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Facure MHM, Gahramanova G, Zhang D, Zhang T, Shuck CE, Mercante LA, Correa DS, Gogotsi Y. All-MXene electronic tongue for neurotransmitters detection. Biosens Bioelectron 2024; 262:116526. [PMID: 38954905 DOI: 10.1016/j.bios.2024.116526] [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: 02/03/2024] [Revised: 05/19/2024] [Accepted: 06/23/2024] [Indexed: 07/04/2024]
Abstract
Neurotransmitters (NTs) are molecules produced by neurons that act as the body's chemical messengers. Their abnormal levels in the human system have been associated with many disorders and neurodegenerative diseases, which makes the monitoring of NTs fundamentally important. Specifically for clinical analysis and understanding of brain behavior, simultaneous detection of NTs at low levels quickly and reliably is imperative for disease prevention and early diagnosis. However, the methods currently employed are usually invasive or inappropriate for multiple NTs detection. Herein, we developed a MXene-based impedimetric electronic tongue (e-tongue) for sensitive NT monitoring, using Nb2C, Nb4C3, Mo2C, and Mo2Ti2C3 MXenes as sensing units of the e-tongue, and Principal Component Analysis (PCA) as the data treatment method. The high specific surface area, distinct electrical properties, and chemical stability of the MXenes gave rise to high sensitivity and good reproducibility of the sensor array toward NT detection. Specifically, the e-tongue detected and differentiated multiple NTs (acetylcholine, dopamine, glycine, glutamate, histamine, and tyrosine) at concentrations as low as 1 nmol L-1 and quantified NTs present in a mixture. Besides, analyses performed with interferents and actual samples confirmed the system's potential to be used in clinical diagnostics. The results demonstrate that the MXene-based e-tongue is a suitable, rapid, and simple method for NT monitoring with high accuracy and sensitivity.
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Affiliation(s)
- Murilo H M Facure
- Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970, Sao Carlos, SP, Brazil; PPGQ, Department of Chemistry, Center for Exact Sciences and Technology, Federal University of Sao Carlos (UFSCar), 13565-905, Sao Carlos, SP, Brazil; A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA
| | - Gulnaz Gahramanova
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA; French-Azerbaijani University, 183 Nizami Str., AZ1000, Baku, Azerbaijan
| | - Danzhen Zhang
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA
| | - Teng Zhang
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA
| | - Christopher E Shuck
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA
| | - Luiza A Mercante
- Institute of Chemistry, Federal University of Bahia (UFBA), 40170-280, Salvador, BA, Brazil
| | - Daniel S Correa
- Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970, Sao Carlos, SP, Brazil; PPGQ, Department of Chemistry, Center for Exact Sciences and Technology, Federal University of Sao Carlos (UFSCar), 13565-905, Sao Carlos, SP, Brazil.
| | - Yury Gogotsi
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA.
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2
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Braunger M, Neto MP, Kirsanov D, Fier I, Amaral LR, Shimizu FM, Correa DS, Paulovich FV, Legin A, Oliveira ON, Riul A. Analysis of Macronutrients in Soil Using Impedimetric Multisensor Arrays. ACS OMEGA 2024; 9:33949-33958. [PMID: 39130582 PMCID: PMC11307303 DOI: 10.1021/acsomega.4c04452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 07/08/2024] [Accepted: 07/17/2024] [Indexed: 08/13/2024]
Abstract
The need to increase food production to address the world population growth can only be fulfilled with precision agriculture strategies to increase crop yield with minimal expansion of the cultivated area. One example is site-specific fertilization based on accurate monitoring of soil nutrient levels, which can be made more cost-effective using sensors. This study developed an impedimetric multisensor array using ion-selective membranes to analyze soil samples enriched with macronutrients (N, P, and K), which is compared with another array based on layer-by-layer films. The results obtained from both devices are analyzed with multidimensional projection techniques and machine learning methods, where a decision tree model algorithm chooses the calibrations (best frequencies and sensors). The multicalibration space method indicates that both devices effectively distinguished all soil samples tested, with the ion-selective membrane setup presenting a higher sensitivity to K content. These findings pave the way for more environmentally friendly and efficient agricultural practices, facilitating the mapping of cropping areas for precise fertilizer application and optimized crop yield.
