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Du Nguyen D, Shuklin F, Barulina E, Albitskaya H, Novikov S, Chernov AI, Kim I, Barulin A. Recent advances in dynamic single-molecule analysis platforms for diagnostics: Advantages over bulk assays and miniaturization approaches. Biosens Bioelectron 2025; 278:117361. [PMID: 40117897 DOI: 10.1016/j.bios.2025.117361] [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: 02/06/2025] [Revised: 03/06/2025] [Accepted: 03/08/2025] [Indexed: 03/23/2025]
Abstract
Single-molecule science is a unique technique for unraveling molecular biophysical processes. Sensitivity to single molecules provides the capacity for the early diagnosis of low biomarker amounts. Furthermore, the miniaturization of instruments for portable diagnostic tools toward point-of-care testing (POCT) is a crucial development in this field. Herein, we discuss recent developments in single-molecule sensing platforms and their advantages for diagnostics over bulk measurements including molecular size measurements, interaction dynamics, and fast biomarker sensing and sequencing at low concentrations. We highlight the capabilities of dynamic optical and electrical sensing platforms for single-biomolecule and single-vesicle monitoring associated with neurodegenerative disorders, viral diseases, cancers, and more. Current approaches to instrument miniaturization have brought technology closer to portable diagnostics settings via smartphone-based devices, multifunctional portable microscopes, handheld electrical circuit devices, and remote single-molecule assays. Finally, we provide an overview of the clinical applications of single-molecule sensors in POCT assays. Altogether, single-molecule analyses platforms exhibit significant potential for the development of novel portable healthcare devices.
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Affiliation(s)
- Dang Du Nguyen
- Department of Biophysics, Institute of Quantum Biophysics, Sungkyunkwan University, Suwon, 16419, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Fedor Shuklin
- Moscow Center for Advanced Studies, Kulakova str. 20, Moscow, 123592, Russia
| | - Elena Barulina
- Moscow Center for Advanced Studies, Kulakova str. 20, Moscow, 123592, Russia; Russian Quantum Center, Moscow, 121205, Russia
| | - Hristina Albitskaya
- Moscow Center for Advanced Studies, Kulakova str. 20, Moscow, 123592, Russia
| | - Sergey Novikov
- Moscow Center for Advanced Studies, Kulakova str. 20, Moscow, 123592, Russia
| | - Alexander I Chernov
- Russian Quantum Center, Moscow, 121205, Russia; Center for Photonics and 2D Materials, Moscow Institute of Physics and Technology, Dolgoprudny, 141700, Russia.
| | - Inki Kim
- Department of Biophysics, Institute of Quantum Biophysics, Sungkyunkwan University, Suwon, 16419, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, 16419, Republic of Korea; Department of MetaBioHealth, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Aleksandr Barulin
- Moscow Center for Advanced Studies, Kulakova str. 20, Moscow, 123592, Russia.
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2
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Piscitelli M, Franco CD, Bianco GV, Bruno G, Macchia E, Torsi L, Scamarcio G. Graphene-Based Opto-Electronic Platform for Ultra-Sensitive Biomarker Detection at Zeptomolar Concentrations. SMALL METHODS 2025:e2402026. [PMID: 39838731 DOI: 10.1002/smtd.202402026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Revised: 01/13/2025] [Indexed: 01/23/2025]
Abstract
A ground-breaking graphene-based biosensor designed for label-free detection of immunoglobulin M (IgM) achieving a remarkable concentration of 100 zeptomolar (10-19 m), is reported. The sensor is a two-terminal device and incorporates a millimeter-wide gold interface, bio-functionalized with ≈1012 anti-IgM antibodies and capacitively coupled to a bare graphene electrode through a water-soaked paper strip. In this configuration, few affinity binding events trigger a collective electrostatic reorganization of the protein layer, leading to an extended surface potential (SP) shift of the biofunctionalized Au surface. The SP shift, mediated by electrolyte capacitive coupling, induces a corresponding shift in the Fermi level of graphene. This shifts the graphene phonon frequencies, which are measured by Raman spectroscopy. Decoupling the sensing interface from the transducing graphene layer provides flexibility in surface chemistry modifications, while preserving the graphene integrity. A key aspect of this biosensor is its ability to precisely determine the graphene charge neutrality point from the voltage dependence of phonon frequency shifts, enabling detections of biomarker at unprecedented low concentrations. The integration of graphene with optical probing demonstrates a proof-of-concept and establishes a ground-breaking approach to in situ biomarker detection, setting the stage for a future generation of portable opto-electronic high-performance diagnostic tools for single-marker detection.
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Affiliation(s)
- Matteo Piscitelli
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy and CNR IFN, Bari, 70125, Italy
| | - Cinzia Di Franco
- Consiglio Nazionale delle Ricerche - Consiglio Nazionale delle Ricerche - Istituto di Fotonica e Nanotecnologie, CNR-IFN, Bari, 70125, Italy
| | - Giuseppe Valerio Bianco
- Consiglio Nazionale delle Ricerche -Istituto di Nanotecnologia, CNR-Nanotech, Bari, 70125, Italy
| | - Giovanni Bruno
- Consiglio Nazionale delle Ricerche -Istituto di Nanotecnologia, CNR-Nanotech, Bari, 70125, Italy
| | - Eleonora Macchia
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, 70125, Italy
| | - Luisa Torsi
- Dipartimento di Chimica, Università degli Studi di Bari Aldo Moro, Bari, 70125, Italy
| | - Gaetano Scamarcio
- NEST, Istituto Nanoscienze - CNR and Scuola Normale Superiore, Pisa, I-56127, Italy
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3
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Chen J, Liu T, Zhang Y, Duan M, Yang Z, Chen M, Wang Y, Zheng L, Zhuang S, Zhang D. One-step time-resolved cascade logic gate microfluidic chip for home testing of SARS-CoV-2 and flu B. Biosens Bioelectron 2024; 263:116564. [PMID: 39033655 DOI: 10.1016/j.bios.2024.116564] [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: 05/10/2024] [Revised: 06/28/2024] [Accepted: 07/10/2024] [Indexed: 07/23/2024]
Abstract
Home testing technology strategy is critical for early screening of disease. However, current home testing technologies often require complex processes, which limits their application. In this study, a time-resolved cascade logic gate microfluidic chip (TCLMC) was revealed to enable capillary force-based one-step operation without manual intervention or professional equipment. By analogy with logic gates in the circuit, TCLMC could automatically control the fluid flow and regulate the incubation time to optimize the immunoassay. The limit of detection of TCLMC for SARS-CoV-2 and influenza B virus (Flu B) was 134.94 and 79.17 pg mL-1 within 10 min. Additionally, this study tested saliva samples from 12 Flu B patients and 24 healthy controls to verify its clinical application. The results showed that TCLMC had high sensitivity (100%), specificity (100%), and accuracy (100%). This study provides a new one-step strategy for home testing and demonstrates its great potential in the diagnosis field.
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Affiliation(s)
- Jingwei Chen
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Tingting Liu
- Department of Pediatric Hematology/Oncology, Xinhua Hospital, Shanghai Jiaotong University, School of Medicine, Kongjiang Road 1665, Shanghai, 200092, PR China
| | - Yule Zhang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Mengnan Duan
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Zhijin Yang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Mengya Chen
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Yiran Wang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Lulu Zheng
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China.
| | - Songlin Zhuang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China
| | - Dawei Zhang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai, 200093, PR China; Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, 200092, PR China
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4
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Lin B, Li B, Zeng W, Zhao Y, Li H, Gu Y, Liu P. Needle-Plug/Piston-Based Modular Mesoscopic Design Paradigm Coupled With Microfluidic Device for Point-of-Care Pooled Testing. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2406076. [PMID: 39269286 PMCID: PMC11558091 DOI: 10.1002/advs.202406076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/26/2024] [Indexed: 09/15/2024]
Abstract
Emerging diagnostic scenarios, such as population surveillance by pooled testing and on-site rapid diagnosis, highlight the importance of advanced microfluidic systems for in vitro diagnostics. However, the widespread adoption of microfluidic technology faces challenges due to the lack of standardized design paradigms, posing difficulties in managing macro-micro fluidic interfaces, reagent storage, and complex macrofluidic operations. This paper introduces a novel modular-based mesoscopic design paradigm, featuring a core "needle-plug/piston" structure with versatile variants for complex fluidic operations. These structures can be easily coupled with various microfluidic platforms to achieve truly self-contained microsystems. Incorporated into a "3D extensible" design architecture, the mesoscopic design meets the demands of function integration, macrofluid manipulations, and flexible throughputs for point-of-care nucleic acid testing. Using this approach, an ultra-sensitive nucleic acid detection system is developed with a limit of detection of ten copies of SARS-CoV-2 per mL. This system efficiently conducts large-scale pooled testing from 50 pharyngeal swabs in a tube with an uncompromised sensitivity, enabling a truly "sample-in-answer-out" microsystem with exceptional performance.
