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Abbasi Majd S, Kashanian S, Shekarbeygi Z, Babaei M. Simultaneous sensing of carbidopa and levodopa by a novel strategy based on dual-emission ratiometric assay of modified carbon dots. Biotechnol Appl Biochem 2024. [PMID: 38728602 DOI: 10.1002/bab.2595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 04/20/2024] [Indexed: 05/12/2024]
Abstract
Rapid control of the content of Parkinson's drugs in biological fluids and pharmaceutical formulations is of great importance because changes in the concentration of these drugs affect their bioavailability and biopharmaceutical properties. Therefore, we presented a simple and convenient method for the ratiometric detection of carbidopa and levodopa for carbon dots (CDs) dual-fluorescent emission. Dual-emission CDs were prepared from chitosan using a microwave method, following which the surface was chemically modified with terephthalaldehyde. CDs had two strong well-separated peaks at 445 and 510 nm. The relative measurement of carbidopa and levodopa was based on the static extinction of CDs at 445 nm and increase at 510 nm, respectively. The linear range for carbidopa measurement was 2.5-300 nM, with a limit of detection (LOD) of 2.1 nM, and a relative standard deviation (RSD) of 1.68%. Further, the linear range for levodopa measurement was equal to 3.0-400 nM, with LOD and RSD% of 2.8 nM and 3.5%, respectively. Also, selectivity of ratiometric sensor in the presence of interferences was investigated, which showed that the recovery of carbidopa and levodopa in serum and urine samples has changed between 96.80% and 116.24% with RSD% 0.11-0.77. CDs also provided good results for the determination of carbidopa and levodopa in real samples, and had high selectivity in the presence of possible interferences.
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Affiliation(s)
- Sasan Abbasi Majd
- Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran
| | - Soheila Kashanian
- Faculty of Chemistry, Sensor and Biosensor Research Center (SBRC), Razi University, Kermanshah, Iran
- Nanobiotechnology Department, Faculty of Innovative Science and Technology, Razi University, Kermanshah, Iran
| | - Zahra Shekarbeygi
- Nano Drug Delivery Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mahsa Babaei
- Department of Biology, Faculty of Science, Razi University, Kermanshah, Iran
- Department of Biology, Faculty of Sciences, Arak University, Arak, Iran
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Hindam FT, Eltanany BM, Abou Al Alamein AM, El Nashar RM, Arafa RM. A voltammetric method coupled with chemometrics for determination of a ternary antiparkinson mixture in its dosage form: greenness assessment. BMC Chem 2024; 18:90. [PMID: 38725000 PMCID: PMC11080133 DOI: 10.1186/s13065-024-01189-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/16/2024] [Indexed: 05/12/2024] Open
Abstract
An electroanalytical methodology was developed by direct differential pulse voltammetric (DPV) measurement of Levodopa (LD), Carbidopa (CD) and Entacapone (ENT) mixture using bare glassy carbon electrode (GCE) in Britton Robinson (BR) buffer (pH = 2.0). A multivariate calibration model was then applied to the exported preprocessed voltammetric data using partial least square (PLS) as a chemometric tool. Additionally, the model was cross-validated and the number of latent variables (LVs) were determined to produce a reliable model for simultaneous quantitation of the three drugs either in their synthetic mixtures or in their marketed pharmaceutical formulation with high accuracy and precision. Data preprocessing was used to tackle the problem of lacking bi-linearity which is commonly found in electrochemical data. The proposed chemometric model was able to provide fast and reliable technique for quantitative determination of antiparkinson drugs in their dosage forms. This was successfully achieved by utilizing sixteen mixtures as calibration set and nine mixtures as validation set. The percent recoveries for LD, CD and ENT were found to be 100.05% ± 1.28%, 100.04% ± 0.53% and 99.99% ± 1.25%, respectively. The obtained results of the proposed method were statistically compared to those of a previously reported High Performance Liquid Chromatography (HPLC) methodology. Finally, the presented analytical method strongly supports green analytical chemistry regarding the minimization of potentially dangerous chemicals and solvents, as well as reducing energy utilization and waste generation.
