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Xiao S, Yao Y, Liao S, Xu B, Li X, Zhang Y, Zhang L, Chen Q, Tang H, Song Q, Dong M. Accurate and Convenient Lung Cancer Diagnosis through Detection of Extracellular Vesicle Membrane Proteins via Förster Resonance Energy Transfer. Nano Lett 2023; 23:8115-8125. [PMID: 37643406 PMCID: PMC10510723 DOI: 10.1021/acs.nanolett.3c02193] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/22/2023] [Indexed: 08/31/2023]
Abstract
Tumor-derived extracellular vesicles (EVs) are promising to monitor early stage cancer. Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For this, we devised an EV membrane proteins detection system (EV-MPDS) based on Förster resonance energy transfer (FRET) signals between aptamer quantum dots and AIEgen dye, which eliminated the EV extraction and purification to conveniently diagnose lung cancer. In a cohort of 80 clinical samples, this system showed enhanced accuracy (100% versus 65%) and sensitivity (100% versus 55%) in cancer diagnosis as compared to the ELISA detection method. Improved accuracy of early screening (from 96.4% to 100%) was achieved by comprehensively profiling five biomarkers using a machine learning analysis system. FRET-based tumor EV-MPDS is thus an isolation-free, low-volume (1 μL), and highly accurate approach, providing the potential to aid lung cancer diagnosis and early screening.
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Affiliation(s)
- Shuting Xiao
- State
Key Laboratory of Respiratory Disease, the First Affiliated Hospital
of Guangzhou Medical University, Guangzhou
Medical University, Guangzhou, Guangdong 510120, China
- Guangzhou
Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong, China
| | - Yi Yao
- Cancer
Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
| | - Shuilin Liao
- Guangzhou
Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong, China
- Faculty
of Innovation Engineering, Macau University
of Science and Technology, Avenida Wai Long, Taipa, Macau 999078, China
| | - Bin Xu
- Cancer
Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
| | - Xue Li
- Guangzhou
Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong, China
| | - Yuxiao Zhang
- State
Key Laboratory of Respiratory Disease, the First Affiliated Hospital
of Guangzhou Medical University, Guangzhou
Medical University, Guangzhou, Guangdong 510120, China
| | - Lei Zhang
- Guangzhou
Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong, China
| | - Qiang Chen
- MOE
Frontier Science Centre for Precision Oncology, University of Macau, Taipa, Macau SAR 999078, China
| | - Haoneng Tang
- State
Key Laboratory of Respiratory Disease, the First Affiliated Hospital
of Guangzhou Medical University, Guangzhou
Medical University, Guangzhou, Guangdong 510120, China
| | - Qibin Song
- Cancer
Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
| | - Ming Dong
- State
Key Laboratory of Respiratory Disease, the First Affiliated Hospital
of Guangzhou Medical University, Guangzhou
Medical University, Guangzhou, Guangdong 510120, China
- Guangzhou
Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong, China
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Abstract
Unpredictable natural disasters, disease outbreaks, climate change, pollution, and war constantly threaten food crop production. Smart and precision farming encourages using information or data obtained by using advanced technology (sensors, AI, and IoT) to improve decision-making in agriculture and achieve high productivity. For instance, weather prediction, nutrient information, pollutant assessment, and pathogen determination can be made with the help of new analytical and bioanalytical methods, demonstrating the potential for societal impact such as environmental, agricultural, and food science. As a rising technology, biosensors can be a potential tool to promote smart and precision farming in developing and underdeveloped countries. This review emphasizes the role of on-field, in vivo, and wearable biosensors in smart and precision farming, especially those biosensing systems that have proven with suitably complex and analytically challenging samples. The development of various agricultural biosensors in the past five years that fulfill market requirements such as portability, low cost, long-term stability, user-friendliness, rapidity, and on-site monitoring will be reviewed. The challenges and prospects for developing IoT and AI-integrated biosensors to increase crop yield and advance sustainable agriculture will be discussed. Using biosensors in smart and precision farming would ensure food security and revenue for farming communities.