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Affiliation(s)
- Baobao Lin
- Department of Biomedical EngineeringTsinghua UniversityBeijing100084China
| | - Bao Li
- Department of Biomedical EngineeringTsinghua UniversityBeijing100084China
| | - Wu Zeng
- Department of Biomedical EngineeringTsinghua UniversityBeijing100084China
- Changping LaboratoryBeijing102206China
| | | | - Huiping Li
- Department of Biomedical EngineeringTsinghua UniversityBeijing100084China
| | - Yin Gu
- State Key Laboratory of Space MedicineChina Astronaut Research and Training CenterBeijing100094China
| | - Peng Liu
- Department of Biomedical EngineeringTsinghua UniversityBeijing100084China
- Changping LaboratoryBeijing102206China
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5
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Li S, Zhang Y, Liu J, Wang X, Qian C, Wang J, Wu L, Dai C, Yuan H, Wan C, Li J, Du W, Feng X, Li Y, Chen P, Liu BF. Fully Integrated and High-Throughput Microfluidic System for Multiplexed Point-Of-Care Testing. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2401848. [PMID: 38940626 DOI: 10.1002/smll.202401848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 06/19/2024] [Indexed: 06/29/2024]
Abstract
For every epidemic outbreak, the prevention and treatments in resource-limited areas are always out of reach. Critical to this is that high accuracy, stability, and more comprehensive analytical techniques always rely on expensive and bulky instruments and large laboratories. Here, a fully integrated and high-throughput microfluidic system is proposed for ultra-multiple point-of-care immunoassay, termed Dac system. Specifically, the Dac system only requires a handheld portable device to automatically recycle repetitive multi-step reactions including on-demand liquid releasing, dispensing, metering, collecting, oscillatory mixing, and discharging. The Dac system performs high-precision enzyme-linked immunosorbent assays for up to 17 samples or targets simultaneously on a single chip. Furthermore, reagent consumption is only 2% compared to conventional ELISA, and microbubble-accelerated reactions shorten the assay time by more than half. As a proof of concept, the multiplexed detections are achieved by detecting at least four infection targets for two samples simultaneously on a singular chip. Furthermore, the barcode-based multi-target results can rapidly distinguish between five similar cases, allowing for accurate therapeutic interventions. Compared to bulky clinical instruments, the accuracy of clinical inflammation classification is 92.38% (n = 105), with a quantitative correlation coefficient of R2 = 0.9838, while the clinical specificity is 100% and the sensitivity is 98.93%.
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Affiliation(s)
- Shunji Li
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Ying Zhang
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jingxuan Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xing Wang
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Chungen Qian
- Department of Reagent Research and Development, Shenzhen YHLO Biotech Co., Ltd., Shenzhen, 518000, China
| | - Jingjing Wang
- Department of Reagent Research and Development, Shenzhen YHLO Biotech Co., Ltd., Shenzhen, 518000, China
| | - Liqiang Wu
- Department of Reagent Research and Development, Shenzhen YHLO Biotech Co., Ltd., Shenzhen, 518000, China
| | - Chenxi Dai
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Huijuan Yuan
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Chao Wan
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jiashuo Li
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Wei Du
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xiaojun Feng
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Yiwei Li
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Peng Chen
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Bi-Feng Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
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6
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Brustoloni CJM, Khamsi PS, Kammarchedu V, Ebrahimi A. Systematic Study of Various Functionalization Steps for Ultrasensitive Detection of SARS-CoV-2 with Direct Laser-Functionalized Au-LIG Electrochemical Sensors. ACS APPLIED MATERIALS & INTERFACES 2024; 16:49041-49052. [PMID: 39231012 PMCID: PMC11479654 DOI: 10.1021/acsami.4c09571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2024]
Abstract
The 2019 coronavirus (COVID-19) pandemic impaired global health, disrupted society, and slowed the economy. Early detection of the infection using highly sensitive diagnostics is crucial in preventing the disease's spread. In this paper, we demonstrate electrochemical sensors based on laser induced graphene (LIG) functionalized directly with gold (Au) nanostructures for the detection of SARS-CoV-2 with an outstanding limit of detection (LOD) of ∼1.2 ag·mL-1. To achieve the optimum performance, we explored various functionalization parameters to elucidate their impact on the LOD, sensitivity, and linearity. Specifically, we investigated the effect of (i) gold precursor concentration, (ii) cross-linker chemistry, (iii) cross-linker and antibody incubation conditions, and (iv) antigen-sensor interaction (diffusion-dominated incubation vs pipette-mixing), as there is a lack of a systematic study of these parameters. Our benchmarking analysis highlights the critical role of the antigen-sensor interaction and cross-linker chemistry. We showed that pipette-mixing enhances sensitivity and LOD by more than 1.6- and 5.5-fold, respectively, and also enables multimodal readout compared to diffusion-dominated incubation. Moreover, the PBA/Sulfo-NHS: EDC cross-linker improves the sensitivity and LOD compared to PBASE. The sensors demonstrate excellent selectivity against other viruses, including HCoV-229E, HCoV-OC43, HCoV-NL63, and influenza H5N1. Beyond the ability to detect antigen fragments, our sensors enable the detection of antigen-coated virion mimics (which are a better representative of the real infection) down to an ultralow concentration of ∼5 particles·mL-1.
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Affiliation(s)
- Caroline Ji-Mei Brustoloni
- Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Pouya Soltan Khamsi
- Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Center for Atomically Thin Multifunctional Coatings, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Vinay Kammarchedu
- Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Center for Atomically Thin Multifunctional Coatings, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Aida Ebrahimi
- Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Center for Atomically Thin Multifunctional Coatings, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
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7
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Wasilewski T, Kamysz W, Gębicki J. AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring. BIOSENSORS 2024; 14:356. [PMID: 39056632 PMCID: PMC11274923 DOI: 10.3390/bios14070356] [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: 05/09/2024] [Revised: 06/25/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024]
Abstract
The steady progress in consumer electronics, together with improvement in microflow techniques, nanotechnology, and data processing, has led to implementation of cost-effective, user-friendly portable devices, which play the role of not only gadgets but also diagnostic tools. Moreover, numerous smart devices monitor patients' health, and some of them are applied in point-of-care (PoC) tests as a reliable source of evaluation of a patient's condition. Current diagnostic practices are still based on laboratory tests, preceded by the collection of biological samples, which are then tested in clinical conditions by trained personnel with specialistic equipment. In practice, collecting passive/active physiological and behavioral data from patients in real time and feeding them to artificial intelligence (AI) models can significantly improve the decision process regarding diagnosis and treatment procedures via the omission of conventional sampling and diagnostic procedures while also excluding the role of pathologists. A combination of conventional and novel methods of digital and traditional biomarker detection with portable, autonomous, and miniaturized devices can revolutionize medical diagnostics in the coming years. This article focuses on a comparison of traditional clinical practices with modern diagnostic techniques based on AI and machine learning (ML). The presented technologies will bypass laboratories and start being commercialized, which should lead to improvement or substitution of current diagnostic tools. Their application in PoC settings or as a consumer technology accessible to every patient appears to be a real possibility. Research in this field is expected to intensify in the coming years. Technological advancements in sensors and biosensors are anticipated to enable the continuous real-time analysis of various omics fields, fostering early disease detection and intervention strategies. The integration of AI with digital health platforms would enable predictive analysis and personalized healthcare, emphasizing the importance of interdisciplinary collaboration in related scientific fields.
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Affiliation(s)
- Tomasz Wasilewski
- Department of Inorganic Chemistry, Faculty of Pharmacy, Medical University of Gdansk, Hallera 107, 80-416 Gdansk, Poland
| | - Wojciech Kamysz
- Department of Inorganic Chemistry, Faculty of Pharmacy, Medical University of Gdansk, Hallera 107, 80-416 Gdansk, Poland
| | - Jacek Gębicki
- Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdansk, Poland;
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8
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Scandurra C, Björkström K, Caputo M, Sarcina L, Genco E, Modena F, Viola FA, Brunetti C, Kovács‐Vajna ZM, Franco CD, Haeberle L, Larizza P, Mancini MT, Österbacka R, Reeves W, Scamarcio G, Wheeler M, Caironi M, Cantatore E, Torricelli F, Esposito I, Macchia E, Torsi L. Analysis of Clinical Samples of Pancreatic Cyst's Lesions with A Multi-Analyte Bioelectronic Simot Array Benchmarked Against Ultrasensitive Chemiluminescent Immunoassay. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308141. [PMID: 38234100 PMCID: PMC11251558 DOI: 10.1002/advs.202308141] [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: 10/27/2023] [Revised: 12/30/2023] [Indexed: 01/19/2024]
Abstract
Pancreatic cancer, ranking as the third factor in cancer-related deaths, necessitates enhanced diagnostic measures through early detection. In response, SiMoT-Single-molecule with a large Transistor multiplexing array, achieving a Technology Readiness Level of 5, is proposed for a timely identification of pancreatic cancer precursor cysts and is benchmarked against the commercially available chemiluminescent immunoassay SIMOA (Single molecule array) SP-X System. A cohort of 39 samples, comprising 33 cyst fluids and 6 blood plasma specimens, undergoes detailed examination with both technologies. The SiMoT array targets oncoproteins MUC1 and CD55, and oncogene KRAS, while the SIMOA SP-X planar technology exclusively focuses on MUC1 and CD55. Employing Principal Component Analysis (PCA) for multivariate data processing, the SiMoT array demonstrates effective discrimination of malignant/pre-invasive high-grade or potentially malignant low-grade pancreatic cysts from benign non-mucinous cysts. Conversely, PCA analysis applied to SIMOA assay reveals less effective differentiation ability among the three cyst classes. Notably, SiMoT unique capability of concurrently analyzing protein and genetic markers with the threshold of one single molecule in 0.1 mL positions it as a comprehensive and reliable diagnostic tool. The electronic response generated by the SiMoT array facilitates direct digital data communication, suggesting potential applications in the development of field-deployable liquid biopsy.
