• Biomolecules & Therapeutics
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• v.26 no.1
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• pp.81-92
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• 2018

It is widely accepted that altered metabolism contributes to cancer growth and has been described as a hallmark of cancer. Our view and understanding of cancer metabolism has expanded at a rapid pace, however, there remains a need to study metabolic dependencies of human cancer in vivo. Recent studies have sought to utilize multi-modality imaging (MMI) techniques in order to build a more detailed and comprehensive understanding of cancer metabolism. MMI combines several in vivo techniques that can provide complementary information related to cancer metabolism. We describe several non-invasive imaging techniques that provide both anatomical and functional information related to tumor metabolism. These imaging modalities include: positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS) that uses hyperpolarized probes and optical imaging utilizing bioluminescence and quantification of light emitted. We describe how these imaging modalities can be combined with mass spectrometry and quantitative immunochemistry to obtain more complete picture of cancer metabolism. In vivo studies of tumor metabolism are emerging in the field and represent an important component to our understanding of how metabolism shapes and defines cancer initiation, progression and response to treatment. In this review we describe in vivo based studies of cancer metabolism that have taken advantage of MMI in both pre-clinical and clinical studies. MMI promises to advance our understanding of cancer metabolism in both basic research and clinical settings with the ultimate goal of improving detection, diagnosis and treatment of cancer patients.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.207-210
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• 2013

We report the construction of a MALDI imaging mass spectrometer equipped with a specially designed laser focusing lens, a compact aspherical singlet lens, that obtains a high-lateral imaging resolution in the microprobe mode. The lens is specially designed to focus the ionization laser (${\lambda}$ = 355 nm) down to a $1{\mu}m$ diameter with a long working distance of 34.5 mm. With the lens being perpendicular to the sample surface and sharing the optical axis with the ion path, the imaging mass spectrometer achieved an imaging resolution of as good as $5{\mu}m$ along with a high detection sensitivity of 100 fmol for peptides. The mass resolution was about 900 (m/${\Delta}m$) in the linear TOF mode. The high-resolution capability of this instrument will provide a new research opportunity for label-free imaging studies of various samples including tissues and biochips, even for the study at a single cell level in the future.

• Applied Science and Convergence Technology
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• v.24 no.6
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• pp.203-214
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• 2015

We have been developing a new label-free nanobio imaging platform using non-linear optics such as Coherent Anti-Stokes Raman Spectroscopy (CARS) and ion beam techniques based on sputtering and scattering such as Secondary Ion Mass Spectrometry (SIMS) and Medium Energy Ion Scattering Spectroscopy (MEIS), which have been widely used for atomic and molecular level analysis of semiconductors and nanomaterials. To apply techniques developed for semiconductors and nanomaterials for biomedical applications, the convergence of nano-analysis and biology were tried. Our activities on label-free nanobio imaging during the last decade are summarized in this review about non-linear optical 3D imaging, ellipsometric interface imaging, SIMS imaging, and TOF-MEIS nano analysis for cardiovascular tissues, collagen thin films, peptides on microarray, nanoparticles, and cell adhesion studies and finally the present snapshot of nanobio imaging and the future prospect are described.

• Mass Spectrometry Letters
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• v.2 no.3
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• pp.61-64
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• 2011

Matrix Assisted Laser Desorption/Ionization-Time-of-Flight mass spectrometry (MALDI-TOF-MS) is the most widely used MS technique for glycan analysis. However, the poor point-to-point and sample-to-sample reproducibility becomes a limit in glycan biomarker research. A prespotted MALDI plate which overcomes the large crystal formation of 2,5-dihydroxybenzoic acid (DHB) has been developed and applied for glycan analysis. A homogeneous matrix coated surface without a crystal structure was formed on a hydrophilic/ hydrophobic patterned surface using a piezoelectric device. The reproducible MALDI-TOF-MS data have been presented using MALDI imaging of beer glycan as well as serum glycan eluted from 10% and 20% ACN elution fractions. The glycan profile from the serum glycan by MALDI-TOF-MS with a DHB prespotted plate was highly conserved for 10 different spectra and the coefficient of variations of significant ion peaks of MALDI data varies from 3.59 to 19.95.

