Yeonho Choi 교수

Lung cancer has a high mortality rate, but an early diagnosis can contribute to a favorable prognosis. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for early-stage diagnosis. Exosomes, nanosized extracellular vesicles found in blood, have been proposed as promising biomarkers for liquid biopsy. Here, we demonstrate an accurate diagnosis of early-stage lung cancer, using deep learning-based surface-enhanced Raman spectroscopy (SERS) of the

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize sign

Exosomes, which are nanovesicles secreted by cells, are promising biomarkers for cancer diagnosis and prognosis, based on their specific surface protein compositions. Here, we demonstrate the correlation of nonsmall cell lung cancer (NSCLC) cell-derived exosomes and potential protein markers by unique Raman scattering profiles and principal component analysis (PCA) for cancer diagnosis. On the basis of surface enhanced Raman scattering (SERS) signals of exosomes from normal and NSCLC cells, we e

Rapid diagnosis and quarantine of influenza virus mutant-infected people is critical to contain the fatal viral infection spread because effective antiviral drugs are normally not available. Conventional methods, however, cannot be used for the diagnosis because these methods need predefined labels, likely also unavailable for just emerging viruses. Here, we propose label-free identification of cells infected with different influenza viruses based on surface-enhanced Raman spectroscopy (SERS) an

The importance of the photothermal effect in surface enhanced Raman scattering (SERS) measurements is addressed. Strong temperature gradient (≈106 K m−1) induced by photothermal effect can force molecules to move. Finally, redistributed molecules can result in a nonuniform SERS intensity. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the author

In vitro diagnosis using biomarkers for major depressive disorder (MDD) can offer considerable advantages in overcoming the lack of objective tests for depression and treating more patients. Plasma exosomes can be novel biomarkers for MDD based on their ability to pass through the blood-brain barrier and offer brain-related information. Here, we demonstrate a novel and precise MDD diagnosis using deep learning analysis and surface-enhanced Raman spectroscopy (SERS) of plasma exosomes. Our system

Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-rela

In spite of severe side effects, chemotherapy is widely used as a major anticancer treatment in non-small cell lung cancer (NSCLC). In order to enhance the therapeutic properties and reduce side effects, enormous efforts have been devoted to direct anticancer agents specifically to tumor tissues by the use of nanoparticles, or cancer cell marker attached drugs. However, cell-specific chemotherapy is still in its infancy and is not applicable to all types of cancers due to the complexity of the c

Protein quantification techniques such as immunoassays have been improved considerably, but they have several limitations, including time-consuming procedures, low sensitivity, and extrinsic detection. Because direct surface-enhanced Raman spectroscopy (SERS) can detect intrinsic signals of proteins, it can be used as an effective detection method. However, owing to the complexity and reliability of SERS signals, SERS is rarely adopted for quantification without a purified target protein. This s

Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutated proteins in body fluids. To increase the diagnostic accuracy, we analyzed plasma exosomes using nanoplasmonic spectra and deep learning. Exosomes, a promising biomarker, are abundant in plasma and stably carry intact proteins originating from mothe

Selective chemical control of multiple reactions is incredibly important for the fabrication of sophisticated nanostructures for functional applications. A representative example is the synthesis of plasmonic nanomaterial-silver chloride (AgCl) conjugates, where metal ions should be selectively reduced into metallic nanostructures for plasmon-enhanced catalytic activity, while the reducible AgCl nanomaterials remain intact despite the presence of a chemical reductant. In addition to the selectiv

Polarization of light carries important information regarding the materials included by biological samples. A Jones matrix is a general tool for quantifying the degree of polarization, however, its measurement has been limited mostly to connective tissues with strong polarization response due to the lack of measurement sensitivity. Here, we demonstrate polarization phase microscopy capable of measuring a Jones matrix of a living eukaryotic cell. Our strategy combines synthetic aperture imaging w

Proactively predicting antidepressant treatment response before medication failures is crucial, as it reduces unsuccessful attempts and facilitates the development of personalized therapeutic strategies, ultimately enhancing treatment efficacy. The current decision-making process, which heavily depends on subjective indicators, underscores the need for an objective, indicator-based approach. This study developed a method for detecting depression and predicting treatment response through deep lea