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Affiliation(s)
| | - Basma M Eltanany
- Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, P.O. Box 11562, Cairo, Egypt
| | - Amal M Abou Al Alamein
- Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, P.O. Box 11562, Cairo, Egypt
| | - Rasha M El Nashar
- Chemistry Department, Faculty of Science, Cairo University, P.O. Box 12613, Giza, Egypt
| | - Reham M Arafa
- Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, P.O. Box 11562, Cairo, Egypt.
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3
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Salimian M, Reza Sohrabi M, Mortazavinik S. Application of net analyte signal and principal component regression for rapid simultaneous determination of Levodopa and carbidopa in commercial pharmaceutical formulation and breast (human) milk sample using spectrophotometric method. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 283:121741. [PMID: 35994995 DOI: 10.1016/j.saa.2022.121741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/02/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
In this study, a UV-vis spectrophotometric method coupled with net analyte signal (NAS) and principal component regression (PCR) as multivariate calibration methods were used for the simultaneous determination of levodopa (LEV) and carbidopa (CBD) in prepared mixtures, pharmaceutical formulation, and breast milk sample. The mean recovery of the NAS model was 98.10% and 99.60% for LEV and CBD, respectively. Also, the relative standard deviation (RSD%) values were found to be lower than 5.5% and 4% for LEV and CBD, respectively. On the other hand, the mean recovery of LEV and CBD related to the PCR method was obtained at 96.86% and 92.43%, respectively. K-Fold cross-validation was used to estimate the number of components, which was 7 and 3 with a mean square error prediction (MSEP) of 1.50 and 7.14 for LEV and CBD, respectively. The results revealed that the NAS model was better than the PCR model. Additionally, the proposed NAS-based calibration method was successfully developed for the simultaneous analyses of LEV and CBD in a commercial tablet and breast milk.
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Affiliation(s)
- Masoumeh Salimian
- Department of Chemistry, Islamic Azad University, North Tehran Branch, Tehran, Iran
| | - Mahmoud Reza Sohrabi
- Department of Chemistry, Islamic Azad University, North Tehran Branch, Tehran, Iran.
| | - Saeed Mortazavinik
- Department of Chemistry, Islamic Azad University, North Tehran Branch, Tehran, Iran
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Xiang G, He X, Liu Y, Huang Q, Huang W, Zhang C, Peng J. A Sensitive Photoelectrochemical Sensor for Levodopa Detection Using Benzothiadiazole-Based Conjugated Microporous Polymer-Coated Graphene Heterostructures. ACS APPLIED MATERIALS & INTERFACES 2022; 14:51329-51340. [PMID: 36326124 DOI: 10.1021/acsami.2c15516] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Since the 1960s, levodopa (LDA) has been the standard drug for treating of Parkinson's disease. In this study, a novel benzothiadiazole-based conjugated microporous polymer-coated graphene heterostructure (CMP-rGO) was synthesized and used to construct a sensitive photoelectrochemical (PEC) sensor capable of detecting LDA. Under optimal experimental conditions, the intensity of the photocurrent produced by the sensor was linear from 0.005 to 40 μM, and the limit of detection of the sensor was 0.0027 μM. The sensor showed good repeatability, stability, and selectivity for LDA detection. Finally, the constructed sensor was used to detect LDA in levodopa tablets, human serum samples, and urine samples and satisfactory results were obtained. Therefore, the PEC sensor provides a novel platform for the detection of LDA in real samples and broadens the applications of conjugated microporous polymers in PEC sensing.
