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Hye Jin Lee

Researcher at Kyungpook National University

Publications -  400
Citations -  10009

Hye Jin Lee is an academic researcher from Kyungpook National University. The author has contributed to research in topics: Medicine & Surface plasmon resonance. The author has an hindex of 49, co-authored 304 publications receiving 8451 citations. Previous affiliations of Hye Jin Lee include University of California, Irvine & University of British Columbia.

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Understanding the effect of co-reactants on ketonization of carboxylic acids in the aqueous-phase pyrolysis oil of wood

TL;DR: In this paper, the influence of co-feed reactants on the performance of ketonization of carboxylic acid over the selected CeZrOx catalyst was investigated.
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Quaternary Ammonium-Bearing Perfluorinated Polymers for Anion Exchange Membrane Applications.

TL;DR: Both perfluorinated polymer-based membranes exhibited distinct hydrophilic-hydrophobic phase-separated morphologies, resulting in high ion conductivity despite their low ion exchange capacities and limited water uptake properties.
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Fluorescent paper strip immunoassay with carbon nanodots@silica for determination of human serum amyloid A1.

TL;DR: A fluorescent paper strip immunoassay in conjunction with carbon nanodots@silica (CND@SiO2) was developed for the quantitative measurements of human serum amyloid A1 (hSAA1) in serum at clinically significant concentrations for lung cancer diagnosis as mentioned in this paper.
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A short PEG linker alters the in vivo pharmacokinetics of trastuzumab to yield high-contrast immuno-PET images

TL;DR: In contrast to the prevailing belief that PEGylation prolongs blood retention time, this article observed that a PEG-ylated antibody with a short PEG8 linker cleared much faster from the blood while maintaining tumor uptake compared to its non-PEGylated counterpart, and breast tumors were clearly visualized with a very high tumor-to-background ratio as early as 24 h after injection in immuno-positron emission tomography (PET) imaging.
Posted ContentDOI

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

TL;DR: It is demonstrated that a novel Kyn pathway regulator derived using deep learning technology can activate T cell immunity and potentiate immune checkpoint blockade by overcoming an immunosuppressive TME.