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Mazur F, Han Z, Tjandra AD, Chandrawati R. Digitalization of Colorimetric Sensor Technologies for Food Safety. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2404274. [PMID: 38932639 DOI: 10.1002/adma.202404274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 06/06/2024] [Indexed: 06/28/2024]
Abstract
Colorimetric sensors play a crucial role in promoting on-site testing, enabling the detection and/or quantification of various analytes based on changes in color. These sensors offer several advantages, such as simplicity, cost-effectiveness, and visual readouts, making them suitable for a wide range of applications, including food safety and monitoring. A critical component in portable colorimetric sensors involves their integration with color models for effective analysis and interpretation of output signals. The most commonly used models include CIELAB (Commission Internationale de l'Eclairage), RGB (Red, Green, Blue), and HSV (Hue, Saturation, Value). This review outlines the use of color models via digitalization in sensing applications within the food safety and monitoring field. Additionally, challenges, future directions, and considerations are discussed, highlighting a significant gap in integrating a comparative analysis toward determining the color model that results in the highest sensor performance. The aim of this review is to underline the potential of this integration in mitigating the global impact of food spoilage and contamination on health and the economy, proposing a multidisciplinary approach to harness the full capabilities of colorimetric sensors in ensuring food safety.
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Affiliation(s)
- Federico Mazur
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Zifei Han
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Angie Davina Tjandra
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Rona Chandrawati
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
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2
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Chen H, Guo S, Zhuang Z, Ouyang S, Lin P, Zheng Z, You Y, Zhou X, Li Y, Lu J, Liu N, Tao J, Long H, Zhao P. Intelligent Identification of Cerebrospinal Fluid for the Diagnosis of Parkinson's Disease. Anal Chem 2024; 96:2534-2542. [PMID: 38302490 DOI: 10.1021/acs.analchem.3c04849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Cerebrospinal fluid (CSF) biomarkers are more sensitive than the Movement Disorder Society (MDS) criteria for detecting prodromal Parkinson's disease (PD). Early detection of PD provides the best chance for successful implementation of disease-modifying treatments, making it crucial to effectively identify CSF extracted from PD patients or normal individuals. In this study, an intelligent sensor array was built by using three metal-organic frameworks (MOFs) that exhibited varying catalytic kinetics after reacting with potential protein markers. Machine learning algorithms were used to process fingerprint response patterns, allowing for qualitative and quantitative assessment of the proteins. The results were robust and capable of discriminating between PD and non-PD patients via CSF detection. The k-nearest neighbor regression algorithm was used to predict MDS scores with a minimum mean square error of 38.88. The intelligent MOF sensor array is expected to promote the detection of CSF biomarkers due to its ability to identify multiple targets and could be used in conjunction with MDS criteria and other techniques to diagnose PD more sensitively and selectively.
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Affiliation(s)
- Huiting Chen
- School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China
| | - Siyun Guo
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Zehong Zhuang
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Sixue Ouyang
- School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China
| | - Peiru Lin
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Zhiyuan Zheng
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yuanyuan You
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiang Zhou
- School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China
| | - Yuan Li
- School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China
| | - Jiajia Lu
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Ningxuan Liu
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Jia Tao
- School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China
| | - Hao Long
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Peng Zhao
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism, Guangdong Provincial Key Laboratory of New Drug Screening, Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
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3
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Bordbar MM, Hosseini MS, Sheini A, Safaei E, Halabian R, Daryanavard SM, Samadinia H, Bagheri H. Monitoring saliva compositions for non-invasive detection of diabetes using a colorimetric-based multiple sensor. Sci Rep 2023; 13:16174. [PMID: 37758789 PMCID: PMC10533566 DOI: 10.1038/s41598-023-43262-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/21/2023] [Indexed: 09/29/2023] Open
Abstract
The increasing population of diabetic patients, especially in developing countries, has posed a serious risk to the health sector, so that the lack of timely diagnosis and treatment process of diabetes can lead to threatening complications for the human lifestyle. Here, a multiple sensor was fabricated on a paper substrate for rapid detection and controlling the progress of the diabetes disease. The proposed sensor utilized the sensing ability of porphyrazines, pH-sensitive dyes and silver nanoparticles in order to detect the differences in saliva composition of diabetic and non-diabetic patients. A unique color map (sensor response) was obtained for each studied group, which can be monitored by a scanner. Moreover, a good correlation was observed between the colorimetric response resulting from the analysis of salivary composition and the fasting blood glucose (FBG) value measured by standard laboratory instruments. It was also possible to classify participants into two groups, including patients caused by diabetes and those were non-diabetic persons with a total accuracy of 88.9%. Statistical evaluations show that the multiple sensor can be employed as an effective and non-invasive device for continuous monitoring of diabetes, substantially in the elderly.
