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Ilchenko O, Pilhun Y, Kutsyk A, Slobodianiuk D, Goksel Y, Dumont E, Vaut L, Mazzoni C, Morelli L, Boisen S, Stergiou K, Aulin Y, Rindzevicius T, Andersen TE, Lassen M, Mundhada H, Jendresen CB, Philipsen PA, Hædersdal M, Boisen A. Optics miniaturization strategy for demanding Raman spectroscopy applications. Nat Commun 2024; 15:3049. [PMID: 38589380 PMCID: PMC11001912 DOI: 10.1038/s41467-024-47044-7] [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: 07/25/2023] [Accepted: 03/12/2024] [Indexed: 04/10/2024] Open
Abstract
Raman spectroscopy provides non-destructive, label-free quantitative studies of chemical compositions at the microscale as used on NASA's Perseverance rover on Mars. Such capabilities come at the cost of high requirements for instrumentation. Here we present a centimeter-scale miniaturization of a Raman spectrometer using cheap non-stabilized laser diodes, densely packed optics, and non-cooled small sensors. The performance is comparable with expensive bulky research-grade Raman systems. It has excellent sensitivity, low power consumption, perfect wavenumber, intensity calibration, and 7 cm-1 resolution within the 400-4000 cm-1 range using a built-in reference. High performance and versatility are demonstrated in use cases including quantification of methanol in beverages, in-vivo Raman measurements of human skin, fermentation monitoring, chemical Raman mapping at sub-micrometer resolution, quantitative SERS mapping of the anti-cancer drug methotrexate and in-vitro bacteria identification. We foresee that the miniaturization will allow realization of super-compact Raman spectrometers for integration in smartphones and medical devices, democratizing Raman technology.
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Affiliation(s)
- Oleksii Ilchenko
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark.
- Lightnovo ApS, Birkerød, Denmark.
| | - Yurii Pilhun
- Lightnovo ApS, Birkerød, Denmark
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Andrii Kutsyk
- Lightnovo ApS, Birkerød, Denmark
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
- Technical University of Denmark, Department of Energy Conversion and Storage, Kgs. Lyngby, Denmark
| | - Denys Slobodianiuk
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
- Institute of Magnetism, Kyiv, Ukraine
| | - Yaman Goksel
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Elodie Dumont
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Lukas Vaut
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Chiara Mazzoni
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Lidia Morelli
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | | | | | | | - Tomas Rindzevicius
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Thomas Emil Andersen
- Department of Clinical Microbiology, Odense University Hospital and Research Unit of Clinical Microbiology, University of Southern Denmark, Odense, Denmark
| | | | | | | | | | - Merete Hædersdal
- Department of Dermatology, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Copenhagen University, Copenhagen, Denmark
| | - Anja Boisen
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
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Wang W, Xia L, Xiao X, Li G. Recent Progress on Microfluidics Integrated with Fiber-Optic Sensors for On-Site Detection. SENSORS (BASEL, SWITZERLAND) 2024; 24:2067. [PMID: 38610279 PMCID: PMC11014287 DOI: 10.3390/s24072067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 04/14/2024]
Abstract
This review introduces a micro-integrated device of microfluidics and fiber-optic sensors for on-site detection, which can detect certain or several specific components or their amounts in different samples within a relatively short time. Fiber-optics with micron core diameters can be easily coated and functionalized, thus allowing sensors to be integrated with microfluidics to separate, enrich, and measure samples in a micro-device. Compared to traditional laboratory equipment, this integrated device exhibits natural advantages in size, speed, cost, portability, and operability, making it more suitable for on-site detection. In this review, the various optical detection methods used in this integrated device are introduced, including Raman, ultraviolet-visible, fluorescence, and surface plasmon resonance detections. It also provides a detailed overview of the on-site detection applications of this integrated device for biological analysis, food safety, and environmental monitoring. Lastly, this review addresses the prospects for the future development of microfluidics integrated with fiber-optic sensors.
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Affiliation(s)
| | | | - Xiaohua Xiao
- School of Chemistry, Sun Yat-sen University, Guangzhou 510006, China; (W.W.); (L.X.)
| | - Gongke Li
- School of Chemistry, Sun Yat-sen University, Guangzhou 510006, China; (W.W.); (L.X.)