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Affiliation(s)
- Gang Xiang
- College of Chemical and Biological Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
- Photochemical Sensing and Regional Environmental Analysis Laboratory, Guangxi Normal University for Nationalities, Chongzuo532200, China
| | - Xiansen He
- School of Pharmacy, Henan University of Traditional Chinese Medicine, Zhengzhou450046, China
| | - Yuxia Liu
- College of Mathematics, Physics and Electronic Information Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
| | - Qing Huang
- College of Chemical and Biological Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
- Photochemical Sensing and Regional Environmental Analysis Laboratory, Guangxi Normal University for Nationalities, Chongzuo532200, China
| | - Wei Huang
- College of Chemical and Biological Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
- Photochemical Sensing and Regional Environmental Analysis Laboratory, Guangxi Normal University for Nationalities, Chongzuo532200, China
| | - Cuizhong Zhang
- College of Chemical and Biological Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
- Photochemical Sensing and Regional Environmental Analysis Laboratory, Guangxi Normal University for Nationalities, Chongzuo532200, China
| | - Jinyun Peng
- College of Chemical and Biological Engineering, Guangxi Normal University for Nationalities, Chongzuo532200, China
- Photochemical Sensing and Regional Environmental Analysis Laboratory, Guangxi Normal University for Nationalities, Chongzuo532200, China
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Safarpour D, Brumbach BH, Arena M, Quinn J, Diamond S, Nutt JG, Pfeiffer R. Gastrointestinal Motility and Response to Levodopa in Parkinson's Disease: A Proof-of-Concept Study. Mov Disord 2022; 37:2153-2158. [PMID: 35969014 DOI: 10.1002/mds.29176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/24/2022] [Accepted: 07/18/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Simultaneous measurement of gastrointestinal transit time (GITT) and plasma levodopa concentration (PLC) is crucial to understanding the effect of dysfunctional motility on levodopa response in patients with Parkinson's disease (PwPD). OBJECTIVE The aim is to determine if altered segmental GITT correlates with clinical response and PLC variability in PwPD. METHODS Ten typical and 10 erratic responders ingested the SmartPill (SP) wireless motility capsule. Serial PLC and finger tapping, obtained every 30 minutes for 3 hours after SP/levodopa ingestion, evaluated the correlation between GITT, clinical response, and PLC. Glucose breath testing assessed small intestinal bacterial overgrowth (SIBO). RESULTS GITT was not significantly different in "typical" and "erratic" responders. SIBO was positive in half of the erratic and negative in most typical responders. CONCLUSION SP is a feasible technology for assessing GITT in PwPD. A larger study may be able to significantly differentiate/correlate GITT in different segments of the GI tract with response to levodopa. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Delaram Safarpour
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Barbara H Brumbach
- OHSU-PSU School of Public Health, Biostatistics and Design Program, Oregon Health & Science University, Portland, Oregon, USA
| | - Monica Arena
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Joseph Quinn
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Sarah Diamond
- Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Jay G Nutt
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - RonaldF Pfeiffer
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
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Determination of levodopa by chromatography-based methods in biological samples: a review. ANAL SCI 2022; 38:1009-1017. [PMID: 35715690 DOI: 10.1007/s44211-022-00132-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/12/2022] [Indexed: 11/01/2022]
Abstract
Levodopa (L-DOPA) is the most effective drug for Parkinson's disease; however, various side effects occur during therapy. L-DOPA metabolites and the high cumulative dose of L-DOPA were responsible for its side effects. It is necessary to monitor the concentration of L-DOPA and its metabolites for individualized therapy. This review focuses on L-DOPA analysis by chromatography-based methods in biological matrices. Literature published up to September 2021 was collected in the PubMed, Web of Science, and Embase by using search strategy ("levodopa" OR "L-DOPA") AND ("chromatography"). A total of 1249 articles were identified and 32 articles were included. The contents for method development and validation were summarized and analyzed. Due to the instability of catecholamines (L-DOPA, dopamine, and 3-O-methyldopa) and carbidopa, antioxidation (0.5 mg sodium metabisulfite for 100 μL sample) and environment temperature control were used alone or in combination to enhance stability. Sample was mainly pretreated by protein precipitation (0.4-0.7 M perchloric acid). Separation was usually achieved using methanol or acetonitrile:water (with formic acid) on C18 columns. Mass spectrometry, electrochemical detector, ultraviolet-visible detector and fluorescence detector were used for detection. For L-DOPA, the calibration range was 2.5-10,000 ng/mL, the matrix effect and its coefficient of variation was 85-115 and -9.0-8.5%, and the recovery was 66.8-127.0%. Without stabilization strategy, L-DOPA was stable in plasma at room temperature for 1-7 h (4-6 h for most studies), at - 70 °C to - 80 °C for 10-20 days and after 3-5 freeze-thaw cycles. With stabilization strategies, the stability of L-DOPA in plasma was significantly improved. Metabolites of L-DOPA and enzyme inhibitors (carbidopa, entacapone, tolcapone and benserazide) were all stable in biological matrix. This study might be useful for researchers to develop their methods for individualized therapy of patients with Parkinson.
