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Ma S, Ding P, Zhou Z, Jin H, Li X, Li Y. Terahertz Radiation Modulates Neuronal Morphology and Dynamics Properties. Brain Sci 2024; 14:279. [PMID: 38539667 PMCID: PMC10968323 DOI: 10.3390/brainsci14030279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/06/2024] [Accepted: 03/11/2024] [Indexed: 11/11/2024] Open
Abstract
Terahertz radiation falls within the spectrum of hydrogen bonding, molecular rotation, and vibration, as well as van der Waals forces, indicating that many biological macromolecules exhibit a strong absorption and resonance in this frequency band. Research has shown that the terahertz radiation of specific frequencies and energies can mediate changes in cellular morphology and function by exciting nonlinear resonance effects in proteins. However, current studies have mainly focused on the cellular level and lack systematic studies on multiple levels. Moreover, the mechanism and law of interaction between terahertz radiation and neurons are still unclear. Therefore, this paper analyzes the mechanisms by which terahertz radiation modulates the nervous system, and it analyzes and discusses the methods by which terahertz radiation modulates neurons. In addition, this paper reviews the laws of terahertz radiation's influence on neuronal morphology and kinetic properties and discusses them in detail in terms of terahertz radiation frequency, energy, and time. In the future, the safety of the terahertz radiation system should be considered first to construct the safety criterion of terahertz modulation, and the spatial resolution of the terahertz radiation system should be improved. In addition, the systematic improvement of the laws and mechanisms of terahertz modulation of the nervous system on multiple levels is the key to applying terahertz waves to neuroscience. This paper can provide a platform for researchers to understand the mechanism of the terahertz-nervous system interaction, its current status, and future research directions.
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Affiliation(s)
- Shaoqing Ma
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; (S.M.); (P.D.); (Z.Z.)
- College of Engineering, Hebei Normal University, Shijiazhuang 050024, China;
- Hebei Key Laboratory of Information Transmission and Signal Processing, Qinhuangdao 066004, China
| | - Peng Ding
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; (S.M.); (P.D.); (Z.Z.)
- Hebei Key Laboratory of Information Transmission and Signal Processing, Qinhuangdao 066004, China
| | - Zhengxuan Zhou
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; (S.M.); (P.D.); (Z.Z.)
- Hebei Key Laboratory of Information Transmission and Signal Processing, Qinhuangdao 066004, China
| | - Huilong Jin
- College of Engineering, Hebei Normal University, Shijiazhuang 050024, China;
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yingwei Li
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; (S.M.); (P.D.); (Z.Z.)
- Hebei Key Laboratory of Information Transmission and Signal Processing, Qinhuangdao 066004, China
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Vasta S, Figorilli S, Ortenzi L, Violino S, Costa C, Moscovini L, Tocci F, Pallottino F, Assirelli A, Saviane A, Cappellozza S. Automated Prototype for Bombyx mori Cocoon Sorting Attempts to Improve Silk Quality and Production Efficiency through Multi-Step Approach and Machine Learning Algorithms. SENSORS (BASEL, SWITZERLAND) 2023; 23:868. [PMID: 36679667 PMCID: PMC9862640 DOI: 10.3390/s23020868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/27/2022] [Accepted: 01/07/2023] [Indexed: 06/17/2023]
Abstract
Cocoon sorting is one of the most labor-demanding activities required both at the end of the agricultural production and before the industrial reeling process to obtain an excellent silk quality. In view of the possible relaunch of European sericulture, the automatization of this production step is mandatory both to reduce silk costs and to standardize fiber quality. The described research starts from this criticality in silk production (the manual labor required to divide cocoons into different quality classes) to identify amelioration solutions. To this aim, the automation of this activity was proposed, and a first prototype was designed and built. This machinery is based on the use of three cameras and imaging algorithms identifying the shape and size of the cocoons and outside stains, a custom-made light sensor and an AI model to discard dead cocoons. The current efficiency of the machine is about 80 cocoons per minute. In general, the amelioration obtained through this research involves both the application of traditional sensors/techniques to an unusual product and the design of a dedicated sensor for the identification of dead/alive pupae inside the silk cocoons. A general picture of the overall efficiency of the new cocoon-sorting prototype is also outlined.
