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Yin J, Jia X, Li H, Zhao B, Yang Y, Ren TL. Recent Progress in Biosensors for Depression Monitoring-Advancing Personalized Treatment. BIOSENSORS 2024; 14:422. [PMID: 39329797 PMCID: PMC11430531 DOI: 10.3390/bios14090422] [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: 07/31/2024] [Revised: 08/26/2024] [Accepted: 08/28/2024] [Indexed: 09/28/2024]
Abstract
Depression is currently a major contributor to unnatural deaths and the healthcare burden globally, and a patient's battle with depression is often a long one. Because the causes, symptoms, and effects of medications are complex and highly individualized, early identification and personalized treatment of depression are key to improving treatment outcomes. The development of wearable electronics, machine learning, and other technologies in recent years has provided more possibilities for the realization of this goal. Conducting regular monitoring through biosensing technology allows for a more comprehensive and objective analysis than previous self-evaluations. This includes identifying depressive episodes, distinguishing somatization symptoms, analyzing etiology, and evaluating the effectiveness of treatment programs. This review summarizes recent research on biosensing technologies for depression. Special attention is given to technologies that can be portable or wearable, with the potential to enable patient use outside of the hospital, for long periods.
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Affiliation(s)
- Jiaju Yin
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China; (J.Y.); (B.Z.)
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xinyuan Jia
- Xingjian College, Tsinghua University, Beijing 100084, China;
| | - Haorong Li
- Weiyang College, Tsinghua University, Beijing 100084, China;
| | - Bingchen Zhao
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China; (J.Y.); (B.Z.)
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China; (J.Y.); (B.Z.)
| | - Tian-Ling Ren
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China; (J.Y.); (B.Z.)
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
- Center for Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
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Zhang H, Li X, Zhou X, Zhang Y, Zhao Y. A lipase-conjugated carbon nanotube fiber-optic SPR sensor for sensitive and specific detection of tributyrin. NANOSCALE 2024; 16:3113-3120. [PMID: 38258424 DOI: 10.1039/d3nr05129c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
As a low-density lipoprotein, tributyrin plays an essential role in food safety and human health. In this study, a novel lipase-conjugated carbon nanotube (CNT) surface plasmon resonance (SPR) fiber-optic sensor is used to specifically detect tributyrin for the first time. In this work, CNTs can be used as an amplifying material to significantly increase the sensitivity of SPR sensors due to their high refractive index and large surface area. CNTs can also be used as an enzyme carrier to provide abundant carboxyl groups for the specific binding of lipases. Covering the surface of the sensor with CNTs can not only enhance the performance of the sensor, but also provide sufficient detection sites for subsequent biomass detection, reduce the functionalization steps, and simplify the sensor preparation process. The experimental results demonstrate that the refractive index sensitivity of the traditional multimode fiber (MMF)-single mode fiber (SMF)-MMF transmissive optical fiber sensor is 1705 nm RIU-1. After covering the sensor with CNTs, the sensitivity is 2077 nm RIU-1, and the sensitivity has been improved very well. In addition, there are abundant functional groups on CNTs, which can provide abundant binding sites. Conjugating lipase on carbon nanotubes helps to achieve linear detection in the range of 0.5 mM to 4 mM tributyrin, with a sensitivity of 4.45 nm mM-1 and a detection limit of 0.34 mM, which is below the 2.26 mM detection standard and meets food safety monitoring requirements. Compared with other sensors, the optical fiber biosensor proposed in this study expands the concentration detection range of tributyrin. Furthermore, the sensor also has good stability, anti-interference performance and specificity. Therefore, the sensor proposed in this paper has good application prospects in the fields of food safety and biomedicine.
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Affiliation(s)
- Hongxin Zhang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
| | - Xuegang Li
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
- Foshan Graduate school of Innovation, Northeastern University, Foshan, Guangdong 528311, China
| | - Xue Zhou
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
- Foshan Graduate school of Innovation, Northeastern University, Foshan, Guangdong 528311, China
| | - Yanan Zhang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
| | - Yong Zhao
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
- Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao, 066004, China
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Han X, Liu W, Zu L, Wu W, Xie J, You D, Du M, Guo T. In situ surface turbidity sensor based on localized light scattering from tilted fiber Bragg gratings. OPTICS LETTERS 2024; 49:650-653. [PMID: 38300081 DOI: 10.1364/ol.512335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 12/21/2023] [Indexed: 02/02/2024]
Abstract
We propose a compact fiber-optic sensor for in situ and continuous turbidity monitoring, based on surface optical scattering of polarized evanescent waves from targeted particles. The sensor is composed of a tilted fiber Bragg grating (TFBG) packaged inside a microfluidic capillary. The transmission spectrum of the TFBG provides a fine comb of narrow cladding resonances that are highly sensitive to the turbidity due to the localized light scattering of polarized evanescent waves from the microparticles near the fiber surface (as opposed to traditional bulk/volumetric turbidity measurement). We also propose a transmission spectral area interrogation method and quantify the repeatable correlation between the surface turbidity and the optical spectral area response. We show that the maximum sensitive turbidity response is achieved when the wavelength of the sensing cladding resonance matches the size of surrounding solid particles.