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Navid Arbabi, Hadi Beitollahi. A New Sensor Based on a La3+/Co3O4 Nanoflowers Modified Screen Printed Electrode for a Sensitive Simultaneous Determination of Levodopa and Tryptophan. SURFACE ENGINEERING AND APPLIED ELECTROCHEMISTRY 2022. [DOI: 10.3103/s106837552203005x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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8
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Unal DN, Yıldırım S, Kurbanoglu S, Uslu B. Current trends and roles of surfactants for chromatographic and electrochemical sensing. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116418] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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9
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Parhizkar E, Mohammadi Z, Alipour S. Rapid High-Performance Liquid Chromatography Method for Levodopa Quantitation at Low UV Wavelength: Application of Pharmacokinetics Study in Rat Following Intranasal Delivery. J Chromatogr Sci 2021; 59:347-354. [PMID: 33367562 DOI: 10.1093/chromsci/bmaa114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 09/29/2020] [Accepted: 11/12/2020] [Indexed: 11/12/2022]
Abstract
Levodopa is widely administered orally in clinical treatment of Parkinson's disease; however, due to levodopa various oral absorption and low bioavailability, intranasal delivery seems to be a suitable alternative route of administration. Pluronic F-127 is a thermosensitive polymer, which can form gel at nasal cavity temperature and increase drug residence time. In this study, a rapid High Performance Liquid Chromatography (HPLC) method was validated in presence of internal standard to determine pharmacokinetic parameters following levodopa administration to rats in three different intravenous solution, intranasal solution and intranasal thermosensitive gel groups. A precised (96.7%) and accurate (95.0%) HPLC method was validated at low UltraViolet (UV) wavelength of 208 nm that showed limit of detection and limit of quantitation of 59 and 177 ng/mL, respectively. Specificity results showed no interference for levodopa with endogenous serum materials, and serum extraction efficacy was 93%. Pharmacokinetic parameters including bioavailability of 75 and 85% with mean residence time of 78 and 94 min were estimated for intranasal solution and thermosensitive gel using the validated HPLC method, which indicated that levodopa nasal gel may be a good alternative with appropriate pharmacokinetic outcome. Therefore, the validated levodopa HPLC analysis method at low UV wavelength was efficiently applied in pharmacokinetic study.
