The Journal of Light Scattering, Volume. 36, Issue 1, 1(2024)

Recent advances in surface-enhanced Raman spectroscopy(SERS) combined with machine learning algorithms in biomedical fields

WANG Jiaqi1, XU Weiqing1, and XU Shuping1,2,3、*
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(46)

    [1] [1] Fleischmann M, Hendra P J, McQuillan A J. Raman spectra of pyridine adsorbed at a silver electrode[J].Chemical Physics Letters, 1974, 26(2): 163-166.

    [2] [2] Pérez-Jiménez A I, Lyu D, Lu Z, et al.Surface-enhanced Raman spectroscopy: benefits, trade-offs and future developments[J]. Chemical Science, 2020, 11(18): 4563-4577.

    [3] [3] Han X X, Rodriguez R S, Haynes C L, et al.Surface-enhanced Raman spectroscopy[J]. Nature Reviews Methods Primers, 2021, 1(1): 87.

    [4] [4] Zong C, Xu M, Xu L J, et al.Surface-enhanced Raman spectroscopy for bioanalysis: reliability and challenges[J]. Chemical Reviews, 2018, 118(10): 4946-4980.

    [6] [6] Kneipp K, Wang Y, Kneipp H, et al. Single molecule detection using surface-enhanced Raman scattering (SERS)[J]. Physical Review Letters, 1997, 78(9): 1667.

    [7] [7] McNay G, Eustace D, Smith W E, et al. Surface-enhanced Raman scattering (SERS) and surface-enhanced resonance Raman scattering (SERRS): a review of applications[J]. Applied Spectroscopy, 2011, 65(8): 825-837.

    [8] [8] Cutshaw G, Uthaman S, Hassan N, et al.The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine[J]. Chemical Reviews, 2023.

    [9] [9] Keyes T J, Domizi P, Lo Y C, et al. A cancer biologist's primer on machine learning applications in high‐dimensional cytometry[J]. Cytometry Part A, 2020, 97(8): 782-799.

    [10] [10] Chester C, Maecker H T. Algorithmic tools for mining high-dimensional cytometry data[J]. The Journal of Immunology, 2015, 195(3): 773-779.

    [11] [11] Kimball A K, Oko L M, Bullock B L, et al. A beginner’s guide to analyzing and visualizing mass cytometry data[J]. The Journal of Immunology, 2018, 200(1): 3-22.

    [12] [12] Morais C L M, Lima K M G, Singh M, et al.Tutorial: multivariate classification for vibrational spectroscopy in biological samples[J]. Nature Protocols, 2020, 15(7): 2143-2162.

    [13] [13] Lussier F, Thibault V, Charron B, et al.Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering[J]. TrAC Trends in Analytical Chemistry, 2020, 124: 115796.

    [14] [14] MacEachern S J, Forkert N D. Machine learning for precision medicine[J]. Genome, 2021, 64(4): 416-425.

    [15] [15] Fan X, Ming W, Zeng H, et al. Deep learning-based component identification for the Raman spectra of mixtures[J]. Analyst, 2019, 144(5): 1789-1798.

    [16] [16] Maleki F, Muthukrishnan N, Ovens K, et al. Machine learning algorithm validation: from essentials to advanced applications and implications for regulatory certification and deployment[J]. Neuroimaging Clinics, 2020, 30(4): 433-445.

    [17] [17] Baek S, Tsai C A, Chen J J. Development of biomarker classifiers from high-dimensional data[J]. Briefings in Bioinformatics, 2009, 10(5): 537-546.

    [18] [18] Desaire H. How (not) to generate a highly predictive biomarker panel using machine learning[J]. Journal of Proteome Research, 2022, 21(9): 2071-2074.

    [19] [19] Saeys Y, Inza I, Larranaga P. A review of feature selection techniques in bioinformatics[J]. Bioinformatics, 2007, 23(19): 2507-2517.

    [20] [20] Chen Y B, Cutler C S. Biomarkers for acute GVHD: can we predict the unpredictable?[J]. Bone marrow transplantation, 2013, 48(6): 755-760.

    [21] [21] Lee W, Nanou A, Rikkert L, et al.Label-free prostate cancer detection by characterization of extracellular vesicles using Raman spectroscopy[J]. Analytical Chemistry, 2018, 90(19): 11290-11296.

    [22] [22] Dai Y, Yu Y, Wang X, et al. Hybrid Principal Component Analysis Denoising Enables Rapid, Label-Free Morpho-Chemical Quantification of Individual Nanoliposomes[J]. Analytical Chemistry, 2022, 94(41): 14232-14241.

    [23] [23] Lussier F, Brulé T, Vishwakarma M, et al. Dynamic-SERS optophysiology: a nanosensor for monitoring cell secretion events[J]. Nano Letters, 2016, 16(6): 3866-3871.

    [24] [24] Dong S, He D, Zhang Q, et al. Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning[J]. eLight, 2023, 3(1): 1-11.

    [25] [25] Lin X, Lin D, Chen Y, et al. High throughput blood analysis based on deep learning algorithm and self-positioning super-hydrophobic SERS platform for non-invasive multi-disease screening[J]. Advanced Functional Materials, 2021, 31(51): 2103382.

    [26] [26] Shin H, Choi B H, Shim O, et al. Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers[J]. Nature Communications, 2023, 14(1): 1644.

    [27] [27] Shin H, Oh S, Hong S, et al. Early-stage lung cancer diagnosis by deep learning-based spectroscopic analysis of circulating exosomes[J]. ACS nano, 2020, 14(5): 5435-5444.