• Molecules and Cells
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• v.38 no.7
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• pp.624-629
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• 2015

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.105.1-105.1
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• 2016

Many of the complex materials developed today derive their unique properties from the presence of multiple phases or from local variations in elemental concentration. Simply performing analysis of the bulk materials is not sufficient to achieve a true understanding of their physical and chemical natures. Secondary ion mass spectrometer (SIMS) has met with a great deal of success in material characterization. The basis of SIMS is the use of a focused ion beam to erode sample atoms from the selected region. The atoms undergo a charge exchange with their local environment, resulting in their conversion to positive and negative secondary ions. The mass spectrometric analysis of these secondary ions is a robust method capable of identifying elemental distribution from hydrogen to uranium with detectability of the parts per million (ppm) or parts per billion (ppb) in atomic range. Nano secondary ion mass spectrometer (Nano SIMS, Cameca Nano-SIMS 50) equipped with the reactive ion such as a cesium gun and duoplasmatron gun has a spatial resolution of 50 nm which is much smaller than other SIMS. Therefore, Nano SIMS is a very valuable tool to map the spatial distribution of elements on the surface of various materials In this talk, the surface imaging applications of Nano SIMS in KBSI will be presented.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.815-819
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• 2013

Micropatterns of streptavidin and human epidermal carcinoma A431 cells were successfully imaged, as received and without any labeling, using cluster $Au_3{^+}$ ion beam-based time-of-flight secondary ion mass spectrometry (TOF-SIMS) together with a principal component analysis (PCA). Three different analysis ion beams ($Ga^+$, $Au^+$ and $Au_3{^+}$) were compared to obtain label-free TOF-SIMS chemical images of micropatterns of streptavidin, which were subsequently used for generating cell patterns. The image of the total positive ions obtained by the $Au_3{^+}$ primary ion beam corresponded to the actual image of micropatterns of streptavidin, whereas the total positive-ion images by $Ga^+$ or $Au^+$ primary ion beams did not. A PCA of the TOF-SIMS spectra was initially performed to identify characteristic secondary ions of streptavidin. Chemical images of each characteristic ion were reconstructed from the raw data and used in the second PCA run, which resulted in a contrasted - and corrected - image of the micropatterns of streptavidin by the $Ga^+$ and $Au^+$ ion beams. The findings herein suggest that using cluster-ion analysis beams and multivariate data analysis for TOF-SIMS chemical imaging would be an effectual method for producing label-free chemical images of micropatterns of biomolecules, including proteins and cells.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Applied Chemistry for Engineering
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• v.28 no.3
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• pp.263-271
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• 2017

The application of mass spectrometry to polymer science has rapidly increased since the development of MALDI-TOF MS. This review summarizes current polymer analysis methods using MALDI-TOF MS, which has been extensively applied to analyze the average molecular weight of biopolymers and synthetic polymers. Polymer sequences have also been analyzed to reveal the structures and composition of monomers. In addition, the analysis of unknown end-groups and the determination of polymer concentrations are very important applications. Hyphenated techniques using MALDI-tandem MS have been used for the analysis of fragmentation patterns and end-groups, and also the combination of SEC and MALDI-TOF MS techniques is recommended for the analysis of complex polymers. Moreover, MALDI-TOF MS has been utilized for the observation of polymer degradation. Ion mobility MS, TOF-SIMS, and MALDI-TOF-imaging are also emerging technologies for polymer characterization because of their ability to automatically fractionate and localize polymer samples. The determination of polymer characteristics and their relation to the material properties is one of the most important demands for polymer scientists; the development of software and instrument for higher molecular mass range (> 100 kD) will increase the applications of MALDI-TOF MS for polymer scientists.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.