1
|
Liu S, Wang Y, Zhao Y, Liu L, Sun S, Zhang S, Liu H, Liu S, Li Y, Yang F, Jiao M, Sun X, Zhang Y, Liu R, Mu X, Wang H, Zhang S, Yang J, Xie X, Duan X, Zhang J, Hong G, Zhang XD, Ming D. A Nanozyme-Based Electrode for High-Performance Neural Recording. Adv Mater 2024; 36:e2304297. [PMID: 37882151 DOI: 10.1002/adma.202304297] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 10/19/2023] [Indexed: 10/27/2023]
Abstract
Implanted neural electrodes have been widely used to treat brain diseases that require high sensitivity and biocompatibility at the tissue-electrode interface. However, currently used clinical electrodes cannot meet both these requirements simultaneously, which hinders the effective recording of electronic signals. Herein, nanozyme-based neural electrodes incorporating bioinspired atomically precise clusters are developed as a general strategy with a heterogeneous design for multiscale and ultrasensitive neural recording via quantum transport and biocatalytic processes. Owing to the dual high-speed electronic and ionic currents at the electrode-tissue interface, the impedance of nanozyme electrodes is 26 times lower than that of state-of-the-art metal electrodes, and the acquisition sensitivity for the local field potential is ≈10 times higher than that of clinical PtIr electrodes, enabling a signal-to-noise ratio (SNR) of up to 14.7 dB for single-neuron recordings in rats. The electrodes provide more than 100-fold higher antioxidant and multi-enzyme-like activities, which effectively decrease 67% of the neuronal injury area by inhibiting glial proliferation and allowing sensitive and stable neural recording. Moreover, nanozyme electrodes can considerably improve the SNR of seizures in acute epileptic rats and are expected to achieve precise localization of seizure foci in clinical settings.
Collapse
Affiliation(s)
- Shuangjie Liu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Yang Wang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Yue Zhao
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Ling Liu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Si Sun
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Shaofang Zhang
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Haile Liu
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Shuhu Liu
- Beijing Synchrotron Radiation Facility (BSRF), Institute of High Energy Physics (IHEP), Chinese Academy of Sciences (CAS), Beijing, 100049, China
| | - Yonghui Li
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Fan Yang
- Department of Materials Science and Engineering, Stanford University, Stanford, California, 94305, USA
| | - Menglu Jiao
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Xinyu Sun
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Yuqin Zhang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Renpeng Liu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Xiaoyu Mu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Hao Wang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| | - Shu Zhang
- Tianjin Neurological Institute, Department of Neurosurgery, General Hospital, Tianjin Medical University, Tianjin, 300041, China
| | - Jiang Yang
- School of Electronics and Information Technology and Medicine, Sun Yat-sen University, Guangzhou, 510060, China
| | - Xi Xie
- School of Electronics and Information Technology and Medicine, Sun Yat-sen University, Guangzhou, 510060, China
| | - Xiaojie Duan
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, China
| | - Jianning Zhang
- Tianjin Neurological Institute, Department of Neurosurgery, General Hospital, Tianjin Medical University, Tianjin, 300041, China
| | - Guosong Hong
- Department of Materials Science and Engineering, Stanford University, Stanford, California, 94305, USA
| | - Xiao-Dong Zhang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
- Department of Physics and Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin, 300354, China
| | - Dong Ming
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
| |
Collapse
|
2
|
Liu YC, Rolfes JD, Björklund J, Deska J. Fully Biocatalytic Rearrangement of Furans to Spirolactones. ACS Catal 2023; 13:7256-7262. [PMID: 37288097 PMCID: PMC10242749 DOI: 10.1021/acscatal.3c00132] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 04/10/2023] [Indexed: 06/09/2023]
Abstract
A multienzymatic pathway enables the preparation of optically pure spirolactone building blocks. In a streamlined one-pot reaction cascade, the combination of chloroperoxidase, an oxidase, and an alcohol dehydrogenase renders an efficient reaction cascade for the conversion of hydroxy-functionalized furans to the spirocyclic products. The fully biocatalytic method is successfully employed in the total synthesis of the bioactive natural product (+)-crassalactone D, and as the key module in a chemoenzymatic route yielding lanceolactone A.
Collapse
Affiliation(s)
- Yu-Chang Liu
- Department
of Chemistry, University of Helsinki, A.I. Virtasen aukio 1, 00560 Helsinki, Finland
- Department
of Chemistry, Aalto University, Kemistintie 1, 02150 Espoo, Finland
| | - J. D. Rolfes
- Albert
Hofmann Institute for Physiochemical Sustainability, Albert-Schweitzer-Street 22, 32602 Vlotho, Germany
| | - Joel Björklund
- Department
of Chemistry, Aalto University, Kemistintie 1, 02150 Espoo, Finland
| | - Jan Deska
- Department
of Chemistry, University of Helsinki, A.I. Virtasen aukio 1, 00560 Helsinki, Finland
- Department
of Chemistry, Aalto University, Kemistintie 1, 02150 Espoo, Finland
| |
Collapse
|
3
|
Soto D, Orozco J. Hybrid Nanobioengineered Nanomaterial-Based Electrochemical Biosensors. Molecules 2022; 27:3841. [PMID: 35744967 DOI: 10.3390/molecules27123841] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/03/2022] [Accepted: 06/11/2022] [Indexed: 02/05/2023] Open
Abstract
Nanoengineering biosensors have become more precise and sophisticated, raising the demand for highly sensitive architectures to monitor target analytes at extremely low concentrations often required, for example, for biomedical applications. We review recent advances in functional nanomaterials, mainly based on novel organic-inorganic hybrids with enhanced electro-physicochemical properties toward fulfilling this need. In this context, this review classifies some recently engineered organic-inorganic metallic-, silicon-, carbonaceous-, and polymeric-nanomaterials and describes their structural properties and features when incorporated into biosensing systems. It further shows the latest advances in ultrasensitive electrochemical biosensors engineered from such innovative nanomaterials highlighting their advantages concerning the concomitant constituents acting alone, fulfilling the gap from other reviews in the literature. Finally, it mentioned the limitations and opportunities of hybrid nanomaterials from the point of view of current nanotechnology and future considerations for advancing their use in enhanced electrochemical platforms.
Collapse
|