• YAKHAK HOEJI
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• v.57 no.6
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• pp.412-419
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• 2013

Drug discovery and development processes are time consuming and costly endeavors. It has been reported that on average it takes 10 to 15 years and costs more than $ 1billion to bring a molecule from discovery to market. Compounds fail for various reasons but one of the significant reasons that accounts for failures in clinical trials is poor prediction/understanding of pharmacokinetics and drug metabolism in human. In an effort to improve the number of compounds that exhibit optimal absorption, distribution, metabolism, elimination (ADME), and pharmacokinetic properties in human, drug metabolism, pharmacokinetic scientists have been continually developing new technologies and compound screening strategies. Over the last few years, accelerator mass spectrometry (AMS) and its applications to preclinical/clinical pharmacokinetics and ADME studies have significantly increased, particularly for new chemical/biological entities that are difficult to support with conventional radiolabel studies. In this review, the application of AMS for micro-dosing, micro-tracer absolute bioavailability, mass balance and metabolite profiling studies will be discussed.

• Journal of the Korean Magnetic Resonance Society
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• v.16 no.1
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• pp.46-66
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• 2012

Metabolomic studies using human urine have shown that human metabolism is altered by a variety of environmental, cultural, and physiological factors. Comprehensive information about normal human metabolite profiles is necessary for accurate clinical diagnosis of disease and for disease prevention and treatment. In this study, metabolite correlation analyses, using $^1H$ nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistics, were performed on human urine to compare metabolic differences based on gender and/or obesity in healthy human subjects. First, we applied partial least squares discriminant analysis to the NMR spectral data set to verify the data's ability to discriminate by gender and obesity. Then, the differences in metabolite-metabolite correlation between male and female, and between normal and high body mass index (obese) subjects were investigated through pairwise correlations. Creatine and several metabolites, including isoleucine, trans-aconitate, and trimethylamine N-oxide (TMAO), exhibited different quantitative relationships depending on gender. Dimethylamine had a different correlation with glycine and TMAO, based on gender. The correlation of TMAO with amino acids was considerably lower in obese, compared to normal, subjects. We expect that the results will shed light on the metabolic pathways of healthy humans and will assist in the accurate diagnosis of human disease.

• Journal of Microbiology and Biotechnology
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• v.28 no.12
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• pp.1971-1981
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• 2018

In this study, we investigated the altered enzymatic activities and metabolite profiles of koji fermented using varying permutations of Aspergillus oryzae and/or Bacillus amyloliquefaciens. Notably, the protease and ${\beta}$-glucosidase activities were manifold increased in co-inoculated (CO) koji samples (co-inoculation of A. oryzae and B. amyloliquefaciens). Furthermore, gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling indicates that levels of amino acids, organic acids, sugars, sugar alcohols, fatty acids, nucleosides, and vitamins were distinctly higher in CO, SA (sequential inoculation of A. oryzae, followed by B. amyloliquefaciens), and SB (sequential inoculation of B. amyloliquefaciens, followed by A. oryzae). The multivariate principal component analysis (PCA) plot based on GC-MS datasets indicated a clustered pattern for MA and MB (koji samples inoculated either with A. oryzae or B. amyloliquefaciens) across PC2 (20.0%). In contrast, the CO, SA, and SB metabolite profiles displayed segregated patterns across PLS1 (22.2%) and PLS2 (21.1%) in the partial least-square discriminant analysis (PLS-DA) model. Intriguingly, the observed disparity in the levels of primary metabolites was engendered largely by higher relative levels of sugars and sugar alcohols in MA, SA, and CO koji samples, which was commensurate with the relative amylase activities in respective samples. Collectively, the present study emphasizes the utility of integrated biochemical and metabolomic approaches for achieving the optimal permutation of fermentative inocula for industrial koji preparation.

• Bulletin of the Korean Chemical Society
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• v.34 no.5
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• pp.1467-1472
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• 2013

Metabolomics is a field that studies systematic dynamics and secretion of metabolites from cells to understand biological pathways based on metabolite changes. The metabolic profiling of intact human colorectal tissues was performed using high-resolution magic angle spinning (HR-MAS) NMR spectroscopy, which was unnecessary to extract metabolites from tissues. We used two different groups of samples, which were defined as normal and cancer, from 9 patients with colorectal cancer and investigated the samples in NMR experiments with a water suppression pulse sequence. We applied target profiling and multivariative statistical analysis to the analyzed 1D NMR spectra to identify the metabolites and discriminate between normal and cancer tissues. Cancer tissue showed higher levels of arginine, betaine, glutamate, lysine, taurine and lower levels of glutamine, hypoxanthine, isoleucine, lactate, methionine, pyruvate, tyrosine relative to normal tissue. In the OPLS-DA (orthogonal partial least square discriminant analysis), the score plot showed good separation between the normal and cancer groups. These results suggest that metabolic profiling of colorectal cancer could provide new biomarkers.

