Article
?
AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button.
Tier 2
?
Original research — experimental, observational, or case-control study. Direct primary evidence.
Policy & Risk
Sign in to save
Microbe-Based Sensor for Long-Term Detection of Urine Glucose
Sensors2022
15 citations
?
Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Score: 45
?
0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Dunzhu Li
Luming Yang,
Dunzhu Li
Dunzhu Li
Yunhong Shi,
Dunzhu Li
Yunhong Shi,
Zeena Wang,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Dunzhu Li
Dunzhu Li
Dunzhu Li
Yifan Sun,
Yunhong Shi,
Dunzhu Li
Dunzhu Li
Yunhong Shi,
Dunzhu Li
Dunzhu Li
Dunzhu Li
Yunhong Shi,
Yunhong Shi,
Dunzhu Li
Luming Yang,
Dunzhu Li
Dunzhu Li
Dunzhu Li
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Luming Yang,
Luming Yang,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Yifan Sun,
Yunhong Shi,
Liwen Xiao,
Yunhong Shi,
Dunzhu Li
Liwen Xiao,
Luming Yang,
Dunzhu Li
Liwen Xiao,
Yunhong Shi,
Yunhong Shi,
Liwen Xiao,
Liwen Xiao,
Yunhong Shi,
Yifan Sun,
Yunhong Shi,
Yunhong Shi,
Yunhong Shi,
Zeena Wang,
Zeena Wang,
Luming Yang,
Luming Yang,
Liwen Xiao,
Liwen Xiao,
Luming Yang,
Daniel K. Kehoe,
Daniel K. Kehoe,
Luming Yang,
Yunhong Shi,
Daniel K. Kehoe,
Daniel K. Kehoe,
Daniel K. Kehoe,
Yunhong Shi,
Yunhong Shi,
Luming Yang,
Daniel K. Kehoe,
Yunhong Shi,
Zeena Wang,
Liwen Xiao,
Zeena Wang,
Luming Yang,
Luming Yang,
Luming Yang,
Luming Yang,
Luming Yang,
Daniel K. Kehoe,
Daniel K. Kehoe,
L. Romeral,
Yurii K. Gun’ko,
Daniel K. Kehoe,
Daniel K. Kehoe,
L. Romeral,
Liwen Xiao,
Fei Gao,
Liwen Xiao,
Yurii K. Gun’ko,
Luming Yang,
Luming Yang,
Dunzhu Li
Liwen Xiao,
Yurii K. Gun’ko,
Yurii K. Gun’ko,
David McCurtin,
Yunhong Shi,
Liwen Xiao,
Liwen Xiao,
Liwen Xiao,
Yunhong Shi,
Liwen Xiao,
David McCurtin,
Dunzhu Li
Liwen Xiao,
Yurii K. Gun’ko,
Liwen Xiao,
Liwen Xiao,
Liwen Xiao,
Michael E. G. Lyons,
Yunhong Shi,
Yunhong Shi,
Liwen Xiao,
Liwen Xiao,
Liwen Xiao,
Yunhong Shi,
Yunhong Shi,
Dunzhu Li
Summary
Researchers developed a microbial fuel cell-based biosensor for continuous urine glucose monitoring, achieving a detection range of 0.3-5 mM, a 100-second response time, and a sensor lifespan of up to five months. The device provided a low-cost, reusable alternative to conventional enzyme-based glucose sensors for diabetes management.
The development of a reusable and low-cost urine glucose sensor can benefit the screening and control of diabetes mellitus. This study focused on the feasibility of employing microbial fuel cells (MFC) as a selective glucose sensor for continuous monitoring of glucose levels in human urine. Using MFC technology, a novel cylinder sensor (CS) was developed. It had a quick response time (100 s), a large detection range (0.3-5 mM), and excellent accuracy. More importantly, the CS could last for up to 5 months. The selectivity of the CS was validated by both synthetic and actual diabetes-negative urine samples. It was found that the CS's selectivity could be significantly enhanced by adjusting the concentration of the culture's organic matter. The CS results were comparable to those of a commercial glucose meter (recovery ranged from 93.6% to 127.9%) when the diabetes-positive urine samples were tested. Due to the multiple advantages of high stability, low cost, and high sensitivity over urine test strips, the CS provides a novel and reliable approach for continuous monitoring of urine glucose, which will benefit diabetes assessment and control.