• Molecules and Cells
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• v.46 no.2
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• pp.106-119
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• 2023

With the increased number of single-cell RNA sequencing (scRNA-seq) datasets in public repositories, integrative analysis of multiple scRNA-seq datasets has become commonplace. Batch effects among different datasets are inevitable because of differences in cell isolation and handling protocols, library preparation technology, and sequencing platforms. To remove these batch effects for effective integration of multiple scRNA-seq datasets, a number of methodologies have been developed based on diverse concepts and approaches. These methods have proven useful for examining whether cellular features, such as cell subpopulations and marker genes, identified from a certain dataset, are consistently present, or whether their condition-dependent variations, such as increases in cell subpopulations in particular disease-related conditions, are consistently observed in different datasets generated under similar or distinct conditions. In this review, we summarize the concepts and approaches of the integration methods and their pros and cons as has been reported in previous literature.

• BMB Reports
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• v.53 no.8
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• pp.393-399
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• 2020

Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease.

• Transactions of the Korean hydrogen and new energy society
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• v.24 no.6
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• pp.480-486
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• 2013

In this study, tubular SOFC unit cell with advanced anode current collector was fabricated to improve the cell performance. First, we prepared two types of single cells having the same manufacture processes such as the same electrolyte, electrode coating condition and sintering processes. And then to compare the developed single cell performance with conventional cells, we changed the anode current collecting methods. From the impedance analysis and I-V curve analysis, the cell performance of advanced cell is much higher than that of conventional cell.

• Environmental Mutagens and Carcinogens
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• v.17 no.2
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• pp.71-77
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• 1997

The single cell gel electrophoressis(SCGE) assay, also known as the comet assay, is a rapid, simple, visual and sensitive technique for measuring and analysing DNA breakage in mammalian cells. The SCGE or comet assay is a promising test for the detection of DNA damage and repair in individnal cells. It has widespread potential applications in DNA damage and repair studies, genotoxicity testing and biomonitoring. In this microgel electrophoresis technique, cells are embedded in agarose gel on microscope slides, iysed and electrophoresed under alkaline conditions. Cells with increased DNA damage display increased migration of DNA from the nucleus towards the anode. The length of DNA migration indicates the amount of DNA breakage in the cell. The comet assay is also capable of identifying apoptotic cells which contain highly fragmented DNA. Here we review the development of the SCGE assay, existing protocols for the detection and analysis of comets, the relevant underlying principles determining the behaviour of DNA and the potential applications of the technique.

• BMB Reports
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• v.57 no.5
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• pp.232-237
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• 2024

This study investigated how adipose tissue-derived mesenchymal stem cells (AT-MSCs) respond to chondrogenic induction using droplet-based single-cell RNA sequencing (scRNA-seq). We analyzed 37,219 high-quality transcripts from control cells and cells induced for 1 week (1W) and 2 weeks (2W). Four distinct cell clusters (0-3), undetectable by bulk analysis, exhibited varying proportions. Cluster 1 dominated in control and 1W cells, whereas clusters (3, 2, and 0) exclusively dominated in control, 1W, and 2W cells, respectively. Furthermore, heterogeneous chondrogenic markers expression within clusters emerged. Gene ontology (GO) enrichment analysis of differentially expressed genes unveiled cluster-specific variations in key biological processes (BP): (1) Cluster 1 exhibited up-regulation of GO-BP terms related to ribosome biogenesis and translational control, crucial for maintaining stem cell properties and homeostasis; (2) Additionally, cluster 1 showed up-regulation of GO-BP terms associated with mitochondrial oxidative metabolism; (3) Cluster 3 displayed up-regulation of GO-BP terms related to cell proliferation; (4) Clusters 0 and 2 demonstrated similar up-regulation of GO-BP terms linked to collagen fibril organization and supramolecular fiber organization. However, only cluster 0 showed a significant decrease in GO-BP terms related to ribosome production, implying a potential correlation between ribosome regulation and the differentiation stages of AT-MSCs. Overall, our findings highlight heterogeneous cell clusters with varying balances between proliferation and differentiation before, and after, chondrogenic stimulation. This provides enhanced insights into the single-cell dynamics of AT-MSCs during chondrogenic differentiation.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.143-148
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• 1996

