• Journal of the Korean Chemical Society
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• v.45 no.5
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• pp.422-428
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• 2001

Retention relative times(RRTs) of PAH molecules and their derivatives in gas chromatography are trained and predicted in testing sets using a multiple linear regression(MLR) and an artificial neural network(ANN). The main descriptors of PAHs and their derivatives in QSRR are the square root of molecular weight(sqmw), molecular connectivity($^1{\chi}_v$), molecular dipole moment(D) and length-to-breadth ratios(L/B). The results of MLR shows that a heavy molecule has a propensity for long retention time. L/B closely related with slot model is a good descriptor in MLR. On the other hand, ANN which is not effected by the linear dependencies among the descriptors were exclusively based on molecular weight and molecular dipole moment. The variances which shows the accuracy of prediction for retention times in testing sets are 1.860, 0.206 for MLR and ANN, respectively. It was shown that ANN can exceed the MLR in prediction accuracy.

• Journal of the Korean Chemical Society
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• v.44 no.2
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• pp.102-108
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• 2000

Relative retention times (RRTs) of RAH molecules in HPLC are trained and predicted intesting sets using a multiple linear regression (NLR) and an artificial neural network (ANN). The maindescriptors in QSRR are molecular connectivity ($^1X_v,\;^2X_v$), the length-to-breadth ratios (L/B), and molecular dipole moment(D). L/B which is related with slot model is a good descripter in ANN, but isn't in MLR. Varainces which show the accuracy of prediction times in testing sets are 0.0099, 0.0114 for ANN and MLR, respectively. It was shown that ANN can exceed the MLR in prediction accuracy.

• The Korean Journal of Food And Nutrition
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• v.12 no.6
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• pp.582-587
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• 1999

감자절편을 고농도용액에 침지하여 탈수시킨 결과 침지용액을 구성하는 용질의 분자량에 따라 탈수형태가 다르게 나타났다. 저분자 용액인 NaCl, PEG 400 용액에 침지한 경우 조직의 뒤틀림현상(cytorrhysis) 은 나타나지 않고 부피의 감소와 수분의 탈수현상이 나타난 반면 고분자 용액인 PEG 4000, PEG 6000용액에 침지한 경우 cytorrhysis 현상을 동반한 부피의 감소와 탈수현상이 나타났다. 초기 탈수속도는 저분자 용액에 침지시 더 빨랐으나 최종 탈수량은 고분자 용액에 침지시 더 컸다 고장성 용액에 감자절편을 침지시켜 탈수되는 기작이 두가지 압력(삼투압 분자압착력)에 의해 진행된다고 가정하고 모델을 제안하여 감정한 결과 제안된 모델은 고분자 용액에 침지시의 탈수현항을 설명하는데 적합하였다. 모델에서 구해진 압력인자(ΔP)와 농도인자(a)는 온도(T)와 농도(C) 의 함수로 표현되며 계수의 탄력성 검정결과 농도에 대한 의존성이 더 큰 것으로 나타났다.

• Reproductive and Developmental Biology
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• v.31 no.1
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• pp.15-20
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• 2007

To search of a new porcine pheromonal odorant for biostimulation control system technologies to offer a potentially useful and practical way to improve reproductive efficiency in livestock species, the two dimensional quantitative structure-activity relationship (QSAR) models between physicochemical parameters as descriptors of 2-cyclohexyloxytetrahydrofurane (A), 2-phenoxytetrahydrofurane (B) analogues and binding affinity constant ($p[Od.]_{50}$) for porcine odorant-binding protein (pOBP) as receptor of pig pheromones were derived and disscused. The statistical quality of the optimized 2D-QSAR model is good ($r^{2}=0.964$) and accounts for 96.4% of the variance in the binding affinity constants. It was found that the binding affinity constants were dependent upon the optimal value, $(SL)_{opt.}=1.418$ of substituent lipole (SL) in molecules. Therefore, the SL constant was very important factor for binding affinity.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.154-160
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• 2008

We investigated molecular polarity by using theoretical means and comparing empirical solvent polarity. Our approach employed electrostatic potentials at the molecular surface calculated by density functional methods. A number of molecular descriptors related to molecular polarities were computed from molecular surface electrostatic potentials. Among computed molecular descriptors, the most positive electrostatic potential provided the best correlation with the empirical solvent polarities. A regression equation was developed in order to predict molecular polarities of molecules whose experimental solvent polarities were unknown. The new regression equations were utilized in estimating solvent polarities of cubane derivatives which are considered important precusors of high-energy density meterials.

• Journal of Life Science
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• v.22 no.10
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• pp.1428-1433
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• 2012

Longevity is an exciting but difficult subject to study because it is determined by complex processes that require the coordinated action of several genetic factors as well as physiological and environmental influences. Genetic approaches have been applied to animal models to identify the molecular mechanism responsible for longevity. Several experimental model organisms obtained over the last decades suggest that the complete deletion of a single gene by gene targeting has proven to be an invaluable tool for the discovery of the mechanisms underlying longevity. The first discovery of long-lived mutants came from Caenorhabditis elegans research, which identified the insulin/IGF-1 pathway as responsible for longevity in this worm. IGF-1 is a multifunctional polypeptide that has sequence similarity to insulin and is involved in normal growth and development of cells. Several factors in the IGF-1 system have since been studied by gene targeting in the control of longevity in lower species, including nematode and fruit fly. In addition, significant progress has been made using mice models to extend the lifespan by targeted mutations that interfere with growth hormone/IGF-1 and IGF-1 signaling cascades. A recent finding that IGF-1 is involved in aging in mice was achieved by using liver-specific knockout mutant mice, and this clearly demonstrated that the IGF-1 signal pathway can extend the lifespan in both invertebrates and vertebrate models. Although the underlying molecular mechanisms for the control of longevity are not fully understood, it is widely accepted that reduced IGF-1 signaling plays an important role in the control of aging and longevity. Several genes involved in the IGF-1 signaling system are reviewed in relation to longevity in genetically modified mice models.