    [28] [28] Haldavnekar R, Venkatakrishnan K, Tan B. Cancer stem cell derived extracellular vesicles with self-functionalized 3D nanosensor for real-time cancer diagnosis: eliminating the roadblocks in liquid biopsy[J]. ACS Nano, 2022, 16(8): 12226-12243.

    [29] [29] Ishwar D, Haldavnekar R, Das S, et al. Glioblastoma associated natural killer cell EVs generating tumour-specific signatures: noninvasive GBM liquid biopsy with self-functionalized quantum probes[J]. ACS Nano, 2022, 16(7): 10859-10877.

    [30] [30] Premachandran S, Haldavnekar R, Das S, et al.DEEP surveillance of brain cancer using self-functionalized 3D nanoprobes for noninvasive liquid biopsy[J]. ACS Nano, 2022, 16(11): 17948-17964.

    [31] [31] Ganesh S, Dharmalingam P, Das S, et al. Mapping Immune-Tumor Bidirectional Dialogue Using Ultrasensitive Nanosensors for Accurate Diagnosis of Lung Cancer[J]. ACS Nano, 2023, 17(9): 8026-8040.

    [32] [32] Tsao S C H, Wang J, Wang Y, et al. Characterising the phenotypic evolution of circulating tumour cells during treatment[J]. Nature communications, 2018, 9(1): 1482.

    [33] [33] Phyo J B, Woo A, Yu H J, et al. Label-free SERS analysis of urine using a 3D-stacked AgNW-glass fiber filter sensor for the diagnosis of pancreatic cancer and prostate cancer[J]. Analytical chemistry, 2021, 93(8): 3778-3785.

    [34] [34] Linh V T N, Lee M Y, Mun J, et al. 3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening[J]. Biosensors and Bioelectronics, 2023, 224: 115076.

    [35] [35] Lu D, Chen Y, Ke L, et al.Machine learning-assisted global DNA methylation fingerprint analysis for differentiating early-stage lung cancer from benign lung diseases[J]. Biosensors and Bioelectronics, 2023, 235: 115235.

    [36] [36] Huang L, Sun H, Sun L, et al.Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning[J]. Nature Communications, 2023, 14(1): 48.

    [37] [37] Liu X, Wang M, Zhang K, et al. Diagnostic strategy for malignant and benign thyroid nodules smaller than 10 mm based on surface-enhanced Raman spectroscopy and machine learning[J]. Chemical Engineer Journal, 2023, 471: 144794.

    [38] [38] Nam W, Ren X, Kim I, et al. Plasmonically calibrated label-free surface-enhanced Raman spectroscopy for improved multivariate analysis of living cells in cancer subtyping and drug testing[J].Analytical Chemistry, 2021, 93(10): 4601-4610.

    [39] [39] Xie Y, Wen Y, Su X, et al. Label-free plasmon-enhanced spectroscopic HER2 detection for dynamic therapeutic surveillance of breast cancer[J]. Analytical Chemistry, 2022, 94(37): 12762-12771.

    [40] [40] Lussier F, Missirlis D, Spatz J P, et al. Machine-learning-driven surface-enhanced Raman scattering optophysiology reveals multiplexed metabolite gradients near cells[J]. ACS nano, 2019, 13(2): 1403-1411.

    [41] [41] Wu L, Teixeira A, Garrido-Maestu A, et al. Profiling DNA mutation patterns by SERS fingerprinting for supervised cancer classification[J]. Biosensors and Bioelectronics, 2020, 165: 112392.

    [42] [42] Cong L, Wang J, Li X, et al.Microfluidic droplet-SERS platform for single-cell cytokine analysis via a cell surface bioconjugation strategy[J]. Analytical Chemistry, 2022, 94(29): 10375-10383.

    [43] [43] Wang J, Cong L, Shi W, et al. Single-Cell Analysis and Classification according to Multiplexed Proteins via Microdroplet-Based Self-Driven Magnetic Surface-Enhanced Raman Spectroscopy Platforms Assisted with Machine Learning Algorithms[J]. Analytical Chemistry, 2023, 95(29): 11019-11027.

    [44] [44] Kim S, Kim T G, Lee S H, et al. Label-free surface-enhanced Raman spectroscopy biosensor for on-site breast cancer detection using human tears[J]. ACS applied materials & interfaces, 2020, 12(7): 7897-7904.

    [45] [45] Paria D, Kwok K S, Raj P, et al. Label-free spectroscopic SARS-CoV-2 detection on versatile nanoimprinted substrates[J].Nano letters, 2022, 22(9): 3620-3627.

    [46] [46] Peng Y, Lin C, Li Y, et al. Identifying infectiousness of SARS-CoV-2 by ultra-sensitive SnS2 SERS biosensors with capillary effect[J]. Matter, 2022, 5(2): 694-709.

    [47] [47] Peng M, Wang Z, Sun X, et al.Deep Learning-Based Label-Free Surface-Enhanced Raman Scattering Screening and Recognition of Small-Molecule Binding Sites in Proteins[J]. Analytical Chemistry, 2022, 94(33): 11483-11491.

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    WANG Jiaqi, XU Weiqing, XU Shuping. Recent advances in surface-enhanced Raman spectroscopy(SERS) combined with machine learning algorithms in biomedical fields[J]. The Journal of Light Scattering, 2024, 36(1): 1

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    Paper Information

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    Received: Sep. 22, 2023

    Accepted: --

    Published Online: Jul. 22, 2024

    The Author Email: Shuping XU (xusp@jlu.edu.cn)

    DOI:10.13883/j.issn1004-5929.202401001

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