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Affiliation(s)
- Cecilia Scandurra
- Dipartimento di Chimica and Centre for Colloid and Surface ScienceUniversità degli Studi di Bari Aldo MoroBari20125Italy
| | - Kim Björkström
- The Faculty of Science and EngineeringÅbo Akademi UniversityTurku20500Finland
| | - Mariapia Caputo
- Dipartimento di Farmacia‐Scienze del FarmacoUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Lucia Sarcina
- Dipartimento di Chimica and Centre for Colloid and Surface ScienceUniversità degli Studi di Bari Aldo MoroBari20125Italy
| | - Enrico Genco
- Department of Electrical EngineeringEindhoven University of TechnologyEindhoven5600 MBThe Netherlands
| | - Francesco Modena
- Center for Nano Science and TechnologyIstituto Italiano di TecnologiaVia Rubattino 81Milan20134Italy
| | - Fabrizio Antonio Viola
- Center for Nano Science and TechnologyIstituto Italiano di TecnologiaVia Rubattino 81Milan20134Italy
- Present address:
Dipartimento di Ingegneria Elettrica ed ElettronicaUniversità degli Studi di CagliariVia Marengo 3Cagliari09123Italy
| | | | - Zsolt M. Kovács‐Vajna
- Dipartimento Ingegneria dell'InformazioneUniversità degli Studi di BresciaBrescia25123Italy
| | | | - Lena Haeberle
- Institute of PathologyHeinrich‐Heine University and University Hospital of Düsseldorf40225DuesseldorfGermany
| | - Piero Larizza
- Masmec Biomed – Masmec SpA divisionModugno (BA)70026Italy
| | | | - Ronald Österbacka
- The Faculty of Science and EngineeringÅbo Akademi UniversityTurku20500Finland
| | | | - Gaetano Scamarcio
- Dipartimento Interateneo di FisicaUniversità degli Studi di Bari Aldo MoroBari70125Italy
| | | | - Mario Caironi
- Center for Nano Science and TechnologyIstituto Italiano di TecnologiaVia Rubattino 81Milan20134Italy
| | - Eugenio Cantatore
- Department of Electrical EngineeringEindhoven University of TechnologyEindhoven5600 MBThe Netherlands
| | - Fabrizio Torricelli
- Dipartimento Ingegneria dell'InformazioneUniversità degli Studi di BresciaBrescia25123Italy
| | - Irene Esposito
- Institute of PathologyHeinrich‐Heine University and University Hospital of Düsseldorf40225DuesseldorfGermany
| | - Eleonora Macchia
- The Faculty of Science and EngineeringÅbo Akademi UniversityTurku20500Finland
- Dipartimento di Farmacia‐Scienze del FarmacoUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Luisa Torsi
- Dipartimento di Chimica and Centre for Colloid and Surface ScienceUniversità degli Studi di Bari Aldo MoroBari20125Italy
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9
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Boukherroub R, Szunerits S. The Future of Nanotechnology-Driven Electrochemical and Electrical Point-of-Care Devices and Diagnostic Tests. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2024; 17:173-195. [PMID: 39018353 DOI: 10.1146/annurev-anchem-061622-012029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2024]
Abstract
Point-of-care (POC) devices have become rising stars in the biosensing field, aiming at prognosis and diagnosis of diseases with a positive impact on the patient but also on healthcare and social care systems. Putting the patient at the center of interest requires the implementation of noninvasive technologies for collecting biofluids and the development of wearable platforms with integrated artificial intelligence-based tools for improved analytical accuracy and wireless readout technologies. Many electrical and electrochemical transducer technologies have been proposed for POC-based sensing, but several necessitate further development before being widely deployable. This review focuses on recent innovations in electrochemical and electrical biosensors and their growth opportunities for nanotechnology-driven multidisciplinary approaches. With a focus on analytical aspects to pave the way for future electrical/electrochemical diagnostics tests, current limitations and drawbacks as well as directions for future developments are highlighted.
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Affiliation(s)
- Rabah Boukherroub
- Université de Lille, CNRS, Université Polytechnique Hauts-de-France, UMR 8520-IEMN, Lille, France;
| | - Sabine Szunerits
- Université de Lille, CNRS, Université Polytechnique Hauts-de-France, UMR 8520-IEMN, Lille, France;
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10
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Belleri P, Pons I Tarrés J, McCulloch I, Blom PWM, Kovács-Vajna ZM, Gkoupidenis P, Torricelli F. Unravelling the operation of organic artificial neurons for neuromorphic bioelectronics. Nat Commun 2024; 15:5350. [PMID: 38914568 PMCID: PMC11196688 DOI: 10.1038/s41467-024-49668-1] [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] [Received: 12/10/2023] [Accepted: 06/17/2024] [Indexed: 06/26/2024] Open
Abstract
Organic artificial neurons operating in liquid environments are crucial components in neuromorphic bioelectronics. However, the current understanding of these neurons is limited, hindering their rational design and development for realistic neuronal emulation in biological settings. Here we combine experiments, numerical non-linear simulations, and analytical tools to unravel the operation of organic artificial neurons. This comprehensive approach elucidates a broad spectrum of biorealistic behaviors, including firing properties, excitability, wetware operation, and biohybrid integration. The non-linear simulations are grounded in a physics-based framework, accounting for ion type and ion concentration in the electrolytic medium, organic mixed ionic-electronic parameters, and biomembrane features. The derived analytical expressions link the neurons spiking features with material and physical parameters, bridging closer the domains of artificial neurons and neuroscience. This work provides streamlined and transferable guidelines for the design, development, engineering, and optimization of organic artificial neurons, advancing next generation neuronal networks, neuromorphic electronics, and bioelectronics.
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Affiliation(s)
- Pietro Belleri
- Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy
| | - Judith Pons I Tarrés
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany
| | - Iain McCulloch
- Department of Chemistry, University of Oxford, 12 Mansfield Road, Oxford, UK
| | - Paul W M Blom
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany
| | - Zsolt M Kovács-Vajna
- Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy
| | - Paschalis Gkoupidenis
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany.
- Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Dr, Raleigh, NC, USA.
- Department of Physics, North Carolina State University, 2401 Stinson Dr, Raleigh, NC, USA.
| | - Fabrizio Torricelli
- Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy.
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11
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Song J, Liu H, Zhao Z, Lin P, Yan F. Flexible Organic Transistors for Biosensing: Devices and Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2300034. [PMID: 36853083 DOI: 10.1002/adma.202300034] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Flexible and stretchable biosensors can offer seamless and conformable biological-electronic interfaces for continuously acquiring high-fidelity signals, permitting numerous emerging applications. Organic thin film transistors (OTFTs) are ideal transducers for flexible and stretchable biosensing due to their soft nature, inherent amplification function, biocompatibility, ease of functionalization, low cost, and device diversity. In consideration of the rapid advances in flexible-OTFT-based biosensors and their broad applications, herein, a timely and comprehensive review is provided. It starts with a detailed introduction to the features of various OTFTs including organic field-effect transistors and organic electrochemical transistors, and the functionalization strategies for biosensing, with a highlight on the seminal work and up-to-date achievements. Then, the applications of flexible-OTFT-based biosensors in wearable, implantable, and portable electronics, as well as neuromorphic biointerfaces are detailed. Subsequently, special attention is paid to emerging stretchable organic transistors including planar and fibrous devices. The routes to impart stretchability, including structural engineering and material engineering, are discussed, and the implementations of stretchable organic transistors in e-skin and smart textiles are included. Finally, the remaining challenges and the future opportunities in this field are summarized.
