Szu-Jui Chen

Dr. Szu-Jui Chen

National Cheng Kung University, Tainan City, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2021 in Talanta
Verified
Journal Article
Closed access
CLCarl Jay D. Laurenciano
Carl Jay D. Laurenciano
CTChin-Chung Tseng
Chin-Chung Tseng
SCSzu-Jui Chen
Szu-Jui Chen
SLSong-Yu Lu
Song-Yu Lu
LTLemmuel L. Tayo
Lemmuel L. Tayo
LFLung-Ming Fu
Lung-Ming Fu

7 July 2022 in Biosensors
Verified
Journal Article
Open access
PDF file
SCSzu-Jui Chen
Szu-Jui Chen
CTChin-Chung Tseng
Chin-Chung Tseng
HHHuang Kuan Hsun
Huang Kuan Hsun
YCYu Chi Chang
Yu Chi Chang
LFLung-Ming Fu
Lung-Ming Fu
A novel assay platform consisting of a microfluidic sliding double-track paper-based chip and a hand-held Raspberry Pi detection system is proposed for determining the albumin-to-creatine ratio (ACR) in human urine. It is a clinically important parameter and can be used for the early detection of related diseases, such as renal insufficiency. In the proposed method, the sliding layer of the microchip is applied and the sample diffuses through two parallel filtration channels to the reaction/detection areas of the microchip to complete the detection reaction, which is a simple method well suited for self-diagnosis of ACR index in human urine. The RGB (red, green, and blue) value intensity signals of the reaction complexes in these two reaction zones are analyzed by a Raspberry Pi computer to derive the ACR value (ALB and CRE concentrations). It is shown that the G + B value intensity signal is linearly related to the ALB and CRE concentrations with the correlation coefficients of R2 = 0.9919 and R2 = 0.9923, respectively. It is additionally shown that the ALB and CRE concentration results determined using the proposed method for 23 urine samples were collected from real suffering chronic kidney disease (CKD) patients are in fine agreement with those acquired operating a traditional high-reliability macroscale method. Overall, for point-of-care (POC) CKD diagnosis and monitoring in clinical applications, the results prove that the proposed method offers a convenient, real time, reliable, and low-spending solution for POC CKD diagnosis.

30 May 2024 in Biosensors
Verified
Journal Article
Open access
PDF file
SCSzu-Jui Chen
Szu-Jui Chen
SLSong-yu Lu
Song-yu Lu
CTChin-Chung Tseng
Chin-Chung Tseng
HHHuang Kuan Hsun
Huang Kuan Hsun
TCTO-LIN Chen
TO-LIN Chen
LFLung-Ming Fu
Lung-Ming Fu
A microfluidic immuno-biosensor detection system consisting of a microfluidic spectrum chip and a micro-spectrometer detection device is presented for the rapid point-of-care (POC) detection and quantification of high-sensitivity C-reactive protein (hs-CRP) in urine. The detection process utilizes a highly specific enzyme-linked immunosorbent assay (ELISA) method, in which capture antibodies and detection antibodies are pre-deposited on the substrate of the microchip and used to form an immune complex with the target antigen. Horseradish peroxidase (HRP) is added as a marker enzyme, followed by a colorimetric reaction using 3,3′,5,5′-tetramethylbenzidine (TMB). The absorbance values (a.u.) of the colorimetric reaction compounds are measured using a micro-spectrometer device and used to measure the corresponding hs-CRP concentration according to the pre-established calibration curve. It is shown that the hs-CRP concentration can be determined within 50 min. In addition, the system achieves recovery rates of 93.8–106.2% in blind water samples and 94.5–104.6% in artificial urine. The results showed that the CRP detection results of 41 urine samples from patients with chronic kidney disease (CKD) were highly consistent with the conventional homogeneous particle-enhanced turbidimetric immunoassay (PETIA) method’s detection results (R2 = 0.9910). The experimental results showed its applicability in the detection of CRP in both urine and serum. Overall, the results indicate that the current microfluidic ELISA detection system provides an accurate and reliable method for monitoring the hs-CRP concentration in point-of-care applications.