2012 ©
             Publication
Journal Publication
Research Title Acute Kidney Injury Detection using Real Human Urine NGAL Biomarker Sensor based on 3D Graphene 
Date of Distribution 22 January 2023 
Conference
     Title of the Conference The 2022 Biomedical Engineering International Conference (BMEiCON-2022) 
     Organiser IEEE EMB Thailand Chapter, IEEJ, IFMBE, PSU และ ThaiBME.org 
     Conference Place Lipe 
     Province/State Songkhla 
     Conference Date 10 November 2022 
     To 13 November 2022 
Proceeding Paper
     Volume 2022 
     Issue 10.1109/BMEiCON56653.2022.10012085 
     Page 1-4 
     Editors/edition/publisher IEEE 
     Abstract Acute kidney injury (AKI) is not a specified symptom in the early stages. Frequency of AKI occurrence is highly correlated to Chronic Kidney Disease (CKD). Therefore, development of non-invasive, ultra-sensitive, and highly accurate sensing platform is crucial for early AKI diagnosis. Serum creatinine (SCr) level usually takes 24-72 hours to response to the incident of AKI. Meanwhile, urine Neutrophil Gelatinase- Associated Lipocalin (NGAL) takes only 2 hours to response after the AKI occurrence. In this work, we investigated the use of microporous graphene and dipole-dipole enhancement between graphene/nickel layers to enhance electrode sensitivity for urine NGAL level determination. Selectivity was assured using enzymatic electrochemistry. Once NGAL level was measured, a doctor can diagnose AKI under additional information on patient’s conditions. The result is promising since the detection range was 0.110 to 93.9 ng/ml and the correlation coefficient is 0.8235. The detection covered AKI primary diagnostic cutoff level at 87 ng/ml in urine. The electrochemical immunosensor was able to determine NGAL in Urine with results compared to those provided by the standard ELISA method. This work is a part of development of handheld NGAL determination strip in human urine samples and prepared portable NGAL sensing devices. Despite our investigation's limitation, the acquired data indicates that non-invasive acute kidney injury detection using actual human urine with graphene foam/nickel-based electrochemical sensor should be further explored as an auxiliary diagnostic tool for AKI. 
Author
645040043-2 Miss NETNAPA SITTIHAKOTE [Main Author]
Engineering Master's Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Full paper 
Type of Presentation Oral 
Part of thesis true 
Presentation awarding false 
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