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Affiliation(s)
- Jiajun Song
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Hong Liu
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Zeyu Zhao
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Peng Lin
- Shenzhen Key Laboratory of Special Functional Materials and Guangdong Research Center for Interfacial Engineering of Functional Materials, College of Materials Science and Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Feng Yan
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
- Research Institute of Intelligent Wearable Systems, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
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12
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Lee DH, Kim S, Woo G, Kim T, Kim YJ, Yoo H. A Mixture of Negative-, Zero-, and Positive-Differential Transconductance Switching from Tellurium/Indium Gallium Zinc Oxide Heterostructures. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38593271 DOI: 10.1021/acsami.3c19471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Conventional transistors have long emphasized signal modulation and amplification, often sidelining polarity considerations. However, the recent emergence of negative differential transconductance, characterized by a drain current decline during gate voltage sweeping, has illuminated an unconventional path in transistor technology. This phenomenon promises to simplify the implementation of ternary logic circuits and enhance energy efficiency, especially in multivalued logic applications. Our research has culminated in the development of a sophisticated mixed transconductance transistor (M-T device) founded on a precise Te and IGZO heterojunction. The M-T device exhibits a sequence of intriguing phenomena, zero differential transconductance (ZDT), positive differential transconductance (PDT), and negative differential transconductance (NDT) contingent on applied gate voltage. We clarify its operation using a three-segment equivalent circuit model and validate its viability with IGZO TFT, Te TFT, and Te/IGZO TFT components. In a concluding demonstration, the M-T device interconnected with Te TFT achieves a ternary inverter with an intermediate logic state. Remarkably, this configuration seamlessly transitions into a binary inverter when it is exposed to light.
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Affiliation(s)
- Dong Hyun Lee
- Department of Electronic Engineering, Gachon University, Seongnam, Gyeonggi 13120, Republic of Korea
| | - Somi Kim
- Department of Electronic Engineering, Gachon University, Seongnam, Gyeonggi 13120, Republic of Korea
| | - Gunhoo Woo
- SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do 16419, Republic of Korea
| | - Taesung Kim
- SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do 16419, Republic of Korea
- School of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do 16419, Republic of Korea
| | - Yeong Jae Kim
- Ceramic Total Solution Center, Korea Institute of Ceramic Engineering and Technology, Icheon 17303, Republic of Korea
| | - Hocheon Yoo
- Department of Electronic Engineering, Gachon University, Seongnam, Gyeonggi 13120, Republic of Korea
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13
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Dai C, Xiong H, He R, Zhu C, Li P, Guo M, Gou J, Mei M, Kong D, Li Q, Wee ATS, Fang X, Kong J, Liu Y, Wei D. Electro-Optical Multiclassification Platform for Minimizing Occasional Inaccuracy in Point-of-Care Biomarker Detection. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2312540. [PMID: 38288781 DOI: 10.1002/adma.202312540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/13/2024] [Indexed: 02/06/2024]
Abstract
On-site diagnostic tests that accurately identify disease biomarkers lay the foundation for self-healthcare applications. However, these tests routinely rely on single-mode signals and suffer from insufficient accuracy, especially for multiplexed point-of-care tests (POCTs) within a few minutes. Here, this work develops a dual-mode multiclassification diagnostic platform that integrates an electrochemiluminescence sensor and a field-effect transistor sensor in a microfluidic chip. The microfluidic channel guides the testing samples to flow across electro-optical sensor units, which produce dual-mode readouts by detecting infectious biomarkers of tuberculosis (TB), human rhinovirus (HRV), and group B streptococcus (GBS). Then, machine-learning classifiers generate three-dimensional (3D) hyperplanes to diagnose different diseases. Dual-mode readouts derived from distinct mechanisms enhance the anti-interference ability physically, and machine-learning-aided diagnosis in high-dimensional space reduces the occasional inaccuracy mathematically. Clinical validation studies with 501 unprocessed samples indicate that the platform has an accuracy approaching 99%, higher than the 77%-93% accuracy of rapid point-of-care testing technologies at 100% statistical power (>150 clinical tests). Moreover, the diagnosis time is 5 min without a trade-off of accuracy. This work solves the occasional inaccuracy issue of rapid on-site diagnosis, endowing POCT systems with the same accuracy as laboratory tests and holding unique prospects for complicated scenes of personalized healthcare.
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Affiliation(s)
- Changhao Dai
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Huiwen Xiong
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Rui He
- School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 73000, China
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Chenxin Zhu
- Institute of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Pintao Li
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Mingquan Guo
- Department of Laboratory Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Jian Gou
- Department of Physics, National University of Singapore, Singapore, 117542, Singapore
| | - Miaomiao Mei
- Yizheng Hospital of Traditional Chinese Medicine, Yangzhou, 211400, China
| | - Derong Kong
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Qiang Li
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Andrew Thye Shen Wee
- Department of Physics, National University of Singapore, Singapore, 117542, Singapore
| | - Xueen Fang
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Jilie Kong
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Dacheng Wei
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
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14
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Ke S, Pan Y, Jin Y, Meng J, Xiao Y, Chen S, Zhang Z, Li R, Tong F, Jiang B, Song Z, Zhu M, Ye C. Efficient Spiking Neural Networks with Biologically Similar Lithium-Ion Memristor Neurons. ACS APPLIED MATERIALS & INTERFACES 2024; 16:13989-13996. [PMID: 38441421 DOI: 10.1021/acsami.3c19261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
Benefiting from the brain-inspired event-driven feature and asynchronous sparse coding approach, spiking neural networks (SNNs) are becoming a potentially energy-efficient replacement for conventional artificial neural networks. However, neuromorphic devices used to construct SNNs persistently result in considerable energy consumption owing to the absence of sufficient biological parallels. Drawing inspiration from the transport nature of Na+ and K+ in synapses, here, a Li-based memristor (LixAlOy) was proposed to emulate the biological synapse, leveraging the similarity of Li as a homologous main group element to Na and K. The Li-based memristor exhibits ∼8 ns ultrafast operating speed, 1.91 and 0.72 linearity conductance modulation, and reproducible switching behavior, enabled by lithium vacancies forming a conductive filament mechanism. Moreover, these memristors are capable of simulating fundamental behaviors of a biological synapse, including long-term potentiation and long-term depression behaviors. Most importantly, a threshold-tunable leaky integrate-and-fire (TT-LIF) neuron is built using LixAlOy memristors, successfully integrating synaptic signals from both temporal and spatial levels and achieving an optimal threshold of SNNs. A computationally efficient TT-LIF-based SNN algorithm is also implemented for image recognition schemes, featuring a high recognition rate of 90.1% and an ultralow firing rate of 0.335%, which is 4 times lower than those of other memristor-based SNNs. Our studies reveal the ion dynamics mechanism of the LixAlOy memristor and confirm its potential in rapid switching and the construction of SNNs.
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Affiliation(s)
- Shanwu Ke
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Yanqin Pan
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Yaoyao Jin
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Jiahao Meng
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Yongyue Xiao
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Siqi Chen
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Zihao Zhang
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Ruiqi Li
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Fangjiu Tong
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Bei Jiang
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
| | - Zhitang Song
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Min Zhu
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Cong Ye
- School of Microelectronics, Key Laboratory of Intelligent Sensing System and Security, Ministry of Education, Hubei University, Wuhan 430062, China
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15
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Macchia E, Torricelli F, Caputo M, Sarcina L, Scandurra C, Bollella P, Catacchio M, Piscitelli M, Di Franco C, Scamarcio G, Torsi L. Point-Of-Care Ultra-Portable Single-Molecule Bioassays for One-Health. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2309705. [PMID: 38108547 DOI: 10.1002/adma.202309705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/20/2023] [Indexed: 12/19/2023]
Abstract
Screening asymptomatic organisms (humans, animals, plants) with a high-diagnostic accuracy using point-of-care-testing (POCT) technologies, though still visionary holds great potential. Convenient surveillance requires easy-to-use, cost-effective, ultra-portable but highly reliable, in-vitro-diagnostic devices that are ready for use wherever they are needed. Currently, there are not yet such devices available on the market, but there are a couple more promising technologies developed at readiness-level 5: the Clustered-Regularly-Interspaced-Short-Palindromic-Repeats (CRISPR) lateral-flow-strip tests and the Single-Molecule-with-a-large-Transistor (SiMoT) bioelectronic palmar devices. They both hold key features delineated by the World-Health-Organization for POCT systems and an occurrence of false-positive and false-negative errors <1-5% resulting in diagnostic-selectivity and sensitivity >95-99%, while limit-of-detections are of few markers. CRISPR-strip is a molecular assay that, can detect down to few copies of DNA/RNA markers in blood while SiMoT immunometric and molecular test can detect down to a single oligonucleotide, protein marker, or pathogens in 0.1mL of blood, saliva, and olive-sap. These technologies can prospectively enable the systematic and reliable surveillance of asymptomatic ones prior to worsening/proliferation of illnesses allowing for timely diagnosis and swift prognosis. This could establish a proactive healthcare ecosystem that results in effective treatments for all living organisms generating diffuse and well-being at efficient costs.
