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Karaboğa MNS, Sezgintürk MK. Biosensor approaches on the diagnosis of neurodegenerative diseases: Sensing the past to the future. J Pharm Biomed Anal 2022; 209:114479. [PMID: 34861607 DOI: 10.1016/j.jpba.2021.114479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 11/05/2021] [Accepted: 11/14/2021] [Indexed: 12/12/2022]
Abstract
Early diagnosis of neurodegeneration-oriented diseases that develop with the aging world is essential for improving the patient's living conditions as well as the treatment of the disease. Alzheimer's and Parkinson's diseases are prominent examples of neurodegeneration characterized by dementia leading to the death of nerve cells. The clinical diagnosis of these diseases only after the symptoms appear, delays the treatment process. Detection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, has the potential to allow early diagnosis of neurodegenerative diseases. Studies on biosensors, whose main responsibility is to detect the target analyte with high specificity, has gained momentum in recent years with the aim of high detection of potential biomarkers of neurodegeneration process. This study aims to provide an overview of neuro-biosensors developed on the basis of biomarkers identified in biological fluids for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD), and Parkinson's disease (PD), and to provide an overview of the urgent needs in this field, emphasizing the importance of early diagnosis in the general lines of the neurodegeneration pathway. In this review, biosensor systems developed for the detection of biomarkers of neurodegenerative diseases, especially in the last 5 years, are discussed.
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Wang J, Liu L, Jiang J. Investigation of the spectroelectrochemical behavior of quercetin isolated from Zanthoxylum bungeanum. OPEN CHEM 2021. [DOI: 10.1515/chem-2021-0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Flavonoids are common bioactive components in plants. Quercetin is the most abundant flavonoid in the human diet, accounting for more than half of the total daily consumption of flavonoids. In this study, adsorption and electrocatalytic activities of quercetin isolated from Zanthoxylum bungeanum on an electrode was studied via homemade electrodes. An in situ UV-Visible thin-layer spectroelectrochemical method was used to study the electrochemical behavior of quercetin in detail and to explore its electrochemical reaction mechanism. This experiment proves that UV-Vis thin-layer spectroelectrochemistry is a feasible way for studying the electrochemical reaction mechanism of flavonoids in plants.
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Affiliation(s)
- Jun Wang
- Department of Pharmacy, The Hospital of Zhejiang University , Hangzhou , Zhejiang 310027 , China
| | - Linxiang Liu
- Department of Pharmacy, The Hospital of Zhejiang University , Hangzhou , Zhejiang 310027 , China
| | - Jianwei Jiang
- Department of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital) , Hangzhou , Zhejiang 310022 , China
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences , Hangzhou , Zhejiang 310022 , China
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Oliveira LG, Lemos SG, Fragoso WD. Simultaneous determination of benzenediol isomers in tap water by second-order calibration and voltabsorptometry. Electrochim Acta 2020. [DOI: 10.1016/j.electacta.2020.136591] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Shui B, Tao D, Florea A, Cheng J, Zhao Q, Gu Y, Li W, Jaffrezic-Renault N, Mei Y, Guo Z. Biosensors for Alzheimer's disease biomarker detection: A review. Biochimie 2018; 147:13-24. [PMID: 29307704 DOI: 10.1016/j.biochi.2017.12.015] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 12/29/2017] [Indexed: 12/15/2022]
Abstract
Alzheimer's disease (AD) is a chronic disease amongst people aged 65 and older. Increasing evidence has illustrated that early diagnosis holds the key to effective treatment of AD. A variety of detection techniques have been developed. Biosensors are excellent analytical tools which have applications in detecting the biomarkers of AD. This review includes appropriate bioreceptors to achieve highly sensitive and selective quantification of AD biomarkers by using transducers. AD biomarkers such as tau protein, amyloid β peptides and apolipoprotein E4, are firstly summarized. The most commonly used bioreceptors, including aptamers and antibodies, are also reviewed. We introduce aptamers specific to AD biomarkers, list the sequences of aptamers designed to capture AD biomarkers and compare the properties of aptamers with those of antibodies with regard to their efficiency as bio-recognition elements. We discuss the recent progress of aptamer systems' applications in AD biomarkers in biosensing. The review also discusses novel strategies used for signal amplification in sensing AD biomarkers.
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Affiliation(s)
- Bingqing Shui
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Dan Tao
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Anca Florea
- Analytical Chemistry Department, Faculty of Pharmacy, Iuliu Haţieganu University of Medicine and Pharmacy, Cluj-Napoca 400012, Romania.
| | - Jing Cheng
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Qin Zhao
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Yingying Gu
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Wen Li
- School of Arts, Wuhan Business University, Wuhan 430056, PR China.
| | - Nicole Jaffrezic-Renault
- Institute of Analytical Sciences, UMR-CNRS 5280, University of Lyon, 5, Rue de La Doua, Villeurbanne 69100, France.
| | - Yong Mei
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
| | - Zhenzhong Guo
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, PR China.
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