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Affiliation(s)
- Elahehnaz Parhizkar
- Department of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Zahra Mohammadi
- Department of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Shohreh Alipour
- Pharmaceutical Sciences Research Center, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.,Department of Quality Control, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
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Sun X, Wang N, Xie Y, Chu H, Wang Y, Wang Y. In-situ anchoring bimetallic nanoparticles on covalent organic framework as an ultrasensitive electrochemical sensor for levodopa detection. Talanta 2021; 225:122072. [DOI: 10.1016/j.talanta.2020.122072] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 12/25/2020] [Accepted: 12/26/2020] [Indexed: 12/26/2022]
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Liang W, Gao M, Li Y, Tong Y, Ye BC. Single-atom electrocatalysts templated by MOF for determination of levodopa. Talanta 2020; 225:122042. [PMID: 33592765 DOI: 10.1016/j.talanta.2020.122042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 12/17/2020] [Accepted: 12/21/2020] [Indexed: 11/25/2022]
Abstract
To overcome the problem of incorrect levodopa (LD) dosage in the treatment of Parkinson's disease, a new analytical tool is urgently needed for accurately determining the concentration of LD in human fluids. Herein, an effective and stable sensor based on a Co-single-atomic-site catalyst (Co-SASC)-modified glassy carbon electrode (Co-SASC/GCE) was developed for the determination of LD concentration. The physicochemical characterization of Co-SASC is systematically investigated. It has excellent thermal stability, graphitization degree, and a large specific surface area. Benefiting from its porous structure for kinetically fast catalysis and component advantages for fix a single cobalt atom to improve stability, Co-SASC/GCE exhibits a superior electrochemical response. Under optimal conditions (pH 2.0, coating amount is 10 μg), an ideal linear relationship is achieved between the logarithm of the peak current of the sensor and the logarithm of LD concentration. The linear range is 0.1-200 μM, and the limit of detection (LOD) is 0.033 μM. After a simple pretreatment, LD in human serum is detected by Co-SASC/GCE with excellent stability and selectivity. As such, this work enlarges the existing electrochemical sensor toolbox by offering a reasonable design and synthesis protocol for advanced materials to accurately determine LD in human fluids for the clinical treatment of Parkinson's disease.
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Affiliation(s)
- Wencui Liang
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Ming Gao
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Yangguang Li
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Yanbin Tong
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Bang-Ce Ye
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China; Institute of Engineering Biology and Health, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China.
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Asadpour Joghani R, Abbas Rafati A, Ghodsi J, Assari P, Feizollahi A. First Report for Levodopa Electrocatalytic Oxidation Based on Copper Metal‐Organic Framework (MOF): Application in a Voltammetric Sensor Development for Levodopa in Real Samples. ChemistrySelect 2020. [DOI: 10.1002/slct.202001781] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Amir Abbas Rafati
- Department of Physical Chemistry, Faculty of ChemistryBu-Ali Sina University P.O.Box 65174 Hamedan Iran
| | - Javad Ghodsi
- Department of Physical Chemistry, Faculty of ChemistryBu-Ali Sina University P.O.Box 65174 Hamedan Iran
| | - Parnaz Assari
- Department of Physical Chemistry, Faculty of ChemistryBu-Ali Sina University P.O.Box 65174 Hamedan Iran
| | - Azizallah Feizollahi
- Department of Physical Chemistry, Faculty of ChemistryBu-Ali Sina University P.O.Box 65174 Hamedan Iran
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13
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Smartphone-Based Electrochemical Potentiostat Detection System Using PEDOT: PSS/Chitosan/Graphene Modified Screen-Printed Electrodes for Dopamine Detection. SENSORS 2020; 20:s20102781. [PMID: 32422926 PMCID: PMC7285078 DOI: 10.3390/s20102781] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 05/09/2020] [Accepted: 05/11/2020] [Indexed: 01/16/2023]
Abstract
In this work, a smartphone-based electrochemical detection system was designed and developed for rapid and real-time detection of dopamine (DA). The system included a screen-printed electrode (SPE) used as a sensor, a hand-held electrochemical potentiostat and a smart phone with a specially designed app. During the detection period, the SPEs modified with poly(3,4-ethylenedioxythiophene) (PEDOT), chitosan (CS) and graphene (G) were used to convert and amplify the electrochemical reaction signals. The electrochemical potentiostat was used to generate excitation electrical signals and collect the electrical signals converted from the sensor. The smartphone—connected to the detector via Bluetooth-was used to control the detector for tests, further process the uploaded data, and plot graphs in real time. Experimental results showed that the self-designed sensing system could be employed for highly selective detection of DA in the presence of interfering substances such as ascorbic acid (AA) and uric acid (UA). CV was carried out to characterize the electrochemical properties of the modified SPEs and the electrochemical behaviors of DA on the modified SPEs. Finally, according to the analysis of DPV responses of DA, the system could detect DA with a detection sensitivity of 0.52 ± 0.01 μA/μM and a limit of detection of 0.29 μM in the linear range of DA concentrations from 0.05 to 70 μM.