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Affiliation(s)
- Eleonora Macchia
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Bari, 70125, Italy
| | - Fabrizio Torricelli
- Dipartimento Ingegneria dell'Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy
| | - Mariapia Caputo
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Bari, 70125, Italy
| | - Lucia Sarcina
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - Cecilia Scandurra
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - Paolo Bollella
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - Michele Catacchio
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - Matteo Piscitelli
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, 70125, Italy
- CNR IFN, Bari, 70126, Italy
| | | | - Gaetano Scamarcio
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, 70125, Italy
- CNR IFN, Bari, 70126, Italy
| | - Luisa Torsi
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
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16
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Di Franco C, Piscitelli M, Macchia E, Scandurra C, Catacchio M, Torsi L, Scamarcio G. Kelvin probe force microscopy on patterned large-area biofunctionalized surfaces: a reliable ultrasensitive platform for biomarker detection. JOURNAL OF MATERIALS CHEMISTRY. C 2023; 12:73-79. [PMID: 38143451 PMCID: PMC10734678 DOI: 10.1039/d3tc03110a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 11/18/2023] [Indexed: 12/26/2023]
Abstract
Kelvin probe force microscopy (KPFM) allows the detection of single binding events between immunoglobulins (IgM, IgG) and their cognate antibodies (anti-IgM, anti-IgG). Here an insight into the reliability and robustness of the methodology is provided. Our method is based on imaging the surface potential shift occurring on a dense layer of ∼5 × 107 antibodies physisorbed on a 50 μm × 90 μm area when assayed with increasing concentrations of antigens in phosphate buffer saline (PBS) standard solutions, in air and at a fixed scanning location. A comprehensive investigation of the influence of the main experimental parameters that may interfere with the outcomes of KPFM immune-assay is provided, showing the robustness and reliability of our approach. The data are supported also by a thorough polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS) analysis of the physisorbed biolayer, in the spectral region of the amide I, amide II and amide A bands. Our findings demonstrate that a 10 min incubation in 500 μL PBS encompassing ≈ 30 antigens (100 zM) triggers an extended surface potential shift that involves the whole investigated area. Such a shift quickly saturates at increasing ligand concentration, showing that the developed sensing platform works as an OFF/ON detector, capable of assessing the presence of a few specific biomarkers in a given assay volume. The reliability of the developed methodology KPFM is an important asset in single molecule detections at a wide electrode interface.
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Affiliation(s)
- Cinzia Di Franco
- CNR - Institute of Photonics and Nanotechnologies, Via Amendola 173 70126 Bari Italy
| | - Matteo Piscitelli
- CNR - Institute of Photonics and Nanotechnologies, Via Amendola 173 70126 Bari Italy
- Dipartimento Interateneo di Fisica ''M. Merlin'', Università degli Studi di Bari Aldo Moro 70126 Bari Italy
| | - Eleonora Macchia
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro 70126 Bari Italy
- The Faculty of Science and Engineering, Åbo Akademi University 20500 Turku Finland
| | - Cecilia Scandurra
- Dipartimento di Chimica, Università degli Studi di Bari Aldo Moro, Via E. Orabona 4 70125 Bari Italy
| | - Michele Catacchio
- Dipartimento di Chimica, Università degli Studi di Bari Aldo Moro, Via E. Orabona 4 70125 Bari Italy
| | - Luisa Torsi
- Dipartimento di Chimica, Università degli Studi di Bari Aldo Moro, Via E. Orabona 4 70125 Bari Italy
| | - Gaetano Scamarcio
- CNR - Institute of Photonics and Nanotechnologies, Via Amendola 173 70126 Bari Italy
- Dipartimento Interateneo di Fisica ''M. Merlin'', Università degli Studi di Bari Aldo Moro 70126 Bari Italy
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17
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Carmina D, Benfenati V, Simonelli C, Rotolo A, Cardano P, Grovale N, Mangoni di S Stefano L, de Santo T, Zamboni R, Palermo V, Muccini M, De Seta F. Innovative solutions for disease management. Bioelectron Med 2023; 9:28. [PMID: 38053220 DOI: 10.1186/s42234-023-00131-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/06/2023] [Indexed: 12/07/2023] Open
Abstract
The increasing prevalence of chronic diseases is a driver for emerging big data technologies for healthcare including digital platforms for data collection, systems for active patient engagement and education, therapy specific predictive models, optimized patient pathway models. Powerful bioelectronic medicine tools for data collection, analysis and visualization allow for joint processing of large volumes of heterogeneous data, which in turn can produce new insights about patient outcomes and alternative interpretations of clinical patterns that can lead to implementation of optimized clinical decisions and clinical patient pathway by healthcare professionals.With this perspective, we identify innovative solutions for disease management and evaluate their impact on patients, payers and society, by analyzing their impact in terms of clinical outcomes (effectiveness, safety, and quality of life) and economic outcomes (cost-effectiveness, savings, and productivity).As a result, we propose a new approach based on the main pillars of innovation in the disease management area, i.e. progressive patient care models, patient-centric approaches, bioelectronics for precise medicine, and lean management that, combined with an increase in appropriate private-public-citizen-partnership, leads towards Patient-Centric Healthcare.
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Affiliation(s)
- Dafni Carmina
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy.
| | - Valentina Benfenati
- Consiglio Nazionale delle Ricerche, Istituto per la Sintesi Organica e Fotoreattività, via Gobetti 101, Bologna, 40129, Italy.
| | - Claudia Simonelli
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy
| | - Alessia Rotolo
- Consiglio Nazionale delle Ricerche, Istituto per lo Studio dei Materiali Nanostrutturati, via Gobetti 101, Bologna, 40129, Italy
| | - Paola Cardano
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy
| | - Nicoletta Grovale
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy
| | | | - Tiziana de Santo
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy
| | - Roberto Zamboni
- Consiglio Nazionale delle Ricerche, Istituto per la Sintesi Organica e Fotoreattività, via Gobetti 101, Bologna, 40129, Italy
| | - Vincenzo Palermo
- Consiglio Nazionale delle Ricerche, Istituto per la Sintesi Organica e Fotoreattività, via Gobetti 101, Bologna, 40129, Italy
| | - Michele Muccini
- Consiglio Nazionale delle Ricerche, Istituto per lo Studio dei Materiali Nanostrutturati, via Gobetti 101, Bologna, 40129, Italy
- Mister Smart Innovation S, via Gobetti 101, Bologna, 40129, Italy
| | - Francesco De Seta
- Medtronic Clinical & Regulatory Solutions - Study & Scientific Solutions, Via Aurelia 866, Roma, 00165, Italy
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18
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Janićijević Ž, Nguyen-Le TA, Alsadig A, Cela I, Žilėnaite R, Tonmoy TH, Kubeil M, Bachmann M, Baraban L. Methods gold standard in clinic millifluidics multiplexed extended gate field-effect transistor biosensor with gold nanoantennae as signal amplifiers. Biosens Bioelectron 2023; 241:115701. [PMID: 37757510 DOI: 10.1016/j.bios.2023.115701] [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: 06/20/2023] [Revised: 08/30/2023] [Accepted: 09/20/2023] [Indexed: 09/29/2023]
Abstract
We present a portable multiplexed biosensor platform based on the extended gate field-effect transistor and demonstrate its amplified response thanks to gold nanoparticle-based bioconjugates introduced as a part of the immunoassay. The platform comprises a disposable chip hosting an array of 32 extended gate electrodes, a readout module based on a single transistor operating in constant charge mode, and a multiplexer to scan sensing electrodes one-by-one. Although employing only off-the-shelf electronic components, our platform achieves sensitivities comparable to fully customized nanofabricated potentiometric sensors. In particular, it reaches a detection limit of 0.2 fM for the pure molecular assay when sensing horseradish peroxidase-linked secondary antibody (∼0.4 nM reached by standard microplate methods). Furthermore, with the gold nanoparticle bioconjugation format, we demonstrate ca. 5-fold amplification of the potentiometric response compared to a pure molecular assay, at the detection limit of 13.3 fM. Finally, we elaborate on the mechanism of this amplification and propose that nanoparticle-mediated disruption of the diffusion barrier layer is the main contributor to the potentiometric signal enhancement. These results show the great potential of our portable, sensitive, and cost-efficient biosensor for multidimensional diagnostics in the clinical and laboratory settings, including e.g., serological tests or pathogen screening.
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Affiliation(s)
- Željko Janićijević
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Trang-Anh Nguyen-Le
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Ahmed Alsadig
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Isli Cela
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Rugilė Žilėnaite
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany; Faculty of Chemistry and Geosciences, Institute of Chemistry, Vilnius University, Naugarduko g. 24, LT-03225, Vilnius, Lithuania
| | - Taufhik Hossain Tonmoy
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Manja Kubeil
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Michael Bachmann
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Larysa Baraban
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany.
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19
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Kaushal JB, Raut P, Kumar S. Organic Electronics in Biosensing: A Promising Frontier for Medical and Environmental Applications. BIOSENSORS 2023; 13:976. [PMID: 37998151 PMCID: PMC10669243 DOI: 10.3390/bios13110976] [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] [Received: 10/02/2023] [Revised: 10/30/2023] [Accepted: 11/02/2023] [Indexed: 11/25/2023]
Abstract
The promising field of organic electronics has ushered in a new era of biosensing technology, thus offering a promising frontier for applications in both medical diagnostics and environmental monitoring. This review paper provides a comprehensive overview of organic electronics' remarkable progress and potential in biosensing applications. It explores the multifaceted aspects of organic materials and devices, thereby highlighting their unique advantages, such as flexibility, biocompatibility, and low-cost fabrication. The paper delves into the diverse range of biosensors enabled by organic electronics, including electrochemical, optical, piezoelectric, and thermal sensors, thus showcasing their versatility in detecting biomolecules, pathogens, and environmental pollutants. Furthermore, integrating organic biosensors into wearable devices and the Internet of Things (IoT) ecosystem is discussed, wherein they offer real-time, remote, and personalized monitoring solutions. The review also addresses the current challenges and future prospects of organic biosensing, thus emphasizing the potential for breakthroughs in personalized medicine, environmental sustainability, and the advancement of human health and well-being.