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Affiliation(s)
- Maria
Luisa Braunger
- Instituto
de Física “Gleb Wataghin” (IFGW), Universidade Estadual de Campinas—UNICAMP, Campinas 13083-859, São Paulo, Brazil
| | - Mario Popolin Neto
- Federal
Institute of São Paulo—IFSP, Araraquara 14804-296, São Paulo, Brazil
| | - Dmitry Kirsanov
- Institute
of Chemistry, Mendeleev Center, St. Petersburg
State University, Universitetskaya nab.7/9, St. Petersburg 199034, Russia
- Laboratory
of Artificial Sensory Systems, ITMO University, Kronverkskiy pr, 49, St. Petersburg 197101, Russia
| | - Igor Fier
- Quantum
Design Latin America, Campinas 13080-655, São Paulo, Brazil
| | - Lucas R. Amaral
- School of
Agricultural Engineering (FEAGRI), University
of Campinas—UNICAMP, Campinas 13083-875, São Paulo, Brazil
| | - Flavio M. Shimizu
- Instituto
de Física “Gleb Wataghin” (IFGW), Universidade Estadual de Campinas—UNICAMP, Campinas 13083-859, São Paulo, Brazil
| | - Daniel S. Correa
- Nanotechnology
National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, São Paulo, Brazil
| | - Fernando V. Paulovich
- Department
of Mathematics and Computer Science, Eindhoven
University of Technology (TU/e), Eindhoven 5600 MB, The Netherlands
| | - Andrey Legin
- Institute
of Chemistry, Mendeleev Center, St. Petersburg
State University, Universitetskaya nab.7/9, St. Petersburg 199034, Russia
- Laboratory
of Artificial Sensory Systems, ITMO University, Kronverkskiy pr, 49, St. Petersburg 197101, Russia
| | - Osvaldo N. Oliveira
- São
Carlos Institute of Physics (IFSC), University
of São Paulo—USP, São Carlos 13566-590, São Paulo, Brazil
| | - Antonio Riul
- Instituto
de Física “Gleb Wataghin” (IFGW), Universidade Estadual de Campinas—UNICAMP, Campinas 13083-859, São Paulo, Brazil
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3
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Coatrini-Soares A, Soares JC, Popolin-Neto M, de Mello SS, Sanches EA, Paulovich FV, Oliveira ON, Mattoso LHC. Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue. Int J Biol Macromol 2024; 271:132460. [PMID: 38772468 DOI: 10.1016/j.ijbiomac.2024.132460] [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: 03/06/2024] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/23/2024]
Abstract
Mastitis diagnosis can be made by detecting Staphylococcus aureus (S. aureus), which requires high sensitivity and selectivity. Here, we report on microfluidic genosensors and electronic tongues to detect S. aureus DNA using impedance spectroscopy with data analysis employing visual analytics and machine learning techniques. The genosensors were made with layer-by-layer films containing either 10 bilayers of chitosan/chondroitin sulfate or 8 bilayers of chitosan/sericin functionalized with an active layer of cpDNA S. aureus. The specific interactions leading to hybridization in these genosensors allowed for a low limit of detection of 5.90 × 10-19 mol/L. The electronic tongue had four sensing units made with 6-bilayer chitosan/chondroitin sulfate films, 10-bilayer chitosan/chondroitin sulfate, 8-bilayer chitosan/sericin, and 8-bilayer chitosan/gold nanoparticles modified with sericin. Despite the absence of specific interactions, various concentrations of DNA S. aureus could be distinguished when the impedance data were plotted using a dimensionality reduction technique. Selectivity of S. aureus DNA was confirmed using multidimensional calibration spaces, based on machine learning, with accuracy up to 89 % for the genosensors and 66 % for the electronic tongue. Hence, with these computational methods one may opt for the more expensive genosensors or the simpler and cheaper electronic tongue, depending on the sensitivity level required to diagnose mastitis.
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Affiliation(s)
- Andrey Coatrini-Soares
- Embrapa Instrumentação, Nanotechnology National Laboratory for Agriculture (LNNA), São Carlos, Brazil.
| | - Juliana Coatrini Soares
- São Carlos Institute of Physics (IFSC), University of São Paulo (USP), 13566-590 São Carlos, Brazil
| | - Mario Popolin-Neto
- Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), 13566-590 São Carlos, Brazil; Federal Institute of São Paulo (IFSP), 14804-296 Araraquara, Brazil
| | | | | | - Fernando V Paulovich
- Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), 5600 MB Eindhoven, the Netherlands
| | - Osvaldo N Oliveira
- São Carlos Institute of Physics (IFSC), University of São Paulo (USP), 13566-590 São Carlos, Brazil.
