• Bulletin of the Korean Chemical Society
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• v.27 no.5
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• pp.725-732
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• 2006

A rapid flotation methodology for zinc(II) separation and enrichment from human biofluids is established. At pH 6.0 and ambient temperature, using oleic acid (HOL) as a foaming reagent, zinc(II) was separated with phenanthraquinone monophenyl thiosemicarbazone (PPT) as a new flotation collector for Zn(II). The floated red colored 1 : 2 Zn(II)-PPT complex was measured spectrophotometrically at 526 nm with a molar absorptivity of $1.83 \;{\times}\; 10^5\; L$ mol $L ^{-1}\;cm ^{-1}$. Beer's law was obeyed over a concentration range 0.05-1.0 mg $L ^{-1}$ in the aqueous as well as in the scum layers. The proposed preconcentration flotation methodology was applied to determine Zn(II) in human biofluids. Application was, also, extended to determine Zn(II) in pharmaceutical samples and natural water samples spiked with known amounts of Zn(II) with a preconcentration factor of 100 and a detection limit of 10 ng m$L ^{-1}$. The method was verified by comparison of the spectrophotometric results with flame atomic absorption spectrometric (AAS) measurements. Moreover a postulation for the mechanism of flotation is proposed.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.1
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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.

• Korean Chemical Engineering Research
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• v.58 no.1
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• pp.106-112
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• 2020

Analyzing vitamin D levels is important for monitoring health conditions because vitamin D deficiency is associated with various diseases such as rickets, osteomalacia, cardiovascular disorders and some cancers. However, vitamin D concentration in the blood is very low with optimal level of 75 nmol/L, making quantitative analysis difficult. The objective of this study was to develop a highly sensitive analysis method for vitamin D using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-MS). 25-hydroxyvitamin D (25(OH)D), which has been used as an indicator of vitamin D metabolites in human biofluids was chemically derivatized using a secosteroid signal enhancing tag (SecoSET) with powerful dienophile and permanent positive charge. The SecoSET-derivatized 25(OH)D provided good linearity (R² > 0.99) and sensitivity (limit of quantitation: 11.3 fmol). Chemical derivatization of deuterated 25-hydroxyvitamin D₃ (d₆-25(OH)D3) with SecoSET enabled absolute quantitative analysis using MALDI-MS. The highly sensitive method could be successfully applied into monitoring of quantitative changes of bioactive vitamin D metabolites after treatment with ketoconazole to inhibit 1α-hydroxylase reaction related to vitamin D metabolism in human breast cancer cells. Taken together, we developed a MALDI-MS-based platform that could quantitatively analyze vitamin D metabolites from cell products, blood and other biofluids. This platform may be applied to monitor various diseases associated with vitamin D deficiency such as rickets, osteomalacia and breast cancer.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.55-61
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• 2022

There is a major interest in diagnostic technology for multiple cancers worldwide. In order to reduce the difficulty of cancer diagnosis, a liquid biopsy technology based on a microfluidic device using trace amounts of biofluids such as blood is being studied. And optical biosensing, which measures the concentration of analytes through fluorescence imaging using biofluids, requires various strategies to improve sensitivity, and specialists and equipment are needed to carry out these strategies. This leads to an increase in diagnostic and production costs, and it is necessary to develop a technology to solve this problem. In this paper, we design and propose a fluorescent multi-cancer diagnostic sensing platform structure that implements passive self-separation technology and molecular recognition activation functions by fluid mixing, only with the geometry and microfluidic phenomena of microchannels based on self-driven flow by capillary force. In order to check the parameters affecting the performance of the plasma separation part of the designed sensor, the hydrodynamic diameter of the channel and the viscosity of the fluid were set as variables to confirm the formation of plasma separation flow through simulation. And finally, we propose an optimal sensor platform structure.

