data to achieve a more accurate prediction from the relational model. Concerning the condition of two mixed languages (English and Korean), the method produces a satisfactory result. According to the relational model of the two products, we can design a recommendation system that suggests products that would be of interest to consumers.

Syntheses and Characteristics of Oligo[(4,4-disubstituted- 2,6-dithieno[3,2-b:2′,3′-d]silolene)-alt-(disubstituted silylene)]s

민용기,박영태 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

Co-oligomerizations of 2,6-dilithio-4,4-diisopropyl- or -diphenyl-dithieno[3,2-b:2′,3′-d]siloles, which were prepared in situ via n-butyllithium treatment of 2,6-dibromo-4,4-diisopropyl- or -diphenyl-dithieno[3,2-b:2′,3′-d]siloles (V or VI), with dichlorodiisopropylsilane or dichlorodiphenylsilane yielded the novel oligomers oligo[(4,4-disubstituted-2,6- dithieno[3,2-b:2′,3′-d]silolene)-alt-(disubstituted silylene)]s VII-X as blue-greenish viscous liquids. These oligomers were characterized using several spectroscopic methods, such as 1H and 13C nuclear magnetic resonance spectroscopy and Fourier transform infrared spectroscopy, photophysical properties, and thermal stabilities, along with density functional theory (DFT) calculations. The absorption spectra of VII, VIII, and X, in particular, revealed partial delocalization over the oligomer backbones in comparison with those of the monomers V and VI, which was consistent with the highest occupied molecular orbital-lowest unoccupied molecular orbital energy trends calculated using DFT. VII-X were generally stable up to 150°C, with the less than 4% loss of the original mass.

Attenuation of Translocator Protein 18 kDa (TSPO) Up-Regulation by Peroxisome Proliferator-Activated Receptor γ Ligand in Activated Microglia

Hyojin Cho,Hyun-Jung Shim,유성운 계명대학교 자연과학연구소 2014 Quantitative Bio-Science Vol.33 No.1

Translocator protein (18 kDa) (TSPO) is a five transmembrane domain protein localized primarily in the outer mitochondrial membrane. Recently, we reported that TSPO is a negative regulator of neuroinflammation in microglia. Peroxisome proliferator-activated receptor (PPAR) is a ligand-specific transcriptional factor belonging to the nuclear receptor superfamily and predicted as a putative TSPO transcriptional factor. A number of studies suggest that the activation of PPARhas anti-inflammatory effects. In this study, we observed that treatment of rosiglitazone, a PPARligand significantly decreased the NO production in lipopolysaccharide-stimulated BV2 microglia cell, indicating inhibition of microglial activation. The inhibitory effect of rosiglitazone extended to attenuated protein level of TSPO. TSPO up-regulation seems an adaptive anti-inflammatory response to overcome microglia activation, according to our previous report. Taken together, these results indicate that PPARactivation by rosiglitazone attenuates neuroinflammation and leads to reduced expression of TSPO in the BV2 microglial cells.

Sparse SVQR for Detecting Differently Expressed Genes

심주용 계명대학교 자연과학연구소 2014 Quantitative Bio-Science Vol.33 No.1

Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among random variables. In this paper we propose the sparse SVQR whose objective function is composed of a weighted quadratic loss function and l1 norm penalty term. We use the iterative reweighted least squares (IRWLS) procedure to solve the objective problem of the proposed SVQR. Furthermore, we introduce the generalized approximate cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of the sparse SVQR using IRWLS procedure.

Empirical Bayesian Markov Chain Model for Random Model Change

Zhi-Ming Luo,김태윤,김범준 계명대학교 자연과학연구소 2014 Quantitative Bio-Science Vol.33 No.1

In this short paper we consider long term binary prediction of stock market by using empirical Bayesian Markov chain model. Our empirical Bayesian MC model is designed to accommodate random change of MC over time. Surprisingly enough, it is shown that empirical Bayesian MC model is homogeneous and has limiting distribution though it accommodates random model change over time. Empirical works are given to illustrate usefulness of our results.

A Trading Strategy Using Divergence on Multiple Timeframes

안원빈,오경주 계명대학교 자연과학연구소 2015 Quantitative Bio-Science Vol.34 No.2

Studies have examined the development of technical analysis strategies due to increasing interest in trading system. Commonly, trading is carried out by many technical analysis rules. Moreover, most studies have used methods that modify indicators or optimize trading rules. Studies using the unit of the time data are rare because one would find it difficult to measure a sensitive time unit appropriately. The present study proposes a method of configuring a trading strategy by using multiple units at the same time. The method, based on the simple trading rules of moving average convergence divergence and Bollinger bands, is tested based on the KOSPI200 futures index.

Predicting Debt Default of P2P Loan Borrowers Using Self-Organizing Map

김승현,이동원,정봉주,오경주 계명대학교 자연과학연구소 2019 Quantitative Bio-Science Vol.38 No.1

P2P loans-a typical example of modern financial markets combining finance and technology-have been growing over time in terms of their size and speed. In Korea, the market size of P2P loans is not large, and cases of delinquency are relatively few. However, in the U.S., several studies have predicted loan overdue in the P2P loan market, which is a developed financial market. Many studies had previously predicted the possibility of delinquency in these P2P loans by building a single model through artificial intelligence methodologies. However, this study used a methodology based on artificial intelligence and the self-organizing map, which finds a cluster of data on similar customers, and confirms that its predictive power is greater than that of the delinquency prediction method relying on only artificial intelligence. This study aimed to conduct empirical research on borrowers’ past dues in 2015 by randomizing customer data from Lending Club.

A Review of Copula Methods for Measuring Uncertainty in Finance and Economics

Jong-Min Kim 계명대학교 자연과학연구소 2020 Quantitative Bio-Science Vol.39 No.2

This paper reviews copula methods used for economic and finance. Copula allows researchers to relax the traditional linear model assumptions so that researchers can specify the marginal distributions and look at the dependence structure linking the marginal distributions to form a joint distribution. In this review, we focus on the copula dynamic correlation coefficient, copula directional dependence and copula applications in economics and finance.