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4
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Parshina A, Yelnikova A, Safronova E, Kolganova T, Kuleshova V, Bobreshova O, Yaroslavtsev A. Multisensory Systems Based on Perfluorosulfonic Acid Membranes Modified with Functionalized CNTs for Determination of Sulfamethoxazole and Trimethoprim in Pharmaceuticals. MEMBRANES 2022; 12:1091. [PMID: 36363646 PMCID: PMC9695963 DOI: 10.3390/membranes12111091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 10/29/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Sulfamethoxazole and trimethoprim are synthetic bacteriostatic drugs. A potentiometric multisensory system for the analysis of sulfamethoxazole and trimethoprim combination drugs was developed. Perfluorosulfonic acid membranes containing functionalized CNTs were used as the sensor materials. The CNTs' surface was modified by carboxyl, sulfonic acid, or (3-aminopropyl)trimethoxysilanol groups. The influence of the CNT concentration and the properties of their surface, as well as preliminary ultrasonic treatment of the polymer and CNT solution before the casting of hybrid membranes, on their ion-exchange capacity, water uptake, and transport properties was revealed. Cross-sensitivity of the sensors to the analytes was achieved due to ion exchange and hydrophobic interactions with hybrid membranes. An array of cross-sensitive sensors based on the membranes containing 1.0 wt% of CNTs with sulfonic acid or (3-aminopropyl)trimethoxysilanol groups enabled us to provide the simultaneous determination of sulfamethoxazole and trimethoprim in aqueous solutions with a concentration ranging from 1.0 × 10-5 to 1.0 × 10-3 M (pH 4.53-8.31). The detection limits of sulfamethoxazole and trimethoprim were 3.5 × 10-7 and 1.3 × 10-7 М. The relative errors of sulfamethoxazole and trimethoprim determination in the combination drug as compared with the content declared by the manufacturer were 4% (at 6% RSD) and 5% (at 7% RSD).
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Affiliation(s)
- Anna Parshina
- Department of Analytical Chemistry, Voronezh State University, 394018 Voronezh, Russia
| | - Anastasia Yelnikova
- Department of Analytical Chemistry, Voronezh State University, 394018 Voronezh, Russia
| | - Ekaterina Safronova
- Kurnakov Institute of General and Inorganic Chemistry RAS, 119991 Moscow, Russia
| | - Tatyana Kolganova
- Department of Analytical Chemistry, Voronezh State University, 394018 Voronezh, Russia
| | - Victoria Kuleshova
- Department of Analytical Chemistry, Voronezh State University, 394018 Voronezh, Russia
| | - Olga Bobreshova
- Department of Analytical Chemistry, Voronezh State University, 394018 Voronezh, Russia
| | - Andrey Yaroslavtsev
- Kurnakov Institute of General and Inorganic Chemistry RAS, 119991 Moscow, Russia
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5
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Jońca J, Pawnuk M, Arsen A, Sówka I. Electronic Noses and Their Applications for Sensory and Analytical Measurements in the Waste Management Plants-A Review. SENSORS 2022; 22:s22041510. [PMID: 35214407 PMCID: PMC8877425 DOI: 10.3390/s22041510] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/03/2022] [Accepted: 02/09/2022] [Indexed: 02/06/2023]
Abstract
Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.
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Affiliation(s)
- Justyna Jońca
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
| | - Marcin Pawnuk
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
| | - Adalbert Arsen
- calval.pl sp. z o.o., Emili Plater 7F/8, 65-395 Zielona Góra, Poland;
| | - Izabela Sówka
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
- Correspondence: ; Tel.: +48-71-320-25-60
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6
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Faura G, Boix-Lemonche G, Holmeide AK, Verkauskiene R, Volke V, Sokolovska J, Petrovski G. Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning. SENSORS 2022; 22:s22030718. [PMID: 35161465 PMCID: PMC8839630 DOI: 10.3390/s22030718] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 12/20/2021] [Accepted: 12/26/2021] [Indexed: 12/13/2022]
Abstract
In this review, a selection of works on the sensing of biomarkers related to diabetes mellitus (DM) and diabetic retinopathy (DR) are presented, with the scope of helping and encouraging researchers to design sensor-array machine-learning (ML)-supported devices for robust, fast, and cost-effective early detection of these devastating diseases. First, we highlight the social relevance of developing systematic screening programs for such diseases and how sensor-arrays and ML approaches could ease their early diagnosis. Then, we present diverse works related to the colorimetric and electrochemical sensing of biomarkers related to DM and DR with non-invasive sampling (e.g., urine, saliva, breath, tears, and sweat samples), with a special mention to some already-existing sensor arrays and ML approaches. We finally highlight the great potential of the latter approaches for the fast and reliable early diagnosis of DM and DR.