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Affiliation(s)
- Jia Ling Tsong
- Department of Chemistry, Faculty of Science, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
| | - Sook Mei Khor
- Department of Chemistry, Faculty of Science, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
- Centre for Fundamental and Frontier Sciences in Nanostructure Self-Assembly, Department of Chemistry, Faculty of Science, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
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Calabria D, Lazzarini E, Pace A, Trozzi I, Zangheri M, Cinti S, Difonzo M, Valenti G, Guardigli M, Paolucci F, Mirasoli M. Smartphone-based 3D-printed electrochemiluminescence enzyme biosensor for reagentless glucose quantification in real matrices. Biosens Bioelectron 2023; 227:115146. [PMID: 36821991 DOI: 10.1016/j.bios.2023.115146] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 01/21/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023]
Abstract
Three-dimensional (3D) printed electrochemical devices are increasingly used in point-of-need and point-of-care testing. They show several advantages such as simple fabrication, low cost, fast response, and excellent selectivity and sensitivity in small sample volumes. However, there are only a few examples of analytical devices combining 3D-printed electrodes with electrochemiluminescence (ECL) detection, an electrochemical detection principle widely employed in clinical chemistry analysis. Herein, a portable, 3D-printed miniaturized ECL biosensor for glucose detection has been developed, based on the luminol/H2O2 ECL system and employing a two-electrode configuration with carbon black-doped polylactic acid (PLA) electrodes. The ECL emission is obtained by means of a 1.5V AA alkaline battery and detected using a smartphone camera, thus providing easy portability of the analytical platform. The ECL system was successfully applied for sensing H2O2 and, upon coupling the luminol/H2O2 system with the enzyme glucose oxidase, for glucose detection. The incorporation of luminol and glucose oxidase in an agarose hydrogel matrix allowed to produce ECL devices preloaded with the reagents required for the assay, so that the analysis only required sample addition. The ECL biosensor showed an excellent ability to detect glucose up to 5 mmol L-1, with a limit of detection of 60 μmol L-1. The biosensor was also used to analyse real samples (i.e., glucose saline solutions and artificial serum samples) with satisfactory results, thus suggesting its suitability for point-of-care analysis. Coupling with other oxidases could further extend the applicability of this analytical platform.
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Affiliation(s)
- Donato Calabria
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy; Interdepartmental Centre for Industrial Aerospace Research (CIRI AEROSPACE), Alma Mater Studiorum-University of Bologna, Via Baldassarre Canaccini 12, I-47121, Forlì, Italy
| | - Elisa Lazzarini
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy
| | - Andrea Pace
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy
| | - Ilaria Trozzi
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy
| | - Martina Zangheri
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy; Interdepartmental Centre for Industrial Agrofood Research (CIRI AGRO), Alma Mater Studiorum - University of Bologna, Via Quinto Bucci 336, I-47521, Cesena, Italy; Interdepartmental Centre for Industrial Research in Advanced Mechanical Engineering Applications and Materials Technology (CIRI MAM), Alma Mater Studiorum-University of Bologna, Viale Risorgimento 2, I-40136, Bologna, Italy
| | - Stefano Cinti
- Department of Pharmacy, University Naples Federico II, Via Domenico Montesano 49, I-80131, Naples, Italy; BAT Center-Interuniversity Center for Studies on Bioinspired Agro-Environmental Technology, University of Napoli "Federico II", 80055, Portici, Naples, Italy
| | - Marinella Difonzo
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy
| | - Giovanni Valenti
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy
| | - Massimo Guardigli
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy; Interdepartmental Centre for Industrial Aerospace Research (CIRI AEROSPACE), Alma Mater Studiorum-University of Bologna, Via Baldassarre Canaccini 12, I-47121, Forlì, Italy; Interdepartmental Centre for Industrial Research in Renewable Resources, Environment, Sea and Energy (CIRI FRAME), Alma Mater Studiorum - University of Bologna, Via Sant'Alberto 163, I-48123, Ravenna, Italy
| | - Francesco Paolucci
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy.
| | - Mara Mirasoli
- Department of Chemistry "Giacomo Ciamician", Alma Mater Studiorum - University of Bologna, Via Selmi 2, I-40126, Bologna, Italy; Interdepartmental Centre for Industrial Aerospace Research (CIRI AEROSPACE), Alma Mater Studiorum-University of Bologna, Via Baldassarre Canaccini 12, I-47121, Forlì, Italy; Interdepartmental Centre for Industrial Research in Renewable Resources, Environment, Sea and Energy (CIRI FRAME), Alma Mater Studiorum - University of Bologna, Via Sant'Alberto 163, I-48123, Ravenna, Italy.
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Mohan B, Neeraj, Virender, Kadiyan R, Singh K, Singh G, Kumar K, Kumar Sharma H, JL Pombeiro A. MOFs composite materials for Pb2+ ions detection in water: recent trends & advances. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
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Wu Y, Jiang T. Developments in FRET- and BRET-Based Biosensors. Micromachines (Basel) 2022; 13:mi13101789. [PMID: 36296141 PMCID: PMC9610962 DOI: 10.3390/mi13101789] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 05/25/2023]
Abstract
Resonance energy transfer technologies have achieved great success in the field of analysis. Particularly, fluorescence resonance energy transfer (FRET) and bioluminescence resonance energy transfer (BRET) provide strategies to design tools for sensing molecules and monitoring biological processes, which promote the development of biosensors. Here, we provide an overview of recent progress on FRET- and BRET-based biosensors and their roles in biomedicine, environmental applications, and synthetic biology. This review highlights FRET- and BRET-based biosensors and gives examples of their applications with their design strategies. The limitations of their applications and the future directions of their development are also discussed.
