Abstract
Background: Alzheimer’s disease (AD) is the most common form of dementia. The process of AD can begin 20 years before any symptom of cognitive loss. Thus, the development of systems for early diagnosis and prevention is very important. The mechanism of AD is still under debate. Nevertheless, higher levels of glycated albumin in cerebrospinal fluid and plasma are observed in AD patients. Therefore, glycated albumin could be a biomarker of AD development.
Methods: Electrochemical biosensor for direct determination of glycated albumin was based on thiol derivative of pentetic acid (DTPA) complex with Cu(II) created on gold electrode surface. His-tagged domains of Receptors for Advanced Glycation End Products (RAGE) were applied as analytical active element for glycated albumin recognition. The binding of glycated albumin by His6- RAGE domains was monitored using Osteryoung square - wave voltammetry. Results: Electrodes modified with His6 - RAGE VC1 natural domain generated decrease of Cu(II) redox currents in the presence of glycated albumin. Human albumin, Aβ 1-40 and S100B protein caused negligible influence on biosensors responses towards glycated albumin. The detection limits were: 2.3 pM, 1.1 pM, 2.9 pM and 3.1 pM in the presence of: buffer, buffer + albumin, buffer + S100B, buffer + Aβ1-40 , respectively. Conclusion: The presented electrochemical biosensor was successfully applied for the determination of glycated albumin. Considering analytical parameters such as good selectivity and sensitivity in pM range, biosensor could be recommended as an analytical tool for medical samples analysis.Keywords: Alzheimer’s disease, pentetic acid-Cu(II) complex, glycated albumin, His-tagged RAGE domains, electrochemical biosensor, redox active monolayer , potential AD biomarkers.
Current Alzheimer Research
Title:Electrochemical Biosensor for the Detection of Glycated Albumin
Volume: 14 Issue: 3
Author(s): Edyta Mikula, Aleksandra Wyslouch-Cieszynska, Liliya Zhukova, Peter Verwilst, Wim Dehaen, Jerzy Radecki and Hanna Radecka
Affiliation:
Keywords: Alzheimer’s disease, pentetic acid-Cu(II) complex, glycated albumin, His-tagged RAGE domains, electrochemical biosensor, redox active monolayer , potential AD biomarkers.
Abstract: Background: Alzheimer’s disease (AD) is the most common form of dementia. The process of AD can begin 20 years before any symptom of cognitive loss. Thus, the development of systems for early diagnosis and prevention is very important. The mechanism of AD is still under debate. Nevertheless, higher levels of glycated albumin in cerebrospinal fluid and plasma are observed in AD patients. Therefore, glycated albumin could be a biomarker of AD development.
Methods: Electrochemical biosensor for direct determination of glycated albumin was based on thiol derivative of pentetic acid (DTPA) complex with Cu(II) created on gold electrode surface. His-tagged domains of Receptors for Advanced Glycation End Products (RAGE) were applied as analytical active element for glycated albumin recognition. The binding of glycated albumin by His6- RAGE domains was monitored using Osteryoung square - wave voltammetry. Results: Electrodes modified with His6 - RAGE VC1 natural domain generated decrease of Cu(II) redox currents in the presence of glycated albumin. Human albumin, Aβ 1-40 and S100B protein caused negligible influence on biosensors responses towards glycated albumin. The detection limits were: 2.3 pM, 1.1 pM, 2.9 pM and 3.1 pM in the presence of: buffer, buffer + albumin, buffer + S100B, buffer + Aβ1-40 , respectively. Conclusion: The presented electrochemical biosensor was successfully applied for the determination of glycated albumin. Considering analytical parameters such as good selectivity and sensitivity in pM range, biosensor could be recommended as an analytical tool for medical samples analysis.Export Options
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Cite this article as:
Mikula Edyta, Wyslouch-Cieszynska Aleksandra, Zhukova Liliya, Verwilst Peter, Dehaen Wim, Radecki Jerzy and Radecka Hanna, Electrochemical Biosensor for the Detection of Glycated Albumin, Current Alzheimer Research 2017; 14 (3) . https://dx.doi.org/10.2174/1567205013666161108110542
DOI https://dx.doi.org/10.2174/1567205013666161108110542 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
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Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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