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3
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Li K, Li H, Zhang Q, Yang D, Yang Y. Core-shell structure DA-CDs/AuNPs for the recognition of fenamidone by surface-enhanced Raman scattering. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123865. [PMID: 38219613 DOI: 10.1016/j.saa.2024.123865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/16/2024]
Abstract
In this work, a facile synthesis method for dopamine carbon dots-based Au nanoparticles (DA-CDs/AuNPs) by seed gold method was reported as the surface enhanced Raman scattering (SERS) booster. DA-CDs with rich in surface functional groups was synthesized using dopamine, citric acid and ethylenediamine as precursors by a facile hydrothermal method, and can be used as the capping agents and reducing agents for the synthesis of DA-CDs/AuNPs. Due to the electromagnetic "hot spots" effect, DA-CDs/AuNPs with core-shell structure exhibited strong SERS activity. Based on the specific interaction of DA-CDs/AuNPs and fenamidone, a detection method of fenamidone was established with a low detection limit of 0.05 μg/mL. Finally, the SERS sensor was successfully applied to the detection of fenamidone in fruit with recoveries between 90.6 % and 98.7 %. The method here proposed can be reliably applied for fenamidone detection on fruits.
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Affiliation(s)
- Kexiang Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China
| | - Hong Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China; Yunnan Agricultural University, Yunnan Province 650100, China
| | - Qian Zhang
- Yunnan Lunyang Technology Co., Ltd, Yunnan Province 650032, China
| | - Dezhi Yang
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China
| | - Yaling Yang
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China.
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Xiao J, Chen Y, Xu T, Zhang X. Hand-held Raman spectrometer-based flexible plasmonic biosensor for label-free multiplex urinalysis. Talanta 2024; 266:124966. [PMID: 37499361 DOI: 10.1016/j.talanta.2023.124966] [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: 04/11/2023] [Revised: 07/04/2023] [Accepted: 07/18/2023] [Indexed: 07/29/2023]
Abstract
Urinalysis is an effective strategy to non-invasively evaluate human health, and surface-enhanced Raman scattering (SERS) may be a powerful technique for use in detecting analytes in urine. Herein, we report a wearable diaper sensor based on a handheld Raman spectrometer for use in the simple, label-free identification of biomolecules (urea, creatinine, and bilirubin) in urine. The raspberry-shaped Au substrate formed on the surface of an Si wafer provides plasmonic enhancement of the SERS signals, with an excellent uniformity and stability. The SERS sensor combines the advantages of flexibility, portability, and multifunctional detection and may be used in identifying multiple analytes in urine. The sensor exhibits high sensitivities in detecting urea, creatinine, and bilirubin, with respective detection limits of 4.17 × 10-3 M, 5.90 × 10-6 M, and 1.38 × 10-7 M (signal-to-noise ratio = 3). Furthermore, we used the wearable diaper sensor to monitor biomolecules at the diagnostic threshold, facilitating non-invasive diagnosis and medical monitoring of disease-related biomarkers.
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Affiliation(s)
- Jingyu Xiao
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China
| | - Yanxia Chen
- Beijing Key Laboratory for Sensor, Beijing Information Science and Technology University, Beijing, 100101, China
| | - Tailin Xu
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
| | - Xueji Zhang
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
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5
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Zhou QQ, Guo J, Wang Z, Li J, Chen M, Xu Q, Zhu L, Xu Q, Wang Q, Pan H, Pan J, Zhu Y, Song M, Liu X, Wang J, Zhang Z, Zhang L, Wang Y, Cai H, Chen X, Lu G. Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology. J Adv Res 2023:S2090-1232(23)00377-6. [PMID: 38072311 DOI: 10.1016/j.jare.2023.12.002] [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: 08/04/2023] [Revised: 11/29/2023] [Accepted: 12/01/2023] [Indexed: 02/13/2024] Open
Abstract
INTRODUCTION Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. OBJECTIVE To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. METHODS We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. RESULTS The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level. CONCLUSIONS This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.