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Affiliation(s)
- Yuexin Wu
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Tianyu Jiang
- Shenzhen Research Institute of Shandong University, Shenzhen 518000, China
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Helmholtz International Lab for Anti-Infectives, Shandong University-Helmholtz Institute of Biotechnology, Shandong University, Qingdao 266237, China
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Shen Y, Nie C, Wei Y, Zheng Z, Xu ZL, Xiang P. FRET-based innovative assays for precise detection of the residual heavy metals in food and agriculture-related matrices. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2022.214676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Nahak BK, Mishra A, Preetam S, Tiwari A. Advances in Organ-on-a-Chip Materials and Devices. ACS Appl Bio Mater 2022; 5:3576-3607. [PMID: 35839513 DOI: 10.1021/acsabm.2c00041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The organ-on-a-chip (OoC) paves a way for biomedical applications ranging from preclinical to clinical translational precision. The current trends in the in vitro modeling is to reduce the complexity of human organ anatomy to the fundamental cellular microanatomy as an alternative of recreating the entire cell milieu that allows systematic analysis of medicinal absorption of compounds, metabolism, and mechanistic investigation. The OoC devices accurately represent human physiology in vitro; however, it is vital to choose the correct chip materials. The potential chip materials include inorganic, elastomeric, thermoplastic, natural, and hybrid materials. Despite the fact that polydimethylsiloxane is the most commonly utilized polymer for OoC and microphysiological systems, substitute materials have been continuously developed for its advanced applications. The evaluation of human physiological status can help to demonstrate using noninvasive OoC materials in real-time procedures. Therefore, this Review examines the materials used for fabricating OoC devices, the application-oriented pros and cons, possessions for device fabrication and biocompatibility, as well as their potential for downstream biochemical surface alteration and commercialization. The convergence of emerging approaches, such as advanced materials, artificial intelligence, machine learning, three-dimensional (3D) bioprinting, and genomics, have the potential to perform OoC technology at next generation. Thus, OoC technologies provide easy and precise methodologies in cost-effective clinical monitoring and treatment using standardized protocols, at even personalized levels. Because of the inherent utilization of the integrated materials, employing the OoC with biomedical approaches will be a promising methodology in the healthcare industry.
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Affiliation(s)
- Bishal Kumar Nahak
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Anshuman Mishra
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Subham Preetam
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Ashutosh Tiwari
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
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Honeychurch KC, Piano M. Sensors for Environmental Monitoring and Food Safety. Biosensors 2022; 12:366. [PMID: 35735513 PMCID: PMC9220911 DOI: 10.3390/bios12060366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 05/25/2022] [Indexed: 12/03/2022]
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Cebrián P, Pérez-Sienes L, Sanz-Vicente I, López-Molinero Á, de Marcos S, Galbán J. Solving Color Reproducibility between Digital Devices: A Robust Approach of Smartphones Color Management for Chemical (Bio)Sensors. Biosensors (Basel) 2022; 12:341. [PMID: 35624642 PMCID: PMC9139083 DOI: 10.3390/bios12050341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 12/02/2022]
Abstract
In the past twelve years, digital image colorimetry (DIC) on smartphones has acquired great importance as an alternative to the most common analytical techniques. This analysis method is based on fast, low-cost, and easily-accessible technology, which can provide quantitative information about an analyte through the color changes of a digital image. Despite the fact that DIC is very widespread, it is not exempt from a series of problems that are not fully resolved yet, such as variability of the measurements between smartphones, image format in which color information is stored, power distribution of the illuminant used for the measurements, among others. This article proposes a methodology for the standardization and correction of these problems using self-developed software, together with the use of a 3D printed light box. This methodology is applied to three different colorimetric analyses using different types and brands of smartphones, proving that comparable measurements between devices can be achieved. As color can be related to many target analytes, establishing this measurement methodology can lead to new control analysis applicable to diverse sectors such as alimentary, industrial, agrarian, or sanitary.
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Affiliation(s)
- Pablo Cebrián
- Analytical Biosensors Group (GBA), Analytical Chemistry Department, Faculty of Sciences, INMA, University of Zaragoza, 50009 Zaragoza, Spain; (P.C.); (I.S.-V.); (Á.L.-M.); (S.d.M.)
| | - Leticia Pérez-Sienes
- Complex Systems Group, Polytechnic University of Madrid, ETSI Agronomy, Food and Biosystems, 28040 Madrid, Spain;
| | - Isabel Sanz-Vicente
- Analytical Biosensors Group (GBA), Analytical Chemistry Department, Faculty of Sciences, INMA, University of Zaragoza, 50009 Zaragoza, Spain; (P.C.); (I.S.-V.); (Á.L.-M.); (S.d.M.)
| | - Ángel López-Molinero
- Analytical Biosensors Group (GBA), Analytical Chemistry Department, Faculty of Sciences, INMA, University of Zaragoza, 50009 Zaragoza, Spain; (P.C.); (I.S.-V.); (Á.L.-M.); (S.d.M.)
| | - Susana de Marcos
- Analytical Biosensors Group (GBA), Analytical Chemistry Department, Faculty of Sciences, INMA, University of Zaragoza, 50009 Zaragoza, Spain; (P.C.); (I.S.-V.); (Á.L.-M.); (S.d.M.)
| | - Javier Galbán
- Analytical Biosensors Group (GBA), Analytical Chemistry Department, Faculty of Sciences, INMA, University of Zaragoza, 50009 Zaragoza, Spain; (P.C.); (I.S.-V.); (Á.L.-M.); (S.d.M.)
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