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Affiliation(s)
- Jyoti Bala Kaushal
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198, USA; (J.B.K.); (P.R.)
| | - Pratima Raut
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198, USA; (J.B.K.); (P.R.)
| | - Sanjay Kumar
- Durham School of Architectural Engineering and Construction, Scott Campus, University of Nebraska-Lincoln, Omaha, NE 68182, USA
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20
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Gunasinghe Pattiya Arachchillage KG, Chandra S, Williams A, Rangan S, Piscitelli P, Florence L, Ghosal Gupta S, Artes Vivancos JM. A single-molecule RNA electrical biosensor for COVID-19. Biosens Bioelectron 2023; 239:115624. [PMID: 37639885 DOI: 10.1016/j.bios.2023.115624] [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: 05/16/2023] [Revised: 08/17/2023] [Accepted: 08/18/2023] [Indexed: 08/31/2023]
Abstract
The COVID-19 pandemic shows a critical need for rapid, inexpensive, and ultrasensitive early detection methods based on biomarker analysis to reduce mortality rates by containing the spread of epidemics. This can be achieved through the electrical detection of nucleic acids at the single-molecule level. In particular, the scanning tunneling microscopic-assisted break junction (STM-BJ) method can be utilized to detect individual nucleic acid molecules with high specificity and sensitivity in liquid samples. Here, we demonstrate single-molecule electrical detection of RNA coronavirus biomarkers, including those of SARS-CoV-2 as well as those of different variants and subvariants. Our target sequences include a conserved sequence in the human coronavirus family, a conserved target specific for the SARS-CoV-2 family, and specific targets at the variant and subvariant levels. Our results demonstrate that it is possible to distinguish between different variants of the COVID-19 virus using electrical conductance signals, as recently suggested by theoretical approaches. Our results pave the way for future miniaturized single-molecule electrical biosensors that could be game changers for infectious diseases and other public health applications.
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Affiliation(s)
| | - Subrata Chandra
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA
| | - Ajoke Williams
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA
| | - Srijith Rangan
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA
| | - Patrick Piscitelli
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA
| | - Lily Florence
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA
| | | | - Juan M Artes Vivancos
- Department of Chemistry, University of Massachusetts Lowell, Lowell, 01854, MA, USA.
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21
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Paradisi A, Berto M, Di Giosia M, Mazzali S, Borsari M, Marforio TD, Zerbetto F, Calvaresi M, Orieshyna A, Amdursky N, Bortolotti CA, Biscarini F. Robust Biosensor Based on Carbon Nanotubes/Protein Hybrid Electrolyte Gated Transistors. Chemistry 2023; 29:e202301704. [PMID: 37432093 DOI: 10.1002/chem.202301704] [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] [Received: 05/29/2023] [Revised: 07/06/2023] [Accepted: 07/11/2023] [Indexed: 07/12/2023]
Abstract
Semiconducting single walled carbon nanotubes (SWCNTs) are promising materials for biosensing applications with electrolyte-gated transistors (EGT). However, to be employed in EGT devices, SWCNTs often require lengthy solution-processing fabrication techniques. Here, we introduce a simple solution-based method that allows fabricating EGT devices from stable dispersions of SWCNTs/bovine serum albumin (BSA) hybrids in water. The dispersion is then deposited on a substrate allowing the formation of a SWCNTs random network as the semiconducting channel. We demonstrate that this methodology allows the fabrication of EGT devices with electric performances that allow their use in biosensing applications. We demonstrate their application for the detection of cortisol in solution, upon gate electrode functionalization with anti-cortisol antibodies. This is a robust and cost-effective methodology that sets the ground for a SWCNT/BSA-based biosensing platform that allows overcoming many limitations of standard SWCNTs biosensor fabrications.
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Affiliation(s)
- Alessandro Paradisi
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 103, 41125, Modena, Italy
| | - Marcello Berto
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 103, 41125, Modena, Italy
| | - Matteo Di Giosia
- Chemistry Department "Giacomo Ciamician", Alma Mater Studiorum University of Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Sara Mazzali
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 103, 41125, Modena, Italy
| | - Marco Borsari
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125, Modena, Italy
| | - Tainah Dorina Marforio
- Chemistry Department "Giacomo Ciamician", Alma Mater Studiorum University of Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Francesco Zerbetto
- Chemistry Department "Giacomo Ciamician", Alma Mater Studiorum University of Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Matteo Calvaresi
- Chemistry Department "Giacomo Ciamician", Alma Mater Studiorum University of Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Anna Orieshyna
- Schulich Faculty of Chemistry, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - Nadav Amdursky
- Schulich Faculty of Chemistry, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - Carlo Augusto Bortolotti
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 103, 41125, Modena, Italy
| | - Fabio Biscarini
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campi 103, 41125, Modena, Italy
- Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Via Fossato di Mortara 17-19, 44121, Ferrara, Italy
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22
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Genco E, Modena F, Sarcina L, Björkström K, Brunetti C, Caironi M, Caputo M, Demartis VM, Di Franco C, Frusconi G, Haeberle L, Larizza P, Mancini MT, Österbacka R, Reeves W, Scamarcio G, Scandurra C, Wheeler M, Cantatore E, Esposito I, Macchia E, Torricelli F, Viola FA, Torsi L. A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2304102. [PMID: 37452695 DOI: 10.1002/adma.202304102] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/18/2023]
Abstract
A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRASmut DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 × 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRASmut , MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma.
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Affiliation(s)
- Enrico Genco
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands
| | - Francesco Modena
- Center for Nano Science and Technology, Istituto Italiano di Tecnologia, Via Rubattino 81, Milan, 20134, Italy
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, 20133, Italy
| | - Lucia Sarcina
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - Kim Björkström
- The Faculty of Science and Engineering, Åbo Akademi University, Turku, 20500, Finland
| | | | - Mario Caironi
- Center for Nano Science and Technology, Istituto Italiano di Tecnologia, Via Rubattino 81, Milan, 20134, Italy
| | - Mariapia Caputo
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Bari, 70125, Italy
| | - Virginia Maria Demartis
- Dipartimento Ingegneria dell'Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy
| | | | - Giulia Frusconi
- Dipartimento Ingegneria dell'Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy
| | - Lena Haeberle
- Institute of Pathology, Heinrich-Heine University and University Hospital of Düsseldorf, 40225, Duesseldorf, Germany
| | - Piero Larizza
- Masmec Biomed - Masmec SpA division, Modugno (BA), 70026, Italy
| | | | - Ronald Österbacka
- The Faculty of Science and Engineering, Åbo Akademi University, Turku, 20500, Finland
| | | | - Gaetano Scamarcio
- CNR IFN, Bari, 70126, Italy
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, 70125, Italy
| | - Cecilia Scandurra
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
| | - May Wheeler
- FlexEnable Technology Ltd, Cambridge, CB4 0FX, UK
| | - Eugenio Cantatore
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands
| | - Irene Esposito
- Institute of Pathology, Heinrich-Heine University and University Hospital of Düsseldorf, 40225, Duesseldorf, Germany
| | - Eleonora Macchia
- The Faculty of Science and Engineering, Åbo Akademi University, Turku, 20500, Finland
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Bari, 70125, Italy
| | - Fabrizio Torricelli
- Dipartimento Ingegneria dell'Informazione, Università degli Studi di Brescia, Brescia, 25123, Italy
| | - Fabrizio Antonio Viola
- Center for Nano Science and Technology, Istituto Italiano di Tecnologia, Via Rubattino 81, Milan, 20134, Italy
| | - Luisa Torsi
- Dipartimento di Chimica and Centre for Colloid and Surface Science, Università degli Studi di Bari Aldo Moro, Bari, 20125, Italy
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23
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Madhurantakam S, Karnam JB, Muthukumar S, Prasad S. COVID severity test (CoST sensor)-An electrochemical immunosensing approach to stratify disease severity. Bioeng Transl Med 2023; 8:e10566. [PMID: 37693054 PMCID: PMC10486328 DOI: 10.1002/btm2.10566] [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: 11/22/2022] [Revised: 06/07/2023] [Accepted: 06/10/2023] [Indexed: 09/12/2023] Open
Abstract
With the evolution of the COVID-19 pandemic, there is now a need for point-of-care devices for the quantification of disease biomarkers toward disease severity assessment. Disease progression has been determined as a multifactor phenomenon and can be treated based on the host immune response within each individual. CoST is an electrochemical immunosensor point-of-care device that can determine disease severity through multiplex measurement and quantification of spike protein, nucleocapsid protein, D-dimer, and IL-2R from 100 μL of plasma samples within a few minutes. The limit of detection was found to be 3 ng/mL and 21 ng/mL for S and N proteins whereas for D-dimer and IL-2R it was 0.0006 ng/mL and 0.242 ng/mL, respectively. Cross-reactivity of all the biomarkers was studied and it was found to be <20%. Inter and intra-assay variability of the CoST sensor was less than <15% confirming its ability to detect the target biomarker in body fluids. In addition, this platform has also been tested to quantify all four biomarkers in 40 patient samples and to predict the severity index. A significant difference was observed between healthy and COVID-19 samples with a p-value of 0.0002 for D-dimer and <0.0001 for other proteins confirming the ability of the COST sensor to be used as a point of care device to assess disease severity at clinical sites. This device platform can be modified to impact a wide range of disease indications where prognostic monitoring of the host response can be critical in modulating therapy.