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Affiliation(s)
- Qing-Qing Zhou
- Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing, China; Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Jingxing Guo
- School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan, China.
| | - Ziyang Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China; Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Jianrui Li
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meng Chen
- Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Qiang Xu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Lijun Zhu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qing Xu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qiang Wang
- Department of Neurosurgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Hao Pan
- Department of Neurosurgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jing Pan
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yong Zhu
- School of Science, China Pharmaceutical University, Nanjing, China
| | - Ming Song
- Department of Mathmatical Sciences, The University of Texas at Dallas, Richardson, USA
| | - Xiaoxue Liu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jiandong Wang
- Department of Pathology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhiqiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Longjiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yiqing Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China
| | - Huiming Cai
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China; Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Xiaoyuan Chen
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore; Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Guangming Lu
- Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing, China; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China.
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6
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Zhang D, Fan Y, Sun X, Wei X, Lin Z, Zhang X, Shi J, Battino M, Gong Y, Shi B, Zou X. SERS determination of hydroxy-α-sanshool in spicy hotpot seasoning: The strategy to restrain the interference of capsaicin and its mechanism. Food Chem 2023; 413:135644. [PMID: 36773357 DOI: 10.1016/j.foodchem.2023.135644] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/01/2023] [Accepted: 02/03/2023] [Indexed: 02/10/2023]
Abstract
Hydroxy-α-sanshool (α-SOH) is the principal ingredient responsible for the numbing sensation in spicy hotpot. However, utilizing surface-enhanced Raman scattering (SERS) to analyze the α-SOH in hotpot seasoning is challenging due to the significant interference of capsaicin (CAP). Therefore, two schemes were proposed to address CAP interference in hotpot seasoning, namely laccase-catalyzed conversion and metal-organic framework (MOF) interaction. Among them, Fe-BTC MOF exhibited significant anti-interference effect and the underlying mechanism is elucidated. The motion of CAP aromatic ring was constrained by steric hindrance and electrostatic interactions of Fe-BTC. Additionally, the interaction between CAP aromatic ring and conjugated triene group in α-SOH was quenched, enhancing the α-SOH SERS signal. The proposed method had a significant anti-interference effect on α-SOH quantification in the presence of CAP, significantly enhancing the α-SOH SERS signal in a range of 0.85 to 4.00 × 107. The linearity and reproducibility of the proposed hotpot seasoning testing method were also validated.
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Affiliation(s)
- Di Zhang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Yushan Fan
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Xiaoxia Sun
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Xiaoou Wei
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Zitao Lin
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Xinai Zhang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Jiyong Shi
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Maurizio Battino
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; International Research Center for Food Nutrition and Safety, Jiangsu University, Zhenjiang 212013, China; Department of Clinical Sciences, Faculty of Medicine, Polytechnic University of Marche, Ancona, Italy
| | - Yunyun Gong
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Bolin Shi
- Food and Agriculture Standardization Institute, China National Institute of Standardization, Beijing 102200, China
| | - Xiaobo Zou
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
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7
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Wu L, Tang X, Wu T, Zeng W, Zhu X, Hu B, Zhang S. A review on current progress of Raman-based techniques in food safety: From normal Raman spectroscopy to SESORS. Food Res Int 2023; 169:112944. [PMID: 37254368 DOI: 10.1016/j.foodres.2023.112944] [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: 01/27/2023] [Revised: 04/27/2023] [Accepted: 05/02/2023] [Indexed: 06/01/2023]
Abstract
Frequently occurrence of food safety incidents has induced global concern over food safety. To ensure food quality and safety, an increasing number of rapid and sensitive analytical methods have been developed for analysis of all kinds of food composition and contaminants. As one of the high-profile analytical techniques, Raman spectroscopy has been widely applied in food analysis with simple, rapid, sensitive, and nondestructive detection performance. Research on Raman techniques is a direction of great interest to many fields, especially in food safety. Hence, it is crucial to gain insight into recent advances on the use of Raman-based techniques in food safety applications. In this review, we introduce Raman techniques from normal Raman spectroscopy to developed ones (e.g., surface enhanced Raman scattering (SERS), spatially offset Raman spectroscopy (SORS), surface-enhanced spatially offset Raman spectroscopy (SESORS)), in view of their history and development, principles, design, and applications. In addition, future challenges and trends of these techniques are discussed regarding to food safety.