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Affiliation(s)
- Georgina Faura
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
- Department of Medical Biochemistry, Institute of Clinical Medicine, University of Oslo, 0424 Oslo, Norway
| | - Gerard Boix-Lemonche
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
| | | | - Rasa Verkauskiene
- Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, LT-50009 Kaunas, Lithuania;
| | - Vallo Volke
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia;
- Institute of Biomedical and Transplant Medicine, Department of Medical Sciences, Tartu University Hospital, L. Puusepa Street, 51014 Tartu, Estonia
| | | | - Goran Petrovski
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
- Department of Ophthalmology, Oslo University Hospital, 0450 Oslo, Norway
- Correspondence: ; Tel.: +47-9222-6158
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7
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Gabrieli G, Hu R, Matsumoto K, Temiz Y, Bissig S, Cox A, Heller R, López A, Barroso J, Kaneda K, Orii Y, Ruch PW. Combining an Integrated Sensor Array with Machine Learning for the Simultaneous Quantification of Multiple Cations in Aqueous Mixtures. Anal Chem 2021; 93:16853-16861. [PMID: 34890188 DOI: 10.1021/acs.analchem.1c03709] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The direct quantification of multiple ions in aqueous mixtures is achieved by combining an automated machine learning pipeline with transient potentiometric data obtained from a single miniaturized array of polymeric sensors electrodeposited on a conventional printed circuit board (PCB) substrate. A proof-of-concept system was demonstrated by employing 16 polymeric sensors in combination with features extracted from the transient differential voltages produced by these sensors when transitioning from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. A tree-based regression model enabled concentrations of various metal cations in pure solutions to be determined in less than 2 min. In a model mixture comprising Al3+, Cu2+, Na+, and Fe3+, the mean relative error was found to depend on the type of ion and varied between 1% for Fe3+ and 44% for Na+ in the concentration range 1-10 mg/L. Overall, a mean relative error of 16% was obtained for quantification of these four ions across a total of 124 tests in different solutions spanning concentrations between 2 and 360 mg/L. These results demonstrate how the analytical capability of a multiselective sensor array can leverage data-driven approaches through training by examples for accelerated testing and can be proposed to complement traditional analytical tools to meet industrial demands, including traceability of chemicals.
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Affiliation(s)
| | - Rui Hu
- IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
| | | | - Yuksel Temiz
- IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
| | - Sacha Bissig
- IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
| | - Aaron Cox
- IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, New York 10598, United States
| | - Ralph Heller
- IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
| | - Antonio López
- IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, New York 10598, United States
| | - Jorge Barroso
- IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, New York 10598, United States
| | | | | | - Patrick W Ruch
- IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland
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8
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Sierra-Padilla A, García-Guzmán JJ, López-Iglesias D, Palacios-Santander JM, Cubillana-Aguilera L. E-Tongues/Noses Based on Conducting Polymers and Composite Materials: Expanding the Possibilities in Complex Analytical Sensing. SENSORS (BASEL, SWITZERLAND) 2021; 21:4976. [PMID: 34372213 PMCID: PMC8347095 DOI: 10.3390/s21154976] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/17/2021] [Accepted: 07/18/2021] [Indexed: 01/14/2023]
Abstract
Conducting polymers (CPs) are extensively studied due to their high versatility and electrical properties, as well as their high environmental stability. Based on the above, their applications as electronic devices are promoted and constitute an interesting matter of research. This review summarizes their application in common electronic devices and their implementation in electronic tongues and noses systems (E-tongues and E-noses, respectively). The monitoring of diverse factors with these devices by multivariate calibration methods for different applications is also included. Lastly, a critical discussion about the enclosed analytical potential of several conducting polymer-based devices in electronic systems reported in literature will be offered.
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Affiliation(s)
- Alfonso Sierra-Padilla
- Institute of Research on Electron Microscopy and Materials (IMEYMAT), Department of Analytical Chemistry, Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polígono del Río San Pedro S/N, 11510 Puerto Real, Cadiz, Spain; (A.S.-P.); (L.C.-A.)
| | - Juan José García-Guzmán
- Instituto de Investigación e Innovación Biomédica de Cadiz (INiBICA), Hospital Universitario ‘Puerta del Mar’, Universidad de Cadiz, 11009 Cadiz, Cadiz, Spain;
| | - David López-Iglesias
- Institute of Research on Electron Microscopy and Materials (IMEYMAT), Department of Analytical Chemistry, Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polígono del Río San Pedro S/N, 11510 Puerto Real, Cadiz, Spain; (A.S.-P.); (L.C.-A.)
| | - José María Palacios-Santander
- Institute of Research on Electron Microscopy and Materials (IMEYMAT), Department of Analytical Chemistry, Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polígono del Río San Pedro S/N, 11510 Puerto Real, Cadiz, Spain; (A.S.-P.); (L.C.-A.)
| | - Laura Cubillana-Aguilera
- Institute of Research on Electron Microscopy and Materials (IMEYMAT), Department of Analytical Chemistry, Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polígono del Río San Pedro S/N, 11510 Puerto Real, Cadiz, Spain; (A.S.-P.); (L.C.-A.)