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Affiliation(s)
- Simone Vasta
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Simone Figorilli
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Luciano Ortenzi
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
- Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University of Viterbo, 01100 Viterbo, Italy
| | - Simona Violino
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Corrado Costa
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Lavinia Moscovini
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Francesco Tocci
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Federico Pallottino
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Alberto Assirelli
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy
| | - Alessio Saviane
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Agricoltura e Ambiente, Laboratorio di Gelsibachicoltura, 35143 Padua, Italy
| | - Silvia Cappellozza
- Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Agricoltura e Ambiente, Laboratorio di Gelsibachicoltura, 35143 Padua, Italy
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Shi J, Guo Z, Chen H, Xiao Z, Bai H, Li X, Niu P, Yao J. Artificial Intelligence-Assisted Terahertz Imaging for Rapid and Label-Free Identification of Efficient Light Formula in Laser Therapy. BIOSENSORS 2022; 12:826. [PMID: 36290963 PMCID: PMC9599775 DOI: 10.3390/bios12100826] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/28/2022] [Accepted: 10/02/2022] [Indexed: 06/16/2023]
Abstract
Photodynamic therapy (PDT) is considered a promising noninvasive therapeutic strategy in biomedicine, especially by utilizing low-level laser therapy (LLLT) in visible and near-infrared spectra to trigger biological responses. The major challenge of PDT in applications is the complicated and time-consuming biological methodological measurements in identification of light formulas for different diseases. Here, we demonstrate a rapid and label-free identification method based on artificial intelligence (AI)-assisted terahertz imaging for efficient light formulas in LLLT of acute lung injury (ALI). The gray histogram of terahertz images is developed as the biophysical characteristics to identify the therapeutic effect. Label-free terahertz imaging is sequentially performed using rapid super-resolution imaging reconstruction and automatic identification algorithm based on a voting classifier. The results indicate that the therapeutic effect of LLLT with different light wavelengths and irradiation times for ALI can be identified using this method with a high accuracy of 91.22% in 33 s, which is more than 400 times faster than the biological methodology and more than 200 times faster than the scanning terahertz imaging technology. It may serve as a new tool for the development and application of PDT.
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Affiliation(s)
- Jia Shi
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
- Key Laboratory of Opto-Electronics Information Technology (Ministry of Education), School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, China
| | - Zekang Guo
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Hongli Chen
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Zhitao Xiao
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Hua Bai
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Xiuyan Li
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Pingjuan Niu
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Jianquan Yao
- Key Laboratory of Opto-Electronics Information Technology (Ministry of Education), School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, China
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Li P, Liu S, Chen X, Geng C, Wu X. Spintronic terahertz emission with manipulated polarization (STEMP). FRONTIERS OF OPTOELECTRONICS 2022; 15:12. [PMID: 36637604 PMCID: PMC9756272 DOI: 10.1007/s12200-022-00011-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 01/11/2022] [Indexed: 06/17/2023]
Abstract
Highly efficient generation and arbitrary manipulation of spin-polarized terahertz (THz) radiation will enable chiral lightwave driven quantum nonequilibrium state regulation, induce new electronic structures, consequently provide a powerful experimental tool for investigation of nonlinear THz optics and extreme THz science and applications. THz circular dichromic spectroscopy, ultrafast electron bunch manipulation, as well as THz imaging, sensing, and telecommunication, also need chiral THz waves. Here we review optical generation of circularly-polarized THz radiation but focus on recently emerged polarization tunable spintronic THz emission techniques, which possess many advantages of ultra-broadband, high efficiency, low cost, easy for integration and so on. We believe that chiral THz sources based on the combination of electron spin, ultrafast optical techniques and material structure engineering will accelerate the development of THz science and applications.
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Affiliation(s)
- Peiyan Li
- School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China
| | - Shaojie Liu
- School of Cyber Science and Technology, Beihang University, Beijing, 100191, China
| | - Xinhou Chen
- School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China
| | - Chunyan Geng
- School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China
| | - Xiaojun Wu
- School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China.
- School of Cyber Science and Technology, Beihang University, Beijing, 100191, China.
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
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Cai J, Guang M, Zhou J, Qu Y, Xu H, Sun Y, Xiong H, Liu S, Chen X, Jin J, Wu X. Dental caries diagnosis using terahertz spectroscopy and birefringence. OPTICS EXPRESS 2022; 30:13134-13147. [PMID: 35472935 DOI: 10.1364/oe.452769] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/28/2022] [Indexed: 06/14/2023]
Abstract
Dental caries is a widespread chronic infectious disease which may induce a series of oral and general problems if untreated. As a result, early diagnosis and follow-up following radiation-free dental caries therapy are critical. Terahertz (THz) waves with highly penetrating and non-ionizing properties are ideally suited for dental caries diagnosis, however related research in this area is still in its infancy. Here, we successfully observe the existence of THz birefringence phenomenon in enamel and demonstrate the feasibility of utilizing THz spectroscopy and birefringence to realize caries diagnosis. By comparing THz responses between healthy teeth and caries, the transmitted THz signals in caries are evidently reduced. Concomitantly, the THz birefringence is also unambiguously inhibited when caries occurs due to the destruction of the internal hydroxyapatite crystal structure. This THz anisotropic activity is position-dependent, which can be qualitatively understood by optical microscopic imaging of dental structures. To increase the accuracy of THz technology in detecting dental caries and stimulate the development of THz caries instruments, the presence of significant THz birefringence effect induced anisotropy in enamel, in combination with the strong THz attenuation at the caries, may be used as a new tool for caries diagnosis.
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