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Affiliation(s)
- Long Wu
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, PR China; College of Bioengineering and Food, Hubei University of Technology, Wuhan 430068, PR China.
| | - Xuemei Tang
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, PR China
| | - Ting Wu
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, PR China
| | - Wei Zeng
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, PR China
| | - Xiangwei Zhu
- College of Bioengineering and Food, Hubei University of Technology, Wuhan 430068, PR China
| | - Bing Hu
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, School of Life Sciences, Dalian Minzu University, Dalian 116600, PR China
| | - Sihang Zhang
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, PR China
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8
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Closed-loop Control Systems for Pumps used in Portable Analytical Systems. J Chromatogr A 2023; 1695:463931. [PMID: 37011525 DOI: 10.1016/j.chroma.2023.463931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/27/2023] [Accepted: 03/14/2023] [Indexed: 03/17/2023]
Abstract
The demand for accurate control of the flowrate/pressure in chemical analytical systems has given rise to the adoption of mechatronic approaches in analytical instruments. A mechatronic device is a synergistic system which combines mechanical, electronic, computer and control components. In the development of portable analytical devices, considering the instrument as a mechatronic system can be useful to mitigate compromises made to decrease space, weight, or power consumption. Fluid handling is important for reliability, however, commonly utilized platforms such as syringe and peristaltic pumps are typically characterized by flow/pressure fluctuations and slow responses. Closed loop control systems have been used effectively to decrease the difference between desired and realized fluidic output. This review discusses the way control systems have been implemented for enhanced fluidic control, categorized by pump type. Advanced control strategies used to enhance the transient and the steady state responses are discussed, along with examples of their implementation in portable analytical systems. The review is concluded with the outlook that the challenge in adequately expressing the complexity and dynamics of the fluidic network as a mathematical model has yielded a trend towards the adoption of experimentally informed models and machine learning approaches.
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9
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McDonnell C, Albarghouthi FM, Selhorst R, Kelley-Loughnane N, Franklin AD, Rao R. Aerosol Jet Printed Surface-Enhanced Raman Substrates: Application for High-Sensitivity Detection of Perfluoroalkyl Substances. ACS OMEGA 2023; 8:1597-1605. [PMID: 36643551 PMCID: PMC9835780 DOI: 10.1021/acsomega.2c07134] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 11/17/2022] [Indexed: 05/06/2023]
Abstract
Printing technologies offer an attractive means for producing low-cost surface-enhanced Raman spectroscopy (SERS) substrates with high-throughput methods. The development of these substrates is especially important for field-deployable detection of environmental contaminants. Toward this end, we demonstrate SERS-based substrates fabricated through aerosol jet printing of silver nanoparticles and graphene inks on Kapton films. Our printed arrays exhibited measurable intensities for fluorescein and rhodamine dyes down to concentrations of 10-7 M, with the highest SERS intensities obtained for four print passes of Ag nanoparticles. The substrates also exhibited an excellent shelf life, with little reduction in fluorescein intensities after 9 months of shelf storage. We also demonstrated the capability of our substrates to sense perfluoroalkyl substances (PFAS), the so-called forever chemicals that resist degradation due to their strong C-F bonds and persist in the environment. Interestingly, the addition of graphene to the Ag nanoparticles greatly enhanced the SERS intensity of the perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) molecules under basic conditions (pH ∼ 9) compared to that of fluorescein and rhodamine. We were able to successfully detect SERS spectra from nano- and picomolar (∼0.4 ppt) concentrations of PFOA and PFOS, respectively, demonstrating the viability of deploying our SERS sensors in the environment for the ultrasensitive detection of contaminants.
