• 한국자기공명학회논문지
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• 제3권2호
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• pp.140-148
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• 1999

Using 1H magnetic resonance spectroscopy (MRS), we quantitatively evaluated correlation representing linear relationship between the metabolite peak area ratios associated with poor shimming conditions. The inadequate shimming due to linear shim offsets directly affected overall MR spectral quality as well as peak area for each metabolite. Three major peaks such as N-acetylaspartate (NAA), creatine (Cr,) choline (Cho) were used as a reference for data analysis. Despite considerable variations of metabolite peak area, a significant correlation between the metabolite peak area ratios relative to Cr was established while the correlation between the peak area ratios relative to Cho and NAA was not. The present study suggested that metabolite peak area ratios based on the metabolite of Cr could be an acceptable quantification method even under the poor shimming in clinical MRS examination.

• 한국환경보건학회지
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• 제28권1호
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• pp.67-77
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• 2002

This study was aimed to determine the urinary metabolite of IBP, one of the organophosphorus pesticides, as the biomarkers of exposure. Urine samples were collected for 24 hours in metabolic cages after oral administration and dermal application of IBP to rats. Identification of the derivatized urinary metabolite was determined by GC/MS and excretion time courses of the urinary metabolite was analyzed by GC/FPD. Urinary metabolite o IBP, diisopropyl phosphorothioate, was detected in rats urine both after oral administration and dermal application of IBP. Parent compound was not detected in the experiment. In GC/MS, the mass spectral confirmation for diisopropyl phosphorothioate ion was identified at m/z 254. Diisopropyl phosphorothioate was excreted within 48 hours and 72 hours after oral administration and dermal application of IBP, respectively. In this study, the same urinary metabolite of IBP was detected both in oral and dermal exposure. Generally, excretion of the urinary metabolite after oral administration was faster than after dermal application. It is suggested that urinary diisopropyl phosphorothioate could be used as the biomarkers of exposure to IBP.

• 분석과학
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• 제13권3호
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• pp.385-393
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• 2000

뇨시료 중 amineptine의 (dihydro-10, 11-dibenzo[a, d] cycloheptenyl-5-amino-7-heptanoic acid) metabolites를 분석하기 위한 최적조건을 찾기 위하여 pH 변화에 따른 추출률과 세가지의 유도체화시약에 대한 반응성을 조사해본 결과 pH는 9.5, 유도체화시약은 carboxylic acid group에 MSTFA로 반응 시켰을 경우 좋은 결과를 나타내었다. GC/MS를 이용하여 amineptine을 복용한 사람의 뇨를 분석한 결과 amineptine과 그 대사물질인 dihydro-10, 11-dibenzo[a, d] cycloheptenyl-5-amino-5-pentanoic acid ($C_5$-metabolite)와 $C_5$-metabolite의 lactamized product인 ${\delta}$-lactam을 확인하였다. Amineptine과 그 metabolite들을 GC/MS-SIM mode로 분석하기 위한 monitoring ion들은 m/z 192를 공통 이온으로 선정하였으며, 각각의 분자이온을 선정하였다. Amineptine의 excretion study 결과, amineptine, ${\delta}$-lactam 및 $C_5$-metabolite는 4시간이내에 70-90%가 배설되었고 20시간 이내에 거의 배설이 완결되었다.

• 대한의용생체공학회:의공학회지
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• 제31권5호
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• pp.412-416
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• 2010

In this study, we measured the chemical shift change of metabolite peaks in the brain-metabolite phantom according to the temperature variation using nuclear magnetic resonance(NMR). The temperature range in NMR system was controled from 25 to 80 (5 step) by internal temperature controller. Temperature coefficients of each metabolite peaks were also calculated from the measured chemical shift depending on the temperature. The chemical shift changes depending on temperature were validated by linear regression method for each metabolite peaks. The temperature coefficients of $_{tot}Cr$, Cho, Cr, NAA, and Lac were 0.0086, 0.0088, 0.0091, 0.0089, and 0.0088ppm/$^{\circ}C$, respectively. This study shows that chemical shift change of brain metabolite and temperature variation have linear relationship each other. This also makes authors believe that brain temperature measurement is possible using MR spectroscopic imaging technique.