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Affiliation(s)
- Mohammad Mahdi Bordbar
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mahboobeh Sadat Hosseini
- Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Azarmidokht Sheini
- Department of Mechanical Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Khuzestan, Iran
| | - Elham Safaei
- Department of Chemistry, College of Sciences, Shiraz University, Shiraz, Iran
| | - Raheleh Halabian
- Applied Microbiology Research Center, Systems Biology and Poising Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | | | - Hosein Samadinia
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hasan Bagheri
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
- Research Center for Health Management in Mass Gathering, Red Crescent Society of the Islamic Republic of Iran, Tehran, Iran.
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Ko A, Liao C. Paper-based colorimetric sensors for point-of-care testing. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:4377-4404. [PMID: 37641934 DOI: 10.1039/d3ay00943b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
By eliminating the need for sample transportation and centralized laboratory analysis, point-of-care testing (POCT) enables on-the-spot testing, with results available within minutes, leading to improved patient management and overall healthcare efficiency. Motivated by the rapid development of POCT, paper-based colorimetric sensing, a powerful analytical technique that exploits the changes in color or absorbance of a chemical species to detect and quantify analytes of interest, has garnered increasing attention. In this review, we strive to provide a bird's eye view of the development landscape of paper-based colorimetric sensors that harness the unique properties of paper to create low-cost, easy-to-use, and disposable analytical devices, thematically covering both fundamental aspects and categorized applications. In the end, we authors summarized the review with the remaining challenges and emerging opportunities. Hopefully, this review will ignite new research endeavors in the realm of paper-based colorimetric sensors.
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Affiliation(s)
- Anthony Ko
- Renaissance Bio, New Territories, Hong Kong SAR, China.
- Medical School, Sun Yat-Sen University, Guangzhou, China
| | - Caizhi Liao
- Renaissance Bio, New Territories, Hong Kong SAR, China.
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Yadav S, Sadique MA, Ranjan P, Khan R. Synergistically functionalized molybdenum disulfide-reduced graphene oxide nanohybrid based ultrasensitive electrochemical immunosensor for real sample analysis of COVID-19. Anal Chim Acta 2023; 1265:341326. [PMID: 37230571 DOI: 10.1016/j.aca.2023.341326] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/04/2023] [Accepted: 05/04/2023] [Indexed: 05/27/2023]
Abstract
Herein, we have proposed a straightforward and label-free electrochemical immunosensing strategy supported on a glassy carbon electrode (GCE) modified with a biocompatible and conducting biopolymer functionalized molybdenum disulfide-reduced graphene oxide (CS-MoS2/rGO) nanohybrid to investigate the SARS-CoV-2 virus. CS-MoS2/rGO nanohybrid-based immunosensor employs recombinant SARS-CoV-2 Spike RBD protein (rSP) that specifically identifies antibodies against the SARS-CoV-2 virus via differential pulse voltammetry (DPV). The antigen-antibody interaction diminishes the current responses of the immunosensor. The obtained results indicate that the fabricated immunosensor is extraordinarily capable of highly sensitive and specific detection of the corresponding SARS-CoV-2 antibodies with a LOD of 2.38 zg mL-1 in phosphate buffer saline (PBS) samples over a broad linear range between 10 zg mL-1-100 ng mL-1. In addition, the proposed immunosensor can detect attomolar concentrations in spiked human serum samples. The performance of this immunosensor is assessed using actual serum samples from COVID-19-infected patients. The proposed immunosensor can accurately and substantially differentiate between (+) positive and (-) negative samples. As a result, the nanohybrid can provide insight into the conception of Point-of-Care Testing (POCT) platforms for cutting-edge infectious disease diagnostic methods.
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Affiliation(s)
- Shalu Yadav
- CSIR - Advanced Materials and Processes Research Institute (AMPRI), Bhopal - 462026, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India
| | - Mohd Abubakar Sadique
- CSIR - Advanced Materials and Processes Research Institute (AMPRI), Bhopal - 462026, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India
| | - Pushpesh Ranjan
- CSIR - Advanced Materials and Processes Research Institute (AMPRI), Bhopal - 462026, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India
| | - Raju Khan
- CSIR - Advanced Materials and Processes Research Institute (AMPRI), Bhopal - 462026, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India.
