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  <channel rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/16193">
    <title>Repository Collection: null</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/16193</link>
    <description />
    <items>
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        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/58997" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/58695" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/57351" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/47862" />
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    <dc:date>2026-04-04T12:10:35Z</dc:date>
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  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/58997">
    <title>Surface Tension-Guided Drop-and-Spread Inkjet Printing for Additive Fabrication of CNT Field-Effect Transistor Biosensors</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/58997</link>
    <description>Title: Surface Tension-Guided Drop-and-Spread Inkjet Printing for Additive Fabrication of CNT Field-Effect Transistor Biosensors
Author(s): Park, Soohyun; Shin, Minhye; Kim, Eunui; Kang, Hongki; Lee, Yoonhee
Abstract: Carbon nanotube field-effect transistors (CNT FETs) are highly regarded in nanoelectronics for their superior electrical properties, yet their broader adoption in nanotechnology is hindered by challenges in scalable fabrication. These challenges are primarily related to controlling nanotube density and achieving consistent alignment at electrode junctions for large-scale production. Here, we present a novel in-place inkjet printing technique to construct CNT FETs, ensuring controlled numbers of connected CNTs. We print a series of pico-liter droplets of CNT ink onto prepatterned electrode arrays over a 4-in. silicon wafer, promoting additive device manufacturing without supplementary lithographic steps. Our technique leverages surface tension-driven flow, guiding droplet spread along electrodes, preventing unwanted CNT networks. This approach enhances manufacturing throughput and device yield and efficiently connects an individualized CNT array to electrodes with less than 10 tubes per device. Moreover, we demonstrate biosensing application by functionalizing devices with DNA aptamers, achieving serotonin detection at thresholds as low as 42 pM. This method establishes cost-efficient and simple micromanufacturing protocols essential for the mass production of CNT FET arrays, particularly beneficial for high-throughput bioassays.</description>
    <dc:date>2025-07-31T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/58695">
    <title>Deep Learning-Based Classification of NSCLC-Derived Extracellular Vesicles Using AFM Nanomechanical Signatures</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/58695</link>
    <description>Title: Deep Learning-Based Classification of NSCLC-Derived Extracellular Vesicles Using AFM Nanomechanical Signatures
Author(s): Park, Soohyun; Kim, Youngkyu; Kim, Jung-Hee; Kim, Haeyoung; Kim, Kwang-Youl; Kim, Eunjoo; Koo, Gyogwon; Lee, Yoonhee
Abstract: Nonsmall cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality, with liquid biopsy emerging as a promising tool for noninvasive diagnostics. Extracellular vesicles (EVs) serve as molecular messengers of the tumor microenvironment, yet precise characterization methods remain limited. Using atomic force microscopy (AFM), we analyzed EVs from NSCLC subtypes (A549, PC9, PC9/GR) and nontumorigenic bronchial epithelial cells (BEAS-2B), revealing that A549-derived EVs exhibited significantly higher stiffness, likely due to KRAS mutation-associated lipid alterations. EGFR mutant EVs (PC9, PC9/GR) showed overlapping nanomechanical properties, correlating with their shared genetic background. To enhance classification, we implemented a DenseNet-based deep learning model for AFM image analysis, integrating nanomechanical and morphological features. This approach significantly improved diagnostic performance, achieving an AUC of 0.92, and notably, EVs from the A549 (KRAS mutant) cell line were classified with 96% accuracy. This study provides the first demonstration of the nanomechanical classification of NSCLC-derived EVs, highlighting the potential of deep learning-enhanced AFM analysis as a powerful tool for advancing liquid biopsy and precision diagnostics. Addressing sample variability and validating performance across clinical samples will be key to enabling its clinical translation.</description>
    <dc:date>2025-06-30T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/57351">
    <title>In Silico Analysis of Binding Sites for a Novel ssDNA Aptamer Specific to Verrucarin A and Detection in Dust Extracts</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/57351</link>
    <description>Title: In Silico Analysis of Binding Sites for a Novel ssDNA Aptamer Specific to Verrucarin A and Detection in Dust Extracts
Author(s): Park, Junyoung; Lee, Yoonhee; Kim, Eunjoo; Choe, Jong Kwon
Abstract: An aptamer is a single-stranded oligonucleotide that serves as a chemical antibody with a high specificity and binding affinity that can recognize a wide range of molecules. Effective modification and truncation of aptamers can enhance their binding affinities to particular targets while also broadening their application for uses, such as biosensors. However, a conventional trial-and-error methodology hinders this process. Herein, we demonstrate an in silico method to elucidate the binding site of single-stranded DNA aptamer specific to verrucarin A, a mycotoxin produced by molds in indoor buildings that causes adverse effects in living organisms. The novel ssDNA aptamer exhibited a binding affinity of 29.5 nM, demonstrating a relatively strong affinity compared to those of previously reported typical aptamers for small molecules. Furthermore, the selected aptamer was highly specific toward verrucarin A among structurally related mycotoxins (i.e., verrucarol and zearalenone). The specific binding site of the aptamer predicted via molecular dynamics and molecular docking simulations was highly consistent with the results observed via truncation, single base mutation, and circular dichroism experiments. The fluorescence assay revealed limits of detection and quantification of 4.1 and 12 nM for the aptamer, respectively. Comparing our developed aptasensor with LC-MS/MS methodology revealed that it could detect verrucarin A levels in phosphate-buffered saline and dust extracts with robust precision and consistency. Our findings provide insight for future studies exploring interaction mechanisms with intended targets and practical sensing applications, such as point-of-care detection of verrucarin A. © 2024 American Chemical Society.</description>
    <dc:date>2024-09-30T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/47862">
    <title>Carbon-nanotube field-effect transistors for resolving single-molecule aptamer-ligand binding kinetics</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/47862</link>
    <description>Title: Carbon-nanotube field-effect transistors for resolving single-molecule aptamer-ligand binding kinetics
Author(s): Lee, Yoonhee; Buchheim, Jakob; Hellenkamp, Bjorn; Lynall, David; Yang, Kyungae; Young, Erik F.; Penkov, Boyan; Sia, Samuel; Stojanovic, Milan N.; Shepard, Kenneth L.
Abstract: Small molecules such as neurotransmitters are critical for biochemical functions in living systems. While conventional ultraviolet–visible spectroscopy and mass spectrometry lack portability and are unsuitable for time-resolved measurements in situ, techniques such as amperometry and traditional field-effect detection require a large ensemble of molecules to reach detectable signal levels. Here we demonstrate the potential of carbon-nanotube-based single-molecule field-effect transistors (smFETs), which can detect the charge on a single molecule, as a new platform for recognizing and assaying small molecules. smFETs are formed by the covalent attachment of a probe molecule, in our case a DNA aptamer, to a carbon nanotube. Conformation changes on binding are manifest as discrete changes in the nanotube electrical conductance. By monitoring the kinetics of conformational changes in a binding aptamer, we show that smFETs can detect and quantify serotonin at the single-molecule level, providing unique insights into the dynamics of the aptamer–ligand system. In particular, we show the involvement of G-quadruplex formation and the disruption of the native hairpin structure in the conformational changes of the serotonin–aptamer complex. The smFET is a label-free approach to analysing molecular interactions at the single-molecule level with high temporal resolution, providing additional insights into complex biological processes. © 2024, The Author(s), under exclusive licence to Springer Nature Limited.</description>
    <dc:date>2024-04-30T15:00:00Z</dc:date>
  </item>
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