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Hyun-June Jang

Publications and source records attributed to Hyun-June Jang.

3 recordsLinked to original sources

Interfacial Potential Transduction for Diagnostics

A major barrier to decentralized, near-patient diagnostics is the lack of a signal transduction modality that is both analytically precise and accessible at the point of care. Optical readouts remain instrument-dependent and difficult to miniaturize, while compact electrochemical readouts are prone to matrix-derived signal distortion, limiting their biomarker coverage in real clinical settings. Here, we define interfacial potential transduction as a standardized electrical modality for portable, clinical-grade diagnostics across diverse assay formats. A mechanistic framework identifying key sample matrix parameters within the interfacial potentials transduction system enables control of biofluid-derived interference, and is demonstrated in a widely accessible lateral flow immunoassay format through quantitative detection of estradiol, progesterone, and luteinizing hormone in human plasma with high correlation (r2 > 0.97) to clinical analyzers. Broader applicability across representative diagnostic sectors is further demonstrated through exceptional performance including glucose quantification for biochemical analysis with limit of detection (LOD) of 0.92 ug/dL, HIV p24 capsid protein under an immunomagnetic separation workflow (LOD = 44.8 fg/mL), and hepatitis B virus detection within 5 min via loop-mediated isothermal amplification for molecular diagnostics. Together, these results establish interfacial potentials transduction as a unified diagnostic paradigm for near-patient deployment beyond optical and electrochemical approaches.

q-bio.BM

Radical-mediated Electrical Enzyme Assay For At-home Clinical Test

To meet the growing demand for accurate, rapid, and cost-effective at-home clinical testing, we developed a radical-mediated enzyme assay (REEA) integrated with a paper fluidic system and electrically read by a handheld field-effect transistor (FET) device. The REEA utilizes horseradish peroxidase (HRP) to catalyze the conversion of aromatic substrates into radical forms, producing protons detected by an ion-sensitive FET for biomarker quantification. Through screening 14 phenolic compounds, halogenated phenols emerged as optimal substrates for the REEA. Encased in an affordable cartridge ($0.55 per test), the system achieved a detection limit of 146 fg/mL for estradiol (E2), with a coefficient of variation (CV) below 9.2% in E2-spiked samples and an r2 of 0.963 across a measuring range of 19 to 4,551 pg/mL in clinical plasma samples, providing results in under 10 minutes. This adaptable system not only promises to offer a fast and reliable platform, but also holds significant potential for expansion to a wide array of biomarkers, paving the way for broader clinical and home-based applications.

q-bio.QM

Deep Learning-based Kinetic Analysis in Paper-based Analytical Cartridges Integrated with Field-effect Transistors

This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity challenge observed in paper analytical devices, enabling electrical measurements with kinetic data. The paper-based cartridge eliminates the need for surface chemistry required in FET sensors, ensuring economical operation (cost < $0.15/test). The DL analysis mitigates chronic challenges of FET biosensors such as sample matrix interference, by leveraging kinetic data from target-specific bioreactions. In our proof-of-concept demonstration, our DL-based analyses showcased a coefficient of variation of < 6.46% and a decent concentration measurement correlation with an r2 value of > 0.976 for cholesterol testing when blindly compared to results obtained from a CLIA-certified clinical laboratory. These integrated technologies can create a new generation of FET-based biosensors, potentially transforming point-of-care diagnostics and at-home testing through enhanced accessibility, ease-of-use, and accuracy.

q-bio.QM