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Li J, Zhang K, Yan F, Lang C. A novel single-particle multiple-signal sensor array combined with multidimensional data mining for the detection of tricarboxylic acid cycle metabolites and discrimination of cells. Anal Bioanal Chem 2023:10.1007/s00216-023-04736-1. [PMID: 37278743 DOI: 10.1007/s00216-023-04736-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 06/07/2023]
Abstract
Tricarboxylic acid (TCA) metabolites in cancer cells show a marked difference from those in normal cells. Herein, we report a single-particle multiple-signal lanthanide/europium-based metal-organic framework (Tb/Eu MOF) sensor array for the detection of TCA metabolites and discrimination of cancer cells. In the presence of TCA metabolite, 6 characteristic peaks of Tb/Eu MOF showed dramatic changes due to host-guest interactions, allowing sensor array-based qualitative and quantitative detection to be performed. In the qualitative detection ability test, 18 TCA metabolites at 4 concentrations (50 μM, 100 μM, 200 μM, 300 μM) were accurately discriminated by the sensor array via linear discriminant analysis (LDA). Significantly, these 4 concentrations include the clinical detection criteria for most TCA metabolites. In the quantitative detection ability test, a good linear relationship between Euclidean distances and the concentrations of L-valine (Val) could be obtained in the range of 50 to 500 μM (R2 = 0.9755). On this basis, the provided method was successfully applied for the classification of 2 normal cells and 5 cancer cells via principal components analysis (PCA), LDA and a radial basis function neural network (RBFN). What's more, by verifying the weight coefficient of each point, detection and discrimination results are proved as a trustworthy balanced evaluation of multiple factors. Depending on precise data processing, the experimental operation was simplified on the premise of ensuring accuracy, so our method is a meaningful exploration for array design.
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Affiliation(s)
- Jiawei Li
- Chongqing University Three Gorges Hospital, Chongqing Municipality Clinical Research Center for Geriatric Diseases, Chongqing, China
| | - Kun Zhang
- Chongqing University Three Gorges Hospital, Chongqing Municipality Clinical Research Center for Geriatric Diseases, Chongqing, China
| | - Fei Yan
- Chongqing University Three Gorges Hospital, Chongqing Municipality Clinical Research Center for Geriatric Diseases, Chongqing, China.
| | - Chunhui Lang
- Chongqing University Three Gorges Hospital, Chongqing Municipality Clinical Research Center for Geriatric Diseases, Chongqing, China.
- Department of Clinical Nutrition, Chongqing University Three Gorges Hospital, Chongqing, China.
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Regina de Oliveira T, Oliveira Leite TH, Miranda WN, Manuli ER, Leal F, Sabino E, Pott-Junior H, Melendez M, Faria RC. Molecular test for COVID-19 diagnosis based on a colorimetric genomagnetic assay. Anal Chim Acta 2023; 1257:341167. [PMID: 37062564 PMCID: PMC10066033 DOI: 10.1016/j.aca.2023.341167] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/10/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023]
Abstract
The world is in a long pandemic period caused by the SARS-CoV-2 virus and massive diagnostic tests to assist efforts to control the spread of the disease and also to avoid new coronavirus variants are still needed. Herein, we propose a simple and accurate saliva-based colorimetric test for the diagnosis of COVID-19. Magnetic beads (MBs) modified with a sequence of single-strand DNA (ssDNA) complementary to the N gene of the SARS-CoV-2 RNA were developed and used for magnetic capture and separation from a complex saliva sample. A second biotinylated ssDNA sequence was applied, and the colorimetric detection was carried out by adding streptavidin-horseradish peroxidase conjugate, H2O2, and tetramethylbenzidine (TMB) as chromogenic substrate. The test does not require viral RNA isolation, transcription, or amplification steps and can be performed at room temperature. The molecular assay test can be run using 96-well microplates, allowing the diagnosis of a large number of samples in 90 min. A simple support for magnets was designed and constructed using a 3D printer that allows the magnetic separations directly in the 96-well microplate. The colorimetric test showed an excellent ability to discriminate between healthy individuals and patients infected with SARS-CoV-2, with 92% and 100% of clinical sensitivity and specificity, respectively. This performance was similar to that achieved using the gold standard RT-PCR technique. The proposed genomagnetic assay offers an opportunity to greatly increase population testing, contribute to controlling the spread of the virus, and improve health equity in testing for COVID-19.
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Affiliation(s)
| | | | - Wyllian Neves Miranda
- Department of Chemistry, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil
| | - Erika Regina Manuli
- Municipal University of São Caetano do Sul, São Caetano do Sul, SP, 09521-160, Brazil
| | - Fábio Leal
- Municipal University of São Caetano do Sul, São Caetano do Sul, SP, 09521-160, Brazil
| | - Ester Sabino
- Institute of Tropical Medicine, University of São Paulo, São Paulo, SP, 05403-000, Brazil
| | - Henrique Pott-Junior
- Department of Medicine, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil
| | - Matias Melendez
- Cloning Solutions Ltda, Barretos, SP, 14780-459, Brazil; Molecular Carcinogenesis Program, National Cancer Institute, Rio de Janeiro, RJ, 20231-050, Brazil
| | - Ronaldo Censi Faria
- Department of Chemistry, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil.
