Journal article
Amperometric sarcosine biosensor with strong anti-interference capabilities based on mesoporous organic-inorganic hybrid materials
Biosensors & bioelectronics, Vol.141, p.111431
09/15/2019
PMID: 31212197
Abstract
Amperometric enzyme biosensors are some of the simplest and cheapest types of medical devices used in the rapid detection of biomarkers that have been developed in the past fifty years. When the concentrations of biomarkers are at micromoles per liter, such as for sarcosine, which was recently discovered as a biomarker for prostate cancer, the response signal of the interferences is huge, and the biosensor is hard to satisfy the requirements of practical applications. In this manuscript, we describe a strategy for synthesizing a surface electronegative organic-inorganic hybrid mesoporous material, which could reduce the interference signal much better than Nafion and Chitosan. We verify that the surface potential of the carrier nanomaterial plays an important role in excluding anionic interferences. We also prepare a sensitive (16.35 mu A mM(-1)), low LOD (0.13 mu M) and wide linear range (1-70 mu M) amperometric sarcosine biosensor with excellent anti-interference properties. This mesoporous material provides a bio-composite platform for the development of simple amperometric biosensors for detecting micromoles per liter of analytes in serum or urine.
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Details
- Title
- Amperometric sarcosine biosensor with strong anti-interference capabilities based on mesoporous organic-inorganic hybrid materials
- Creators
- Qia Wang - Shenzhen UniversityYuting Zhao - Shenzhen UniversityQingui Yang - Shenzhen UniversityDan Du - Washington State UniversityHaipeng Yang - Shenzhen UniversityYuehe Lin - Washington State University
- Publication Details
- Biosensors & bioelectronics, Vol.141, p.111431
- Academic Unit
- School of Mechanical and Materials Engineering
- Publisher
- Elsevier
- Number of pages
- 6
- Grant note
- JCYJ20180305124343508 / Shenzhen Science and Technology Innovation Commission PIDFPZR2019027 / Postgraduate Innovation Development Fund Project of Shenzhen University
- Identifiers
- 99901227847601842
- Language
- English
- Resource Type
- Journal article