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Affiliation(s)
- Colleen McDonnell
- Materials
and Manufacturing Directorate, Air Force
Research Laboratory, WPAFB, Ohio 45433, United States
- UES
Inc., Dayton, Ohio 45433, United States
- Department
of Biology, University of Dayton, Dayton, Ohio 46469, United States
| | - Faris M. Albarghouthi
- Department
of Electrical & Computer Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Ryan Selhorst
- Materials
and Manufacturing Directorate, Air Force
Research Laboratory, WPAFB, Ohio 45433, United States
- UES
Inc., Dayton, Ohio 45433, United States
| | - Nancy Kelley-Loughnane
- Materials
and Manufacturing Directorate, Air Force
Research Laboratory, WPAFB, Ohio 45433, United States
| | - Aaron D. Franklin
- Department
of Electrical & Computer Engineering, Duke University, Durham, North Carolina 27708, United States
- Department
of Chemistry, Duke University, Durham, North Carolina 27708, United States
| | - Rahul Rao
- Materials
and Manufacturing Directorate, Air Force
Research Laboratory, WPAFB, Ohio 45433, United States
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10
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Li R, Wang Z, Zhang Z, Sun X, Hu Y, Wang H, Chen K, Liu Q, Chen M, Chen X. Deep Learning-Based Multicapturer SERS Platform on Plasmonic Nanocube Metasurfaces for Multiplex Detection of Organophosphorus Pesticides in Environmental Water. Anal Chem 2022; 94:16006-16014. [PMID: 36345908 DOI: 10.1021/acs.analchem.2c02973] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In situ rapid detection of contaminants in environmental water is crucial for protecting the ecological environment and human health; however, it is always hindered by the complexity of sample matrices, trace content, and unknown species. Herein, we demonstrate a deep learning-based multicapturer surface-enhanced Raman scattering (SERS) platform on plasmonic nanocube metasurfaces for multiplex determination of organophosphorus pesticides (OPPs) residues. Poly(vinylpyrrolidone), 4-mercaptobenzoic acid, and l-cysteine are assembled on Ag nanocubes (AgNCs) and act as capturers to chemically define OPPs. Meanwhile, the OPPs-captured AgNCs efficiently close the interparticle distance and generate plasmonic metasurfaces, guaranteeing ultrasensitive and reproducible SERS analysis. Furthermore, by strategically combining all capturer-OPP SERS spectra, comprehensive "combined-SERS spectra" are reconstructed to enhance spectral variations of each OPP. Based on the combined-SERS spectra, a deep learning model is trained to predict OPPs, which significantly improve the qualitative and quantitative analysis accuracy. We successfully identified multiple OPPs in farmland, river, and fishpond water using this strategy. The whole detection procedure requires only 30 min, including sampling, SERS measurements, and deep learning analyses. This combination of a multicapturer SERS platform with the deep learning algorithm creates a rapid and reliable analytical strategy for multiplex detection of target molecules, providing a potential paradigm shift for environment-related research.
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Affiliation(s)
- Ruili Li
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Zi Wang
- School of Life Sciences, Central South University, Changsha 410013, China
| | - Zhipeng Zhang
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Xiaotong Sun
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Yuyang Hu
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Haoyang Wang
- School of Life Sciences, Central South University, Changsha 410013, China
| | - Kecen Chen
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Qi Liu
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Miao Chen
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
- School of Life Sciences, Central South University, Changsha 410013, China
| | - Xiaoqing Chen
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
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Saviñon-Flores AI, Saviñon-Flores F, Trejo G, Méndez E, Ţălu Ş, González-Fuentes MA, Méndez-Albores A. A review of cardiac troponin I detection by surface enhanced Raman spectroscopy: Under the spotlight of point-of-care testing. Front Chem 2022; 10:1017305. [PMID: 36311415 PMCID: PMC9608872 DOI: 10.3389/fchem.2022.1017305] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/29/2022] [Indexed: 11/29/2022] Open
Abstract
Cardiac troponin I (cTnI) is a biomarker widely related to acute myocardial infarction (AMI), one of the leading causes of death around the world. Point-of-care testing (POCT) of cTnI not only demands a short turnaround time for its detection but the highest accuracy levels to set expeditious and adequate clinical decisions. The analytical technique Surface-enhanced Raman spectroscopy (SERS) possesses several properties that tailor to the POCT format, such as its flexibility to couple with rapid assay platforms like microfluidics and paper-based immunoassays. Here, we analyze the strategies used for the detection of cTnI by SERS considering POCT requirements. From the detection ranges reported in the reviewed literature, we suggest the diseases other than AMI that could be diagnosed with this technique. For this, a section with information about cardiac and non-cardiac diseases with cTnI release, including their release kinetics or cut-off values are presented. Likewise, POCT features, the use of SERS as a POCT technique, and the biochemistry of cTnI are discussed. The information provided in this review allowed the identification of strengths and lacks of the available SERS-based point-of-care tests for cTnI and the disclosing of requirements for future assays design.