• Asian-Australasian Journal of Animal Sciences
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• 제15권5호
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• pp.637-642
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• 2002

Thirty Holstein calves were used to determine effects of age, environment and sex on blood metabolite concentrations during 1 to 90 d of age. Calves were weaned at 75 d of age. Environmental effects are grouped by the difference in month at birth and site of feeding. Blood samples were obtained every 2 or 3 d. The mean metabolite concentration every 3 d was used for the statistical analysis. Dairy bodyweight gain was not affected by environmental group and sex effect. Concentrations of plasma glucose, nonesterified fatty acids (NEFA), triglyceride, total cholesterol and total ketone changed with growth. These developmental changes in metabolite levels would be caused by ruminal maturation with increment of grain intake. Levels of plasma urea nitrogen, glucose, NEFA, triglyceride and total cholesterol drastically changed during a few weeks after birth, indicating that the physiological state in calves greatly changed during that time. Effects of the environmental group and sex were significant in almost all metabolites. Temperature influenced plasma metabolite concentrations. The plasma metabolite concentrations were affected more intensely by heat stress in the infant period than in the neonatal period.

• 한국자기공명학회논문지
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• 제22권1호
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• pp.10-17
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• 2018

Metabolite identification and quantification are one of the foremost important issues in metabolomics. In NMR based metabolomics, mainly one-dimensional proton NMR spectra of biofluids, such as urine and serum are measured. However, it is not always easy to identify and quantify metabolites in one-dimensional proton NMR spectra. This article introduces useful public metabolite databases, metabolic profiling software, and articles.

• 한국식물생명공학회:학술대회논문집
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• 한국식물생명공학회 2004년도 생명공학 실용화를 위한 비젼
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• pp.209-209
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• 2004

• Journal of Microbiology and Biotechnology
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• 제19권4호
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• pp.368-371
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• 2009

In the course of screening for the melanogenesis inhibitors, aspochalasin I was isolated from solid-state culture of Aspergillus sp. Fb020460. Its structure was determined by spectroscopic analysis including mass spectroscopy and NMR analysis. Aspochalasin I potently inhibited melanogenesis in Mel-Ab cells with an $IC_{50}$ value of $22.4{\mu}M$ without cytotoxicity.

• Journal of Microbiology and Biotechnology
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• 제17권10호
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• pp.1717-1720
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• 2007

In the course of screening for nitric oxide inhibitors in activated microglial BV-2 cells, cyclo(dehydrohistidyl-L-tryptophyl) was isolated from solid-state fermentation cultures of an unidentified fungal strain, Fb956. Its structure was determined by spectroscopic methods including 2D NMR and chiral TLC analyses. Cyclo(dehydrohistidyl-L-tryptophyl) was found to have an inhibitory activity on nitric oxide production with an $IC_{50}$ of $6.5\;{\mu}M$ in activated BV-2 cells. The structure determination and biological activity of cyclo(dehydrohistidyl-L-tryptophyl) was reported for the first time in this study.

• Mycobiology
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• 제36권2호
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• pp.121-133
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• 2008

Aspergillus niger isolated from Allium sativum was used at large scale fermentation (150 mg flavone/200ml medium) to obtain suitable amounts of the products, efficient for identification. Then spectral analysis (UV, IR, $^1H$-NMR, $^{13}C$-NMR) and mass spectrometry were performed for the two products, which contributed to the identification process. The metabolite (1) was identified as 2'-hydroxydihydrochalcone, and the metabolite (2) was identified as 2'-hydroxyphenylmethylketone, which were more active than flavone itself. Antioxidant activities of the two isolated metabolites were tested compared with ascorbic acid. Antioxidant activity of metabolite (1) was recorded 64.58% which represented 79% of the antioxidant activity of ascorbic acid, and metabolite (2) was recorded 54.16% (67% of ascorbic acid activity). However, the antioxidant activity of flavone was recorded 37.50% which represented 46% of ascorbic acid activity. The transformed products of flavone have anti-microbial activity against Pseudomonas aeruginosa, Aspergillus flavus and Candida albicans, with MIC was recorded $250{\mu}g/ml$ for metabolite (2) against all three organism and 500, 300, and $300{\mu}g/ml$ for metabolite (1) against tested microorganisms (P. aeruginosa, Escherichia coli, Bacillus subtilis, and Klebsiella pneumonia, Fusarium moniliforme, A. flavus, Saccharomyces cerviceae, Kluveromyces lactis and C. albicans) at this order.