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Affiliation(s)
- Sasya Madhurantakam
- Department of BioengineeringThe University of Texas at DallasRichardsonTexasUSA
| | | | | | - Shalini Prasad
- Department of BioengineeringThe University of Texas at DallasRichardsonTexasUSA
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24
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Moetlhoa B, Maluleke K, Mathebula EM, Kgarosi K, Nxele SR, Lenonyane B, Mashamba-Thompson T. REASSURED diagnostics at point-of-care in sub-Saharan Africa: A scoping review. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001443. [PMID: 37276194 PMCID: PMC10241361 DOI: 10.1371/journal.pgph.0001443] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 05/12/2023] [Indexed: 06/07/2023]
Abstract
Point-of-care (POC) diagnostics that meet the REASSURED criteria are essential in combating the rapid increase and severity of global health emergencies caused by infectious diseases. However, little is known about whether the REASSURED criteria are implemented in regions known to have a high burden of infectious diseases such as sub-Saharan Africa (SSA). This scoping review maps evidence of the use of REASSURED POC diagnostic tests in SSA. The scoping review was guided by the advanced methodological framework of Arksey and O'Malley, and Levac et al. We searched the following electronic databases for relevant literature: Scopus, Dimensions, ProQuest Central, Google Scholar, and EBSCOhost (MEDLINE, CINAHL, as well as AFRICA-WIDE). Two reviewers independently screened abstracts and full-text articles using the inclusion criteria as reference. We appraised the quality of the included studies using the mixed-method appraisal tool (MMAT) version 2018. We retrieved 138 publications, comprising 134 articles and four grey literature articles. Of these, only five articles were included following abstract and full-text screening. The five included studies were all conducted in SSA. The following themes emerged from the eligible articles: quality assurance on accuracy of REASSURED POC diagnostic tests, sustainability of REASSURED POC diagnostic tests, and local infrastructure capability for delivering REASSURED POC diagnostic tests to end users. All five articles had MMAT scores between 90% and 100%. In conclusion, our scoping review revealed limited published research on REASSURED diagnostics at POC in SSA. We recommend primary studies aimed at investigating the implementation of REASSURED POC diagnostic tests in SSA.
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Affiliation(s)
- Boitumelo Moetlhoa
- Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Kuhlula Maluleke
- Faculty of Health Sciences, School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Evans M. Mathebula
- Faculty of Health Sciences, School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
- Medical and Scientific Affairs, Rapid Diagnostics, Infectious Diseases Emerging Markets, Abbot Rapid Diagnostics (Pty) Ltd, Sandton, South Africa
| | - Kabelo Kgarosi
- Faculty of Health Sciences, Department of Library Services, University of Pretoria, Pretoria, South Africa
| | | | - Bonolo Lenonyane
- Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
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25
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Arya SS, Dias SB, Jelinek HF, Hadjileontiadis LJ, Pappa AM. The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics? Biosens Bioelectron 2023; 235:115387. [PMID: 37229842 DOI: 10.1016/j.bios.2023.115387] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 04/11/2023] [Accepted: 05/10/2023] [Indexed: 05/27/2023]
Abstract
Advances in consumer electronics, alongside the fields of microfluidics and nanotechnology have brought to the fore low-cost wearable/portable smart devices. Although numerous smart devices that track digital biomarkers have been successfully translated from bench-to-bedside, only a few follow the same fate when it comes to track traditional biomarkers. Current practices still involve laboratory-based tests, followed by blood collection, conducted in a clinical setting as they require trained personnel and specialized equipment. In fact, real-time, passive/active and robust sensing of physiological and behavioural data from patients that can feed artificial intelligence (AI)-based models can significantly improve decision-making, diagnosis and treatment at the point-of-procedure, by circumventing conventional methods of sampling, and in person investigation by expert pathologists, who are scarce in developing countries. This review brings together conventional and digital biomarker sensing through portable and autonomous miniaturized devices. We first summarise the technological advances in each field vs the current clinical practices and we conclude by merging the two worlds of traditional and digital biomarkers through AI/ML technologies to improve patient diagnosis and treatment. The fundamental role, limitations and prospects of AI in realizing this potential and enhancing the existing technologies to facilitate the development and clinical translation of "point-of-care" (POC) diagnostics is finally showcased.
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Affiliation(s)
- Sagar S Arya
- Department of Biomedical Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates
| | - Sofia B Dias
- Department of Biomedical Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates; Interdisciplinary Center for Human Performance, Faculdade de Motricidade Humana, Universidade de Lisboa, Portugal.
| | - Herbert F Jelinek
- Department of Biomedical Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates; Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, P O Box 127788, Abu Dhabi, United Arab Emirates
| | - Leontios J Hadjileontiadis
- Department of Biomedical Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates; Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, P O Box 127788, Abu Dhabi, United Arab Emirates; Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR, 54124, Thessaloniki, Greece
| | - Anna-Maria Pappa
- Department of Biomedical Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates; Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, P O Box 127788, Abu Dhabi, United Arab Emirates; Department of Chemical Engineering and Biotechnology, Cambridge University, Cambridge, UK.
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26
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Taha BA, Al Mashhadany Y, Al-Jubouri Q, Rashid ARBA, Luo Y, Chen Z, Rustagi S, Chaudhary V, Arsad N. Next-generation nanophotonic-enabled biosensors for intelligent diagnosis of SARS-CoV-2 variants. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163333. [PMID: 37028663 PMCID: PMC10076079 DOI: 10.1016/j.scitotenv.2023.163333] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 04/02/2023] [Indexed: 04/15/2023]
Abstract
Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.
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Affiliation(s)
- Bakr Ahmed Taha
- Photonics Technology Laboratory, Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia.
| | - Yousif Al Mashhadany
- Department of Electrical Engineering, College of Engineering, University of Anbar, Anbar 00964, Iraq
| | - Qussay Al-Jubouri
- Department of Communication Engineering, University of Technology, Baghdad, Iraq
| | - Affa Rozana Bt Abdul Rashid
- Faculty of Science and Technology, University Sains Islam Malaysia, Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia
| | - Yunhan Luo
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Department of Optoelectronic Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632, China
| | - Zhe Chen
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University Guangzhou, 510632, China
| | - Sarvesh Rustagi
- School of Applied and Life Sciences, Uttaranchal University, Dehradun, Uttarakhand, India
| | - Vishal Chaudhary
- Department of Physics, Bhagini Nivedita College, University of Delhi, New Delhi 110045, India.
| | - Norhana Arsad
- Photonics Technology Laboratory, Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia.
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27
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Park SJ, Lee S, Lee D, Lee NE, Park JS, Hong JH, Jang JW, Kim H, Roh S, Lee G, Lee D, Cho SY, Park C, Lee DG, Lee R, Nho D, Yoon DS, Yoo YK, Lee JH. PCR-like performance of rapid test with permselective tunable nanotrap. Nat Commun 2023; 14:1520. [PMID: 36934093 PMCID: PMC10024276 DOI: 10.1038/s41467-023-37018-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 02/24/2023] [Indexed: 03/20/2023] Open
Abstract
Highly sensitive rapid testing for COVID-19 is essential for minimizing virus transmission, especially before the onset of symptoms and in asymptomatic cases. Here, we report bioengineered enrichment tools for lateral flow assays (LFAs) with enhanced sensitivity and specificity (BEETLES2), achieving enrichment of SARS-CoV-2 viruses, nucleocapsid (N) proteins and immunoglobulin G (IgG) with 3-minute operation. The limit of detection is improved up to 20-fold. We apply this method to clinical samples, including 83% with either intermediate (35%) or low viral loads (48%), collected from 62 individuals (n = 42 for positive and n = 20 for healthy controls). We observe diagnostic sensitivity, specificity, and accuracy of 88.1%, 100%, and 91.9%, respectively, compared with commercial LFAs alone achieving 14.29%, 100%, and 41.94%, respectively. BEETLES2, with permselectivity and tunability, can enrich the SARS-CoV-2 virus, N proteins, and IgG in the nasopharyngeal/oropharyngeal swab, saliva, and blood serum, enabling reliable and sensitive point-of-care testing, facilitating fast early diagnosis.
