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Srivastava S, Sandhu N, Liu J, Xie YH. AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids. Bioengineering (Basel) 2024; 11:482. [PMID: 38790349 PMCID: PMC11117800 DOI: 10.3390/bioengineering11050482] [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: 03/03/2024] [Revised: 05/05/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024] Open
Abstract
Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.
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Affiliation(s)
| | | | | | - Ya-Hong Xie
- Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA; (S.S.); (N.S.); (J.L.)
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Chen C, Qi J, Li Y, Li D, Wu L, Li R, Chen Q, Sun N. Applications of Raman spectroscopy in the diagnosis and monitoring of neurodegenerative diseases. Front Neurosci 2024; 18:1301107. [PMID: 38370434 PMCID: PMC10869569 DOI: 10.3389/fnins.2024.1301107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/17/2024] [Indexed: 02/20/2024] Open
Abstract
Raman scattering is an inelastic light scattering that occurs in a manner reflective of the molecular vibrations of molecular structures and chemical conditions in a given sample of interest. Energy changes in the scattered light can be assessed to determine the vibration mode and associated molecular and chemical conditions within the sample, providing a molecular fingerprint suitable for sample identification and characterization. Raman spectroscopy represents a particularly promising approach to the molecular analysis of many diseases owing to clinical advantages including its instantaneous nature and associated high degree of stability, as well as its ability to yield signal outputs corresponding to a single molecule type without any interference from other molecules as a result of its narrow peak width. This technology is thus ideally suited to the simultaneous assessment of multiple analytes. Neurodegenerative diseases represent an increasingly significant threat to global public health owing to progressive population aging, imposing a severe physical and social burden on affected patients who tend to develop cognitive and/or motor deficits beginning between the ages of 50 and 70. Owing to a relatively limited understanding of the etiological basis for these diseases, treatments are lacking for the most common neurodegenerative diseases, which include Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. The present review was formulated with the goal of briefly explaining the principle of Raman spectroscopy and discussing its potential applications in the diagnosis and evaluation of neurodegenerative diseases, with a particular emphasis on the research prospects of this novel technological platform.
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Affiliation(s)
- Chao Chen
- Central Laboratory, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
| | - Jinfeng Qi
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ying Li
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ding Li
- Department of Clinical Laboratory, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
| | - Lihong Wu
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ruihua Li
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Qingfa Chen
- Institute of Tissue Engineering and Regenerative Medicine, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
- Research Center of Basic Medicine, Jinan Central Hospital, Jinan, China
| | - Ning Sun
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
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Srivastava S, Terai Y, Liu J, Capellini G, Xie YH. Controlling the Nucleation and Growth of Salt from Bodily Fluid for Enhanced Biosensing Applications. BIOSENSORS 2023; 13:1016. [PMID: 38131777 PMCID: PMC10741434 DOI: 10.3390/bios13121016] [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: 11/16/2023] [Revised: 12/02/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) represents a transformative tool in medical diagnostics, particularly for the early detection of key biomarkers such as small extracellular vesicles (sEVs). Its unparalleled sensitivity and compatibility with intricate biological samples make it an ideal candidate for revolutionizing noninvasive diagnostic methods. However, a significant challenge that mars its efficacy is the throughput limitation, primarily anchored in the prerequisite of hotspot and sEV colocalization within a minuscule range. This paper delves deep into this issue, introducing a never-attempted-before approach which harnesses the principles of crystallization-nucleation and growth. By synergistically coupling lasers with plasmonic resonances, we navigate the challenges associated with the analyte droplet drying method and the notorious coffee ring effect. Our method, rooted in a profound understanding of crystallization's materials science, exhibits the potential to significantly increase the areal density of accessible plasmonic hotspots and efficiently guide exosomes to defined regions. In doing so, we not only overcome the throughput challenge but also promise a paradigm shift in the arena of minimally invasive biosensing, ushering in advanced diagnostic capabilities for life-threatening diseases.
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Affiliation(s)
- Siddharth Srivastava
- Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA
| | - Yusuke Terai
- Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA
- Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya 464-8601, Japan
| | - Jun Liu
- Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA
| | - Giovanni Capellini
- IHP—Leibniz Institute for High Performance Microelectronics, 15236 Frankfurt (Oder), Germany;
- Department of Science, Università Degli Studi Roma Tre, Viale Marconi 446, 00146 Rome, Italy
| | - Ya-Hong Xie
- Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095, USA
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Xu Y, Pan X, Li H, Cao Q, Xu F, Zhang J. Accuracy of Raman spectroscopy in the diagnosis of Alzheimer's disease. Front Psychiatry 2023; 14:1112615. [PMID: 37009107 PMCID: PMC10060832 DOI: 10.3389/fpsyt.2023.1112615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
ObjectiveTo systematically evaluate the accuracy of Raman spectroscopy in the diagnosis of Alzheimer's disease.MethodsDatabases including Web of Science, PubMed, The Cochrane Library, EMbase, CBM, CNKI, Wan Fang Data, and VIP were electronically searched for studies on Raman spectroscopy in diagnosis of Alzheimer's disease from inception to November 2022. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in the included studies. Then, meta-analysis was performed using Meta-Disc1.4 and Stata 16.0 software.ResultsA total of eight studies were finally included. The pooled sensitivity of Raman spectroscopy was 0.86 [95% CI (0.80–0.91)], specificity was 0.87 [95% CI (0.79–0.92)], positive likelihood ratio was 5.50 [95% CI (3.55–8.51)], negative likelihood ratio was 0.17 [95% CI (0.09–0.34)], diagnosis odds ratio and area under the curve of SROC were 42.44 [95% CI (19.80–90.97)] and 0.931, respectively. Sensitivity analysis was carried out after each study was excluded one by one, and the results showed that pooled sensitivity and specificity had no significant change, indicating that the stability of the meta-analysis results was great.ConclusionsOur findings indicated that Raman spectroscopy had high accuracy in the diagnosis of AD, though it still did not rule out the possibility of misdiagnosis and missed diagnosis. Limited by the quantity and quality of the included studies, the above conclusions need to be verified by more high-quality studies.
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Affiliation(s)
- Yanmei Xu
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xinyu Pan
- School of Pharmacy, Chengdu Medical College, Chengdu, Sichuan, China
| | - Huan Li
- School of Pharmacy, Chengdu Medical College, Chengdu, Sichuan, China
| | - Qiongfang Cao
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
| | - Fan Xu
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
- *Correspondence: Fan Xu
| | - Jianshu Zhang
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Jianshu Zhang
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