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14
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Submicellar liquid chromatography with fluorescence detection improves the analysis of naproxen in plasma and brain tissue. J Sep Sci 2019; 42:1702-1709. [DOI: 10.1002/jssc.201801250] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 02/18/2019] [Accepted: 02/18/2019] [Indexed: 11/07/2022]
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15
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Entacapone detection by a GOQDs-molecularly imprinted silica fluorescent chemical nanosensor. Anal Bioanal Chem 2019; 411:1075-1084. [DOI: 10.1007/s00216-018-1534-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 11/08/2018] [Accepted: 12/03/2018] [Indexed: 10/27/2022]
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16
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Ji D, Xu N, Liu Z, Shi Z, Low SS, Liu J, Cheng C, Zhu J, Zhang T, Xu H, Yu X, Liu Q. Smartphone-based differential pulse amperometry system for real-time monitoring of levodopa with carbon nanotubes and gold nanoparticles modified screen-printing electrodes. Biosens Bioelectron 2018; 129:216-223. [PMID: 30297172 DOI: 10.1016/j.bios.2018.09.082] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 09/18/2018] [Accepted: 09/22/2018] [Indexed: 02/06/2023]
Abstract
Parkinson's disease caused by lack of dopamine in brain is a common neurodegenerative disorder. The traditional treatment is to replenish levodopa since it could pass through blood brain barrier and form dopamine. However, its accumulation can cause patients' movement disorders and uncontrollable emotion. Therefore, it is critical to control the levodopa dosage accuracy to improve the curative effect in clinical. In this study, a smartphone-based electrochemical detection system was developed for rapid monitoring of levodopa. The system involved a disposable sensor, a hand-held electrochemical detector, and a smartphone with designed application. Single-wall carbon nanotubes and gold nanoparticles modified screen-printed electrodes were used to convert and amplify the electrochemical current signals upon presence of levodopa molecules. The electrochemical detectors were used to generate electrochemical excitation signals and detect the resultant currents. Smartphone was connected to the detector, which was used to control the detector, calculate data, and plot graph in real-time. The smartphone-based differential pulse amperometry system was demonstrated to monitor levodopa at concentrations as low as 0.5 µM in human serum. Furthermore, it has also been verified to be able to distinguish levodopa from other representative substances in the body. Therefore, its performance was more sensitive and rapid than electrochemical workstation. With these advantages, the system can be used in the field of point-of-care testing (POCT) to detect levodopa and provide the possibility to solve clinical demand for levodopa detection.
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Affiliation(s)
- Daizong Ji
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China; Zhejiang University Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang Province, PR China; Collaborative Innovation Center of TCM Health Management, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, PR China
| | - Ning Xu
- Institute of Automation Engineering, Northeast Electric Power University, Jilin 132012, PR China
| | - Zixiang Liu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Zhouyuanjing Shi
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Sze Shin Low
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Jingjing Liu
- Institute of Automation Engineering, Northeast Electric Power University, Jilin 132012, PR China
| | - Chen Cheng
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China; Collaborative Innovation Center of TCM Health Management, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, PR China
| | - Jingwen Zhu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Tingkai Zhang
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Haoxuan Xu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China
| | - Xiongjie Yu
- Zhejiang University Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang Province, PR China
| | - Qingjun Liu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China; Collaborative Innovation Center of TCM Health Management, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, PR China.
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