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Affiliation(s)
- Anel I. Saviñon-Flores
- Centro de Química-ICUAP- Posgrado en Ciencias Ambientales, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | | | - G. Trejo
- Laboratory of Composite Materials and Functional Coatings, Center for Research and Technological Development in Electrochemistry (CIDETEQ), Querétaro, Mexico
| | - Erika Méndez
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Ştefan Ţălu
- Technical University of Cluj-Napoca, The Directorate of Research, Development and Innovation Management (DMCDI), Cluj-Napoca, Romania
| | - Miguel A. González-Fuentes
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
- *Correspondence: Miguel A. González-Fuentes, ; Alia Méndez-Albores,
| | - Alia Méndez-Albores
- Centro de Química-ICUAP- Posgrado en Ciencias Ambientales, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
- *Correspondence: Miguel A. González-Fuentes, ; Alia Méndez-Albores,
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12
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Shaban SM, Byeok Jo S, Hafez E, Ho Cho J, Kim DH. A comprehensive overview on alkaline phosphatase targeting and reporting assays. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2022.214567] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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13
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A High-Detection-Efficiency Optoelectronic Device for Trace Cadmium Detection. SENSORS 2022; 22:s22155630. [PMID: 35957187 PMCID: PMC9371226 DOI: 10.3390/s22155630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 12/10/2022]
Abstract
Cadmium (Cd) pollution in soil is a serious threat to food security and human health, while, currently, the most widely used detection methods cannot accurately reflect the content of heavy metals in soil. Soil heavy metal detection combined with microelectronic sensors has become an important means of environmental heavy metal pollution prevention and control. X-ray Fluorescence spectrometry (XRF) can capture the excitation spectrum of metal elements, which is often used to detect Cd (II). However, due to the lack of high-performance optoelectronic devices, the analysis accuracy of the system cannot meet the requirements. Therefore, this study proposes a high-detection-efficiency photodiode (HDEPD) which can effectively improve the detection accuracy of the analyzer. The HDEPD is manufactured based on a 0.18 μm standard complementary metal-oxide-semiconductor (CMOS) process. The volt-ampere curve, spectral response and noise characteristics of the device are obtained by constructing a test circuit combined with a spectral detection system. The test results show that the threshold voltage of HDEPD is 12.15 V. When the excess bias voltage increases from 1 V to 3 V, the spectral response peak of the device appears at 500 nm, and the photon detection probability (PDP) increases from 41.7% to 52.8%. The dark count rate (DCR) is 31.9 Hz/μm2 at a 3 V excess bias voltage. Since the excitation spectrum peak of Cd (II) is between 500 nm and 600 nm, the wavelength response range of HDEPD fully meets the detection requirements of Cd (II).
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14
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Umapathi R, Rani GM, Kim E, Park S, Cho, Y, Huh YS. Sowing kernels for food safety: Importance of rapid on‐site detction of pesticide residues in agricultural foods. FOOD FRONTIERS 2022. [DOI: 10.1002/fft2.166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Reddicherla Umapathi
- NanoBio High‐Tech Materials Research Center, Department of Biological Engineering Inha University Incheon Republic of Korea
| | - Gokana Mohana Rani
- Department of Organic Chemistry Sri Padmavati Mahila Visvavidyalayam Andhra Pradesh India
- Department of Materials Science and Engineering National Taiwan University of Science and Technology Taiwan
| | - Eunsu Kim
- NanoBio High‐Tech Materials Research Center, Department of Biological Engineering Inha University Incheon Republic of Korea
| | - So‐Young Park
- NanoBio High‐Tech Materials Research Center, Department of Biological Engineering Inha University Incheon Republic of Korea
| | - Youngjin Cho,
- Food Safety and Distribution Research Group Korea Food Research Institute Wanju Republic of Korea
| | - Yun Suk Huh
- NanoBio High‐Tech Materials Research Center, Department of Biological Engineering Inha University Incheon Republic of Korea
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15
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Establishment of the thin-layer chromatography-surface-enhanced Raman spectroscopy and chemometrics method for simultaneous identification of eleven illegal drugs in anti-rheumatic health food. FOOD BIOSCI 2022. [DOI: 10.1016/j.fbio.2022.101842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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16
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Duan C, Li J, Zhang Y, Ding K, Geng X, Guan Y. Portable instruments for on-site analysis of environmental samples. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116653] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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