• Journal of Life Science
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• v.34 no.2
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• pp.128-137
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• 2024

This review discusses the pivotal role of vascular endothelial growth factors (VEGF) in angiogenesis and lymphangiogenesis, vital processes influencing vascular permeability, endothelial cell recruitment, and the maintenance of tumor-associated blood and lymphatic vessels. VEGF exerts its effects through tyrosine-kinase receptors, VEGFR-1, VEGFR-2, and VEGFR-3. This VEGF-VEGFR system is central not only to cancer but also to diseases arising from abnormal blood vessel and lymphatic vessel formation. In the context of cancer, VEGF and its receptors are essential for the development of tumor-associated vessels, making them attractive targets for therapeutic intervention. Various approaches, such as anti-VEGF antibodies, receptor antagonists, and VEGF receptor function inhibitors, are being explored to interfere with tumor growth. However, the clinical efficacy of anti-angiogenic agents remains uncertain and necessitates further refinement. The article also highlights the physiological role of VEGFs, emphasizing their involvement in endothelial cell functions, survival, and vascular permeability. The identification of five distinct VEGFs in humans (VEGF-A, VEGF-B, VEGF-C, VEGF-D, and PLGF) is discussed, along with the classification of VEGFRs as typical receptor tyrosine kinases with distinct signaling systems. The family includes VEGFR-1 and VEGFR-2, crucial in tumor biology and angiogenesis, and VEGFR-3, specifically involved in lymphangiogenesis. Overall, this review has provided a comprehensive overview of VEGF and VEGFR, detailing their roles in various diseases, including cancer. This is expected to further facilitate the utilization of VEGF and VEGFR as therapeutic targets.

• Journal of Korean Biological Nursing Science
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• v.7 no.1
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• pp.29-46
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• 2005

Purpose ; 본 연구는 X-염색체와 관련된 장애 중에서 가장 흔하고 심한 Duchenne Muscular Dystrophy(DMD)의 세포유전학 및 분자유전학적 특성을 설명하기 위해서 DMD에 영향을 받고 있는 두 가계의 13명을 대상으로 가계도 분석과 염색체 분석 및 DNA 분석을 하였다. Method ; DNA분석은 DNA probe을 이용한 Southern blotting method로써 RFLPs와 DMD유전자 부위의 exon소실 유무를 조사하여 아래와 같은 결과를 얻었다. Conclusion ; A 염색체 분석 : 말초혈액과 양수를 표본으로 High-Resolution GTG염색에서 A가계와 B가계의 염색체 분석에서 12명의 염색체는 정상 X-염색체였으나 B가계의 I-2(DMD여성)에서 46, x,-x,+t(2:x)(q 21.1 : p21.2)로 나타난다. B. DNA분석3 : 1) RFLPs의 분석 J66,XJ-1.1,754-11로써 B가계의 RELPs(Restriction Fragment Length Polymorphisms)에서 J66/Pst I은 1.7hb(E), 1.6kb(e)을 보여 주었고 XJ-1.1/Taq I은 3.6kb(F), 3.0kb(f), 754-11/EoR I은 4.2kb(G), 2.0kb(g)의 대립인자를 나타내었다. 이상의 결과를 바탕으로 영향을 받고 있는 남자 (II-2)의 haplotype는 보인자인 어머니의 한쪽 인자를 받았으며 어머니와 딸은 보인자이고 임산부의 태아는 남아였고 태아의 인자들은 그의 할아버지로부터 물려받아 DMD에 영향을 받지 않은 것으로 진단되었다. 2) DMD 유전자의 exon 소실에 대한 분석 cDNA probe 8과 cDNA probe 2b-3으로써 소실에 대한 진단은 영향을 받은 남자(II-2)는 cDNA probe 8에서 12, 7.3, 6.6, 4.2kb에 소실이 있고 cDNA 2b-3은 1.7kb에 소실에 나타났다.

• Journal of the Korean Chemical Society
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• v.42 no.6
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• pp.646-651
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• 1998

The molecular structure of sulfur compounds and the retention relationship are studied by gas chromatography. Analyzed sulfur compounds are, hydrogen sulfide, sulfur dioxide, carbon disulfide, ethyl mercaptan, dimethyl sulfide, iso-propyl mercaptan, normal propyl mercaptan, ethyl methyl sulfide, tert-butyl mercaptan, tetrahydrothiophene, thiophene, and 2-chlorothiophene. Multiple linear regression explains the retention relationship of molecular descriptors. In GC the temperature program is 30$^{\circ}C$ held for 10.5 min, and then increased to 150$^{\circ}C$ at a rate 15$^{\circ}C$/min. Predicted equation for relative retention time (RRT) using SAS program is as follows; $RRT=0.121bp+14.39dp-8.94dp^2+0.0741sqmw-35.78\; (N=8,\; R^2=0.989, \;Variance=0.175,\;F=66.21)$. RRTs are function of boiling point, the square root of molecular weight, molecular dipole moment, and boiling point effects mostly on RRT. The RRT is maximized at the molecular dipole moment of 0.805D, when using nonpolar columns. The planar and highly symmetric compounds are eluted slowly. The square, of correlation coefficient $(R^2)$ using SAS program, is 0.989, and the variance is 0.175 in training sets. For three sulfur compounds, the variance between observed RRTs and predicted RRTs is 0.432 in testing sets.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.23-30
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• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.