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9
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Pauliukaite R, Voitechovič E. Multisensor Systems and Arrays for Medical Applications Employing Naturally-Occurring Compounds and Materials. SENSORS (BASEL, SWITZERLAND) 2020; 20:E3551. [PMID: 32585936 PMCID: PMC7349305 DOI: 10.3390/s20123551] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/17/2020] [Accepted: 06/20/2020] [Indexed: 12/14/2022]
Abstract
The significant improvement of quality of life achieved over the last decades has stimulated the development of new approaches in medicine to take into account the personal needs of each patient. Precision medicine, providing healthcare customization, opens new horizons in the diagnosis, treatment and prevention of numerous diseases. As a consequence, there is a growing demand for novel analytical devices and methods capable of addressing the challenges of precision medicine. For example, various types of sensors or their arrays are highly suitable for simultaneous monitoring of multiple analytes in complex biological media in order to obtain more information about the health status of a patient or to follow the treatment process. Besides, the development of sustainable sensors based on natural chemicals allows reducing their environmental impact. This review is concerned with the application of such analytical platforms in various areas of medicine: analysis of body fluids, wearable sensors, drug manufacturing and screening. The importance and role of naturally-occurring compounds in the development of electrochemical multisensor systems and arrays are discussed.
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Affiliation(s)
- Rasa Pauliukaite
- Department of Nanoengineering, Center for Physical Sciences and Technology, Savanoriu Ave. 231, LT-02300 Vilnius, Lithuania;
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10
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Masson JF. Portable and field-deployed surface plasmon resonance and plasmonic sensors. Analyst 2020; 145:3776-3800. [PMID: 32374303 DOI: 10.1039/d0an00316f] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Plasmonic sensors are ideally suited for the design of small, integrated, and portable devices that can be employed in situ for the detection of analytes relevant to environmental sciences, clinical diagnostics, infectious diseases, food, and industrial applications. To successfully deploy plasmonic sensors, scaled-down analytical devices based on surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) must integrate optics, plasmonic materials, surface chemistry, fluidics, detectors and data processing in a functional instrument with a small footprint. The field has significantly progressed from the implementation of the various components in specifically designed prism-based instruments to the use of nanomaterials, optical fibers and smartphones to yield increasingly portable devices, which have been shown for a number of applications in the laboratory and deployed on site for environmental, biomedical/clinical, and food applications. A roadmap to deploy plasmonic sensors is provided by reviewing the current successes and by laying out the directions the field is currently taking to increase the use of field-deployed plasmonic sensors at the point-of-care, in the environment and in industries.
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Affiliation(s)
- Jean-Francois Masson
- Departement de chimie, Centre Québécois sur les Matériaux Fonctionnels (CQMF) and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, CP 6128 Succ. Centre-Ville, Montreal, QC, CanadaH3C 3J7.
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11
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Abstract
An electronic tongue (e-tongue) is a multisensory system usually applied to complex liquid media that uses computational/statistical tools to group information generated by sensing units into recognition patterns, which allow the identification/distinction of samples. Different types of e-tongues have been previously reported, including microfluidic devices. In this context, the integration of passive mixers inside microchannels is of great interest for the study of suppression/enhancement of sensorial/chemical effects in the pharmaceutical, food, and beverage industries. In this study, we present developments using a stereolithography technique to fabricate microfluidic devices using 3D-printed molds for elastomers exploring the staggered herringbone passive mixer geometry. The fabricated devices (microchannels plus mixer) are then integrated into an e-tongue system composed of four sensing units assembled on a single printed circuit board (PCB). Gold-plated electrodes are designed as an integral part of the PCB electronic circuitry for a highly automated platform by enabling faster analysis and increasing the potential for future use in commercial applications. Following previous work, the e-tongue sensing units are built functionalizing gold electrodes with layer-by-layer (LbL) films. Our results show that the system is capable of (i) covering basic tastes below the human gustative perception and (ii) distinguishing different suppression effects coming from the mixture of both strong and weak electrolytes. This setup allows for triplicate measurements in 12 electrodes, which represents four complete sensing units, by automatically switching all electrodes without any physical interaction with the sensor. The result is a fast and reliable data acquisition system, which comprises a suitable solution for monitoring, sequential measurements, and database formation, being less susceptible to human errors.
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