• Toxicological Research
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• v.29 no.2
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• pp.81-86
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• 2013

Toxicoproteomics integrates the proteomic knowledge into toxicology by enabling protein quantification in biofluids and tissues, thus taking toxicological research to the next level. Post-translational modification (PTM) alters the three-dimensional (3D) structure of proteins by covalently binding small molecules to them and therefore represents a major protein function diversification mechanism. Because of the crucial roles PTM plays in biological systems, the identification of novel PTMs and study of the role of PTMs are gaining much attention in proteomics research. Of the 300 known PTMs, protein acylation, including lysine formylation, acetylation, propionylation, butyrylation, malonylation, succinylation, and crotonylation, regulates the crucial functions of many eukaryotic proteins involved in cellular metabolism, cell cycle, aging, growth, angiogenesis, and cancer. Here, I reviewed recent studies regarding novel types of lysine acylation, their biological functions, and their applicationsin toxicoproteomics research.

• 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 Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• YAKHAK HOEJI
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• v.49 no.1
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• pp.74-79
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• 2005

Metabonomic analysis has been recognized as a powerful approach for characterizing metabolic changes in biofluids due to toxicity, disease process or environmental influences. To investigate the possibility of relating metabolic changes with $^{1}H-NMR$ spectra, urine samples from Sprague-Dawley rats treated with various dietary restrictions or toxic substances (nicotine) were analysed using $^{1}H-NMR$ spectroscopy and pattern recognition techniques. Dietary restrictions-given to male rats were normal diet and high fat diet and fasting. The nicotine urine samples were collected from SD rats administered with nicotine (25 mg/kg) at the various time intervals. $^{1}H-NMR$ spectra of all urine samples were acquired at 400 MHz on a VARIAN spectrometer. To establish the presence of any intrinsic class-related patterns or clusters in each NMR data, methods of PCA (principal component analysis) and soft independent modeling of class analogy (SIMCA) analysis were used, and the results from these analyses were compared to each other. In all cases of dietary conditions and nicotine treatment, SIMCA analysis gave better results for the discrimination of NMR spectra of urine samples than PCA.

• Journal of the Korean institute of surface engineering
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• v.55 no.6
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• pp.342-352
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• 2022

Purine catabolite screening enables reliable diagnosis of certain diseases. In this regard, the development of a facile detection strategy with high sensitivity and selectivity is demanded for point-of-care applications. In this work, the simultaneous detection of uric acid (UA), xanthine (XA), and hypoxanthine (HX) was carried out as model purine catabolites by surface-enhanced Raman Spectroscopy (SERS). The detection assay was conducted by employing high-aspect ratio Au nanopillar substrates coupled with in-situ Au electrodeposition on the substrates. The additional modification of the Au nanopillar substrates via electrodeposition was found to be an effective method to encapsulate molecules in solution into nanogaps of growing Au films that increase metal-molecule contact and improve substrate's sensitivity and selectivity. In complex solutions, the approach facilitated ternary identification of UA, XA, and HX down to concentration limits of 4.33 𝜇M, 0.71 𝜇M, and 0.22 𝜇M, respectively, which are comparable to their existing levels in normal human physiology. These results demonstrate that the proposed platform is reliable for practical point-of-care analysis of biofluids where solution matrix effects greatly reduce selectivity and sensitivity for rapid on-site disease diagnosis.

• Biomedical Science Letters
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• v.27 no.4
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• pp.208-215
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• 2021

The purpose of this study was to explain the pathology of Alzheimer's disease (AD) and to investigate the correlation between AD and microRNA. AD is the most common type of dementia, accounting for about 80% of all types of dementia, causing dysfunction in various daily activities such as memory loss, cognitive impairment, and behavioral impairment. The typical pathology of AD is explained by the accumulation of beta-amyloid peptide plaques and neurofibrillary tangles containing hyperphosphorylated tau protein. On the other hand, microRNA is small non-coding RNA 22~23 nucleotides in length that binds to the 3' untranslated region of messenger RNA to inhibit gene expression. Many reports explain that microRNAs found in circulating biofluids are abundant in the central nervous system, are involved in the pathogenic mechanism of AD, and act as important factors for early diagnosis and therapeutic agents of AD. Therefore, this paper aims to clarify the correlation between AD and microRNA. In this review, the basic mechanism of miRNAs is described, and the regulation of miRNAs in the pathological processes of AD are highlighted. Furthermore, we suggest that miRNA-based system in development of therapeutic and diagnostic agents of AD can be a promising tool.