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Tarim EA, Anil Inevi M, Ozkan I, Kecili S, Bilgi E, Baslar MS, Ozcivici E, Oksel Karakus C, Tekin HC. Microfluidic-based technologies for diagnosis, prevention, and treatment of COVID-19: recent advances and future directions. Biomed Microdevices 2023; 25:10. [PMID: 36913137 PMCID: PMC10009869 DOI: 10.1007/s10544-023-00649-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 03/14/2023]
Abstract
The COVID-19 pandemic has posed significant challenges to existing healthcare systems around the world. The urgent need for the development of diagnostic and therapeutic strategies for COVID-19 has boomed the demand for new technologies that can improve current healthcare approaches, moving towards more advanced, digitalized, personalized, and patient-oriented systems. Microfluidic-based technologies involve the miniaturization of large-scale devices and laboratory-based procedures, enabling complex chemical and biological operations that are conventionally performed at the macro-scale to be carried out on the microscale or less. The advantages microfluidic systems offer such as rapid, low-cost, accurate, and on-site solutions make these tools extremely useful and effective in the fight against COVID-19. In particular, microfluidic-assisted systems are of great interest in different COVID-19-related domains, varying from direct and indirect detection of COVID-19 infections to drug and vaccine discovery and their targeted delivery. Here, we review recent advances in the use of microfluidic platforms to diagnose, treat or prevent COVID-19. We start by summarizing recent microfluidic-based diagnostic solutions applicable to COVID-19. We then highlight the key roles microfluidics play in developing COVID-19 vaccines and testing how vaccine candidates perform, with a focus on RNA-delivery technologies and nano-carriers. Next, microfluidic-based efforts devoted to assessing the efficacy of potential COVID-19 drugs, either repurposed or new, and their targeted delivery to infected sites are summarized. We conclude by providing future perspectives and research directions that are critical to effectively prevent or respond to future pandemics.
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Affiliation(s)
- E Alperay Tarim
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - Muge Anil Inevi
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - Ilayda Ozkan
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - Seren Kecili
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - Eyup Bilgi
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - M Semih Baslar
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | - Engin Ozcivici
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey
| | | | - H Cumhur Tekin
- Department of Bioengineering, Izmir Institute of Technology, Izmir, Turkey.
- METU MEMS Center, Ankara, Turkey.
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Bordbar MM, Samadinia H, Sheini A, Aboonajmi J, Hashemi P, Khoshsafar H, Halabian R, Khanmohammadi A, Nobakht M Gh BF, Sharghi H, Ghanei M, Bagheri H. Visual diagnosis of COVID-19 disease based on serum metabolites using a paper-based electronic tongue. Anal Chim Acta 2022; 1226:340286. [PMID: 36068068 PMCID: PMC9393192 DOI: 10.1016/j.aca.2022.340286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 08/05/2022] [Accepted: 08/17/2022] [Indexed: 12/12/2022]
Abstract
This study aims to use a paper-based sensor array for point-of-care detection of COVID-19 diseases. Various chemical compounds such as nanoparticles, organic dyes and metal ion complexes were employed as sensing elements in the array fabrication, capturing the metabolites of human serum samples. The viral infection caused the type and concentration of serum compositions to change, resulting in different color responses for the infected and control samples. For this purpose, 118 serum samples of COVID-19 patients and non-COVID controls both men and women with the age range of 14–88 years were collected. The serum samples were initially subjected to the sensor, followed by monitoring the variation in the color of sensing elements for 5 min using a scanner. By taking into consideration the statistical information, this method was capable of discriminating COVID-19 patients and control samples with 83.0% accuracy. The variation of age did not influence the colorimetric patterns. The desirable correlation was observed between the sensor responses and viral load values calculated by the PCR test, proposing a rapid and facile way to estimate the disease severity. Compared to other rapid detection methods, the developed assay is cost-effective and user-friendly, allowing for screening COVID-19 diseases reliably.
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Affiliation(s)
- Mohammad Mahdi Bordbar
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hosein Samadinia
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Azarmidokht Sheini
- Department of Mechanical Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Khuzestan, Iran
| | - Jasem Aboonajmi
- Department of Chemistry, College of Sciences, Shiraz University, Shiraz, Iran
| | - Pegah Hashemi
- Research and Development Department, Farin Behbood Tashkhis LTD, Tehran, Iran
| | - Hosein Khoshsafar
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Raheleh Halabian
- Applied Microbiology Research Center, Systems Biology and Poising Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Akbar Khanmohammadi
- Research and Development Department, Farin Behbood Tashkhis LTD, Tehran, Iran
| | - B Fatemeh Nobakht M Gh
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hashem Sharghi
- Department of Chemistry, College of Sciences, Shiraz University, Shiraz, Iran
| | - Mostafa Ghanei
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hasan Bagheri
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
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