• Journal of Microbiology and Biotechnology
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• v.22 no.11
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• pp.1523-1531
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• 2012

The metabolite profile of meju during fermentation was analyzed using mass spectrometry techniques, including GC-MS and LC-MS, and the bacterial diversity was characterized. The relative proportions of bacterial strains indicated that lactic acid bacteria, such as Enterococcus faecium and Leuconostoc lactis, were the dominant species. In partial least-squares discriminate analysis (PLS-DA), the componential changes, which depended on fermentation, proceeded gradually in both the GC-MS and LC-MS data sets. During fermentation, lactic acid, amino acids, monosaccharides, sugar alcohols, and isoflavonoid aglycones (daidzein and genistein) increased, whereas citric acid, glucosides, and disaccharides decreased. MS-based metabolite profiling and bacterial diversity characterization of meju demonstrated the changes in metabolites according to the fermentation period and provided a better understanding of the correlation between metabolites and bacterial diversity.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.3
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• pp.96-101
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• 2017

Metabolomics is one of latest '-omics', which is to analyze metabolome in cells, tissues and biofluids and to study metabolisms. It has become increasingly popular since 1990. The first goal of metabolomics is to analyze metabolites in a technical aspect. The major two analytical platforms in metabolomics are NMR spectroscopy and mass spectrometry (MS). MS is superior to NMR for detecting many more metabolites. That is one of the most important factors in metabolomics. However, NMR also has several advantages over MS. In this review, I firstly introduced metabolomics by comparing NMR-based metabolomics and MS-based metabolomics. Second, I explored technical issues on sample preparation and NMR experiments for metabolite identification and quantification.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2010.05a
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• pp.5-5
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• 2010

Selection of specific medicinal sources as well as bioactive compounds is important for the preparation of medicine and related products with good quality. It is necessary to pay close attention for choosing correct medicinal sources, particularly in case of medicinal plants, because of their diversity, which can affect the quality and efficacy of medicine. Discrimination of plants based on morphological or genetic characteristics has been used as a conventional classification method of pharmaceutical sources so far; however, more need demands more general methods for accurate quality assessment of medicinal plants. In this study, ultra performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) technique applied to this metabolic profiling is a powerful tool due to its higher sensitivity, resolution, and speed compared to conventional HPLC technique. The metabolite profiling of several medicinal plants including Panax ginseng was carried out using UPLC/Q-TOF MS and total metabolites were then subsequently applied to various statistical tools to compare the patterns. The developed metabolomics tool with UPLC/Q-TOF MS successfully identified and classified the samples tested according to their origins.

• Mass Spectrometry Letters
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• v.11 no.1
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• pp.1-5
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• 2020

In this study, some of the recently reported data processing strategies were evaluated and modified based on their capabilities and a brief workflow for data mining was redefined for Q-TOF LC-MS based untargeted metabolomics. Commercial pooled human plasma samples were used for this purpose. An ultrafiltration procedure was applied on sample preparation. Sample set was analyzed through Q-TOF LC/MS. A C18 column (Agilent Zorbax 1.8 µM, 50 × 2.1 mm) was used for chromatographic separation. Raw chromatograms were processed using XCMS - R programming language edition and Isotopologue Parameter Optimization (IPO) was used to optimize XCMS parameters. The raw XCMS table was processed using MS Excel to find reliable and reproducible peaks. Totally 1650 reliable and reproducible potential metabolite peaks were found based on the data processing procedures given in this paper. The redefined dataset was upload into MetaboAnalyst platform and the identified metabolites were matched with 86 metabolic pathways. Thus, two list were obtained and presented in this study as supplement files. The first list is to present the retention times and m/z values of detected metabolite peaks. The second list is the metabolic pathways related with the identified metabolites. The briefly described data processing strategies and dataset presented in this study could be beneficial for the researchers working on untargeted metabolomics for processing their data and validating their results.

• Journal of the Korean Magnetic Resonance Society
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• v.15 no.1
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• pp.54-68
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• 2011

$^1H$ nuclear magnetic resonance (NMR) spectroscopy of biological samples has been proven to be an effective and nondestructive approach to probe drug toxicity within an organism. In this study, ketoprofen toxicity was investigated using $^1H$-NMR spectroscopy coupled with multivariate statistical analysis. Histopathologic test of ketoprofen-induced acute gastrointestinal damage in rats demonstrated a significant dose-dependent effect. Furthermore, principal component analysis (PCA) derived from $^1H$-NMR spectra of urinary samples showed clear separation between the vehicle-treated control and ketoprofen-treated groups. Moreover, PCA derived from endogenous metabolite concentrations through targeted profiling revealed a dose-dependent metabolic shift between the vehicle-treated control, low-dose ketoprofen-treated (10 mg/kg body weight), and high-dose ketoprofen-treated (50 mg/kg) groups coinciding with their gastric damage scores after ketoprofen administration. The resultant metabolic profiles demonstrated that the ketoprofen-induced gastric damage exhibited energy metabolism perturbations that increased urinary levels of citrate, cis-aconitate, succinate, and phosphocreatine. In addition, ketoprofen administration induced an enhancement of xenobiotic activity in fatty oxidation, which caused increase levels of N-isovalerylglycine, adipate, phenylacetylglycine, dimethylamine, betaine, hippurate, 3-indoxylsulfate, N,N-dimethylglycine, trimethyl-N-oxide, and glycine. These findings demonstrate that $^1H$-NMR-based urinary metabolic profiling can be used for noninvasive and rapid way to diagnose adverse drug effects and is suitable for explaining the possible biological pathways perturbed by nonsteroidal anti-inflammatory drug toxicity.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.419-424
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• 2014

Metabolite profiling of blueberry (cultivar "Spartan") was performed by extraction using different solvents, methanol and ethyl acetate, through metabolomic analysis using LC-MS/MS. Unsupervised classification method (PCA) and supervised prediction model (OPLS-DA) provided good categorization of metabolites according to the extraction solvents. Metabolites of the anthocyanin family, including delphinidin hexoside, delphinidin, 5-O-feruloylquinic acid, malvidin hexoside, malvidin-3-arabinoside, petunidin-3-arabinoside, and petunidin hexoside, were mainly detected in methanol fractions, whereas those of the flavonoid family, including chlorogenic acid, chlorogenic acid dimer, 6,8-di-C-arabinopyranosyl-luteolin, and luteolin were successfully prepared in the ethyl acetate fraction. Thus, metabolomic analysis of blueberry extracts allows for the simple profiling of whole and distinctive metabolites for future applications.