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Wu X, Wang Y, Zhang J, Zhang Y, Rao X, Chen C, Liu H, Deng Y, Liao C, Smietana MJ, Chen GY, Liu L, Qu J, Wang Y. A D-Shaped Polymer Optical Fiber Surface Plasmon Resonance Biosensor for Breast Cancer Detection Applications. BIOSENSORS 2023; 14:15. [PMID: 38248392 PMCID: PMC10813458 DOI: 10.3390/bios14010015] [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: 11/21/2023] [Revised: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 01/23/2024]
Abstract
Fiber-optic biosensors have garnered significant attention and witnessed rapid development in recent years owing to their remarkable attributes such as high sensitivity, immunity to electromagnetic interference, and real-time monitoring. They have emerged as a potential tool in the realm of biomarker detection for low-concentration and small molecules. In this paper, a portable and cost-effective optical fiber biosensor based on surface plasmon resonance for the early detection of breast cancer is demonstrated. By utilizing the aptamer human epidermal growth factor receptor 2 (HER2) as a specific biomarker for breast cancer, the presence of the HER2 protein can be detected through an antigen-antibody binding technique. The detection method was accomplished by modifying a layer of HER2 aptamer on the flat surface of a gold-coated D-shaped polymer optical fiber (core/cladding diameter 120/490 μm), of which the residual thickness after side-polishing was about 245 μm, the thickness of the coated gold layer was 50 nm, and the initial wavelength in pure water was around 1200 nm. For low-concentration detection of the HER2 protein, the device exhibited a wavelength shift of ~1.37 nm with a concentration of 1 μg/mL (e.g., 5.5 nM), which corresponded to a limit of detection of ~5.28 nM. Notably, the response time of the biosensor was measured to be as fast as 5 s. The proposed biosensor exhibits the potential for early detection of HER2 protein in initial cancer serum and offers a pathway to early prevention of breast cancer.
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Affiliation(s)
- Xun Wu
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Ying Wang
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
| | - Jiaxiong Zhang
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yunfang Zhang
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Xing Rao
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Chen Chen
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Han Liu
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yubin Deng
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Changrui Liao
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
| | - Mateusz Jakub Smietana
- Division of Microsystem & Electronic Materials Technology, Institute of Microelectronics & Optoelectronics, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
| | - George Yuhui Chen
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
| | - Liwei Liu
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Junle Qu
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yiping Wang
- Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
- Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
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Li S, Li H, Lu Y, Zhou M, Jiang S, Du X, Guo C. Advanced Textile-Based Wearable Biosensors for Healthcare Monitoring. BIOSENSORS 2023; 13:909. [PMID: 37887102 PMCID: PMC10605256 DOI: 10.3390/bios13100909] [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: 08/28/2023] [Revised: 09/19/2023] [Accepted: 09/22/2023] [Indexed: 10/28/2023]
Abstract
With the innovation of wearable technology and the rapid development of biosensors, wearable biosensors based on flexible textile materials have become a hot topic. Such textile-based wearable biosensors promote the development of health monitoring, motion detection and medical management, and they have become an important support tool for human healthcare monitoring. Textile-based wearable biosensors not only non-invasively monitor various physiological indicators of the human body in real time, but they also provide accurate feedback of individual health information. This review examines the recent research progress of fabric-based wearable biosensors. Moreover, materials, detection principles and fabrication methods for textile-based wearable biosensors are introduced. In addition, the applications of biosensors in monitoring vital signs and detecting body fluids are also presented. Finally, we also discuss several challenges faced by textile-based wearable biosensors and the direction of future development.
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Affiliation(s)
- Sheng Li
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
- CCZU-ARK Institute of Carbon Materials, Nanjing 210012, China
| | - Huan Li
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
| | - Yongcai Lu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
| | - Minhao Zhou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
| | - Sai Jiang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
| | - Xiaosong Du
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China; (S.L.); (H.L.); (Y.L.); (M.Z.); (S.J.)
| | - Chang Guo
- CCZU-ARK Institute of Carbon Materials, Nanjing 210012, China
- School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, China
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Li G, Li X, Singh R, Zhang G, Zhang B, Kumar S. Slide-type waveflex biosensor based on signal enhancement technology for alpha-fetoprotein detection. OPTICS LETTERS 2023; 48:4745-4748. [PMID: 37707892 DOI: 10.1364/ol.501864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 08/20/2023] [Indexed: 09/15/2023]
Abstract
The development of signal enhancement technology in optical fiber biosensors is beneficial for the accurate measurement of low-concentration samples. Here, a localized surface plasmon resonance (LSPR)-based fiber biosensor combining a slide-type fiber structure (thus named WaveFlex Biosensor) and low-dimensional materials is proposed for alpha-fetoprotein (AFP) detection. A symmetric transverse offset splicing technology was used to fabricate the multi-mode fiber (MMF-multi-core fiber (MCF)-MMF structure. Furthermore, the MMF on one side was prepared into an S-taper, forming a slide-type fiber structure to generate more energy leakage. The LSPR signal generated by gold nanoparticles (AuNPs) was enhanced by the CeO2 NPs and C3N quantum dots functionalized on the fiber probe. The excellent performance of NPs was conducive to improving the sensitivity of the WaveFlex biosensor and enabling the rapid detection of samples. An AFP antibody was used to identify AFP micro-biomolecules in a specific manner. Based on the combination of the above two methods, the developed fiber probe was applied to detect AFP, and the sensitivity and limit of detection were 32 pm/(ng/mL) and 6.65 ng/mL, respectively. The experimental results demonstrate that the signal-enhanced AFP WaveFlex biosensor has great potential for the rapid and accurate detection of AFP.
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