Detailed analyses have been presentd for a basic single-electron-logic-cell consisting of two single-electron-transistors (SETs) in series. The interconnection between two SETs has been treated as a coulomb island and the joint probability density function of all three coulomb islands (two from the SETs and one form the interconnection) has been exactly calculated. The average number of electrons in each coulomb island and the steady-state ouptut voltage have been calculated and analyzed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.4
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• pp.314-321
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• 2006

There have been great demands for higher density SRAM in all area of SRAM applications, such as mobile, network, cache, and embedded applications. Therefore, aggressive shrinkage of 6 T Full CMOS SRAM had been continued as the technology advances. However, conventional 6 T Full CMOS SRAM has a basic limitation in the cell size because it needs 6 transistors on a silicon substrate compared to 1 transistor in a DRAM cell. The typical cell area of 6 T Full CMOS SRAM is $70{\sim}90\;F^2$, which is too large compared to $8{\sim}9\;F^2$ of DRAM cell. With 80 nm design rule using 193 nm ArF lithography, the maximum density is 72 Mbits at the most. Therefore, pseudo SRAM or 1 T SRAM, whose memory cell is the same as DRAM cell, is being adopted for the solution of the high density SRAM applications more than 64 M bits. However, the refresh time limits not only the maximum operation temperature but also nearly all critical electrical characteristics of the products such as stand_by current and random access time. In order to overcome both the size penalty of the conventional 6 T Full CMOS SRAM cell and the poor characteristics of the TFT load cell, we have developed S3 cell. The Load pMOS and the Pass nMOS on ILD have nearly single crystal silicon channel according to the TEM and electron diffraction pattern analysis. In this study, we present $S^3$ SRAM cell technology with 100 nm design rule in further detail, including the process integration and the basic characteristics of stacked single crystal silicon TFT.

• Biomedical Science Letters
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• v.18 no.1
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• pp.71-75
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• 2012

The PLA2G4A catalyzes the hydrolysis of membrane phospholipids to release arachidonic acid, which is metabolized into lipid-based cellular hormones that regulate inflammatory response. The circulating blood cell numbers can be influenced by stress, infection or inflammation. Quantitative blood cell count traits analysis for the 19 SNPs in the PLA2G4A gene in the Korean Association Resource (KARE) cohort (7551 subjects) was performed. The only one SNP (rs10752979) in the all blood cell count was satisfied with the Bonferroni corrected P-value (<0.00263). Furthermore, 6 of the 19 SNPs in the PLA2G4A gene showed a weak or moderate association with blood cell count (P-values: 0.0048~0.042), suggesting the clue of an association between the PLA2G4A gene and blood cell count, especially white blood cell count. This study may provide insight into the genetic basis of blood cell count related with reaction of infection.

• Korean Journal of Microbiology
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• v.53 no.2
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• pp.71-78
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• 2017

Raman microspectroscopy is a promising tool for microbial analysis at single cell level since it can rapidly measure the cell materials including lipids, nucleic acids, and proteins by measuring the inelastic scattering of a molecule irradiated by monochromatic lights. Using Raman spectra provides high specificity and sensitivity in classification of bacteria at the strain level. In addition, a Raman approach coupled with stabled isotope such as $^{13}C$ and $^2H$ is able to detect and quantify general metabolic activity at single cell level. After bacterial detection process by Raman microspectroscopy, interested unculturable cell sorting and single cell genomics can be accomplished by combination with optical tweezer and microfluidic devices. In this review, the characteristics and applications of Raman microspectroscopy were reviewed and summarized in order to provide a better understanding of microbial analysis using Raman spectroscopy.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.572-575
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• 2008

Flow-field design has much influence over the performance of proton exchange membrane fuel cell (PEMFC) because it affects the pressure magnitude and distribution of the reactant gases. To obtain the pressure magnitude and distribution of reactant gases in four kinds of flow-field designs without additional measurement equipment, computational fluid dynamics (CFD) analysis was performed. After the CFD analysis, the performance values of PEMFC according to the flow-field configurations were measured via a single cell test. As expected, the pressure differences due to different flow-field configurations were related to the PEMFC performance because the actual performance results showed the same tendency as the results of the CFD analysis. A large pressure drop resulted in high PEMFC performance. So, the single serpentine configuration gave the highest performance. On the other hand, the parallel flow-field configuration gave the lowest performance because the pressure difference between inlet and outlet was the lowest.