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Affiliation(s)
- Seong Jun Park
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
| | - Seungmin Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
| | - Dongtak Lee
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
| | - Na Eun Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
- Department of Biotechnology, College of Life Sciences and Biotechnology, Korea University, Seoul, 02841, Republic of Korea
| | - Jeong Soo Park
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
| | - Ji Hye Hong
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
| | - Jae Won Jang
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, Republic of Korea
| | - Hyunji Kim
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, Republic of Korea
| | - Seokbeom Roh
- Department of Biotechnology and Bioinformatics, Korea University, Sejong, 30019, Republic of Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong, 30019, Korea
| | - Gyudo Lee
- Department of Biotechnology and Bioinformatics, Korea University, Sejong, 30019, Republic of Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong, 30019, Korea
| | - Dongho Lee
- CALTH Inc., Changeop-ro 54, Seongnam, Gyeonggi, 13449, Republic of Korea
| | - Sung-Yeon Cho
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chulmin Park
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong-Gun Lee
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Raeseok Lee
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dukhee Nho
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dae Sung Yoon
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea.
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, Republic of Korea.
- Astrion Inc, Seoul, 02841, Republic of Korea.
| | - Yong Kyoung Yoo
- Department of Electronic Engineering, Catholic Kwandong University, 24, Beomil-ro 579 beon-gil, Gangneung-si, Gangwon-do, 25601, Republic of Korea.
| | - Jeong Hoon Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea.
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28
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Romagnoli A, D'Agostino M, Pavoni E, Ardiccioni C, Motta S, Crippa P, Biagetti G, Notarstefano V, Rexha J, Perta N, Barocci S, Costabile BK, Colasurdo G, Caucci S, Mencarelli D, Turchetti C, Farina M, Pierantoni L, La Teana A, Al Hadi R, Cicconardi F, Chinappi M, Trucchi E, Mancia F, Menzo S, Morozzo Della Rocca B, D'Annessa I, Di Marino D. SARS-CoV-2 multi-variant rapid detector based on graphene transistor functionalized with an engineered dimeric ACE2 receptor. NANO TODAY 2023; 48:101729. [PMID: 36536857 PMCID: PMC9750890 DOI: 10.1016/j.nantod.2022.101729] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/14/2022] [Accepted: 12/11/2022] [Indexed: 05/14/2023]
Abstract
Reliable point-of-care (POC) rapid tests are crucial to detect infection and contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The emergence of several variants of concern (VOC) can reduce binding affinity to diagnostic antibodies, limiting the efficacy of the currently adopted tests, while showing unaltered or increased affinity for the host receptor, angiotensin converting enzyme 2 (ACE2). We present a graphene field-effect transistor (gFET) biosensor design, which exploits the Spike-ACE2 interaction, the crucial step for SARS-CoV-2 infection. Extensive computational analyses show that a chimeric ACE2-Fragment crystallizable (ACE2-Fc) construct mimics the native receptor dimeric conformation. ACE2-Fc functionalized gFET allows in vitro detection of the trimeric Spike protein, outperforming functionalization with a diagnostic antibody or with the soluble ACE2 portion, resulting in a sensitivity of 20 pg/mL. Our miniaturized POC biosensor successfully detects B.1.610 (pre-VOC), Alpha, Beta, Gamma, Delta, Omicron (i.e., BA.1, BA.2, BA.4, BA.5, BA.2.75 and BQ.1) variants in isolated viruses and patient's clinical nasopharyngeal swabs. The biosensor reached a Limit Of Detection (LOD) of 65 cps/mL in swab specimens of Omicron BA.5. Our approach paves the way for a new and reusable class of highly sensitive, rapid and variant-robust SARS-CoV-2 detection systems.
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Affiliation(s)
- Alice Romagnoli
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
- New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Mattia D'Agostino
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Eleonora Pavoni
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Chiara Ardiccioni
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Stefano Motta
- Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Paolo Crippa
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Giorgio Biagetti
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Valentina Notarstefano
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Jesmina Rexha
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
| | - Nunzio Perta
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
| | - Simone Barocci
- Department of Clinical Pathology, ASUR Marche AV1, Urbino, PU, Italy
| | - Brianna K Costabile
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY 10032, USA
| | | | - Sara Caucci
- Virology Unit, Department of Biomedical Sciences and Public Health, Polytechnic University of Marche, Torrette, 60126 Ancona, Italy
| | - Davide Mencarelli
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Claudio Turchetti
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Marco Farina
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Luca Pierantoni
- Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Anna La Teana
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
- New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Richard Al Hadi
- Alcatera Inc., 1401 Westwood Blvd Suite 280, Los Angeles, CA 90024, USA
| | - Francesco Cicconardi
- School of Biological Sciences, University of Bristol, Life Sciences Building, 24 Tyndall Ave, Bristol BS8 1TQ, UK
| | - Mauro Chinappi
- Department of Industrial Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy
| | - Emiliano Trucchi
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - Filippo Mancia
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY 10032, USA
| | - Stefano Menzo
- Virology Unit, Department of Biomedical Sciences and Public Health, Polytechnic University of Marche, Torrette, 60126 Ancona, Italy
| | - Blasco Morozzo Della Rocca
- Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy
| | - Ilda D'Annessa
- Institute of Chemical Science and Technologies, SCITEC-CNR, Via Mario Bianco 9, 20131 Milan, Italy
| | - Daniele Di Marino
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
- New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
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29
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Trinh KTL. Microfluidic Biosensors for Point-of-Care Nucleic Acid Amplification Tests. BIOSENSORS 2022; 13:5. [PMID: 36671840 PMCID: PMC9855661 DOI: 10.3390/bios13010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 12/18/2022] [Indexed: 06/17/2023]
Abstract
This Special Issue of Biosensors, "Microfluidic Biosensors for Point-of-Care Nucleic Acid Amplification Tests" aims to gather original research papers and comprehensive reviews detailing novel research, fabrication methods, and applications, as well as the challenges and prospects of developing microfluidics for improved biosensing and diagnostics [...].
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Affiliation(s)
- Kieu The Loan Trinh
- Department of Industrial Environmental Engineering, Gachon University, Seongnam-si 13120, Republic of Korea
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30
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Sarcina L, Macchia E, Loconsole G, D'Attoma G, Bollella P, Catacchio M, Leonetti F, Di Franco C, Elicio V, Scamarcio G, Palazzo G, Boscia D, Saldarelli P, Torsi L. Fast and Reliable Electronic Assay of a Xylella fastidiosa Single Bacterium in Infected Plants Sap. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203900. [PMID: 36031404 PMCID: PMC9596825 DOI: 10.1002/advs.202203900] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/08/2022] [Indexed: 06/15/2023]
Abstract
Pathogens ultra-sensitive detection is vital for early diagnosis and provision of restraining actions and/or treatments. Among plant pathogens, Xylella fastidiosa is among the most threatening as it can infect hundreds of plant species worldwide with consequences on agriculture and the environment. An electrolyte-gated transistor is here demonstrated to detect X. fastidiosa at a limit-of-quantification (LOQ) of 2 ± 1 bacteria in 0.1 mL (20 colony-forming-unit per mL). The assay is carried out with a millimeter-wide gate functionalized with Xylella-capturing antibodies directly in saps recovered from naturally infected plants. The proposed platform is benchmarked against the quantitave polymerase chain reaction (qPCR) gold standard, whose LOQ turns out to be at least one order of magnitude higher. Furthermore, the assay selectivity is proven against the Paraburkholderia phytofirmans bacterium (negative-control experiment). The proposed label-free, fast (30 min), and precise (false-negatives, false-positives below 1%) electronic assay, lays the ground for an ultra-high performing immunometric point-of-care platform potentially enabling large-scale screening of asymptomatic plants.
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Affiliation(s)
- Lucia Sarcina
- Dipartimento di ChimicaUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Eleonora Macchia
- Dipartimento di Farmacia – Scienze del FarmacoUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | | | - Giusy D'Attoma
- Institute for Sustainable Plant Protection CNRBari70125Italy
| | - Paolo Bollella
- Dipartimento di ChimicaUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Michele Catacchio
- Dipartimento di ChimicaUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Francesco Leonetti
- Dipartimento di Farmacia – Scienze del FarmacoUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Cinzia Di Franco
- Istituto di Fotonica e Nanotecnologie CNRc/o Dipartimento Interateneo di FisicaUniversità degli Studi di Bari Aldo MoroBari70125Italy
| | - Vito Elicio
- Agritest SrlTecnopolisCasamassimaBA70010Italy
| | - Gaetano Scamarcio
- Istituto di Fotonica e Nanotecnologie CNRc/o Dipartimento Interateneo di FisicaUniversità degli Studi di Bari Aldo MoroBari70125Italy
- Dipartimento Interateneo di FisicaUniversità degli Studi di Bari Aldo MoroBari70125Italy
| | - Gerardo Palazzo
- Dipartimento di ChimicaUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
| | - Donato Boscia
- Institute for Sustainable Plant Protection CNRBari70125Italy
| | | | - Luisa Torsi
- Dipartimento di ChimicaUniversità degli Studi di Bari “Aldo Moro”Bari70125Italy
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