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http://dx.doi.org/10.3807/KJOP.2022.33.6.331

Ex Vivo Raman Spectroscopy Measurement of a Mouse Model of Alzheimer's Disease  

Ko, Kwanhwi (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)
Seo, Younghee (Department of Neurosurgery, Brain Research Institute, College of Medicine, Yonsei University)
Im, Seongmin (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)
Lee, Hongki (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)
Park, Ji Young (Department of Neurosurgery, Brain Research Institute, College of Medicine, Yonsei University)
Chang, Won Seok (Department of Neurosurgery, Brain Research Institute, College of Medicine, Yonsei University)
Kim, Donghyun (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)
Publication Information
Korean Journal of Optics and Photonics / v.33, no.6, 2022 , pp. 331-337 More about this Journal
Abstract
Raman spectroscopy is an optical technique that can identify molecules in a label-free manner, and is therefore heavily investigated in various areas ranging from biomedical engineering to materials science. Probe-based Raman spectroscopy can perform minimally invasive chemical analysis, and thus has potential as a real-time diagnostic tool during surgery. In this study, Raman experimentation was calibrated by examining the Raman shifts with respect to the concentrations of chemical substances. Raman signal characteristics, targeted for normal mice and cerebral tissues of the 5xFAD dementia mutant model with accumulated amyloid beta plaques, were measured and analyzed to explore the possibility of diagnosis of Alzheimer's disease. The application to the diagnosis of dementia was cross-validated by measuring Raman signals of amyloid beta. The results suggest the potential of Raman spectroscopy as a diagnostic tool that may be useful in various areas of application.
Keywords
Biosensor; Neurodegenerative disease; Raman spectroscopy;
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1 M. J. Egan, S. K. Sharma, and T. E. Acosta-Maeda, "Modified spatial heterodyne Raman spectrometer for remote-sensing analysis of organics," Proc. SPIE 10779, 107790L (2018).
2 K. Maquelin, C. Kirschner, L. P. Choo-Smith, N. van den Braak, H. P. Endtz, D. Naumann, and G. J. Puppels, "Identification of medically relevant microorganisms by vibrational spectroscopy," J. Microbiol. Methods 51, 255-271 (2002).   DOI
3 E. Staniszewska-Slezak, K. Malek, and M. Baranska, "Complementary analysis of tissue homogenates composition obtained by Vis and NIR laser excitations and Raman spectroscopy," Spectrochim. Acta A: Mol. Biomol. Spectrosc. 147, 245-256 (2015).   DOI
4 B. Lochocki, B. D. C. Boon, S. R. Verheul, L. Zada, J. J. M. Hoozemans, F. Ariese, and J. F. de Boer, "Multimodal, label-free fluorescence and Raman imaging of amyloid deposits in snap-frozen Alzheimer's disease human brain tissue," Commun. Biol. 4, 474 (2021).   DOI
5 G. Moon, J. Lee, H. Lee, H. Yoo, K. Ko, S. Im, and D. Kim, "Machine learning and its applications for plasmonics in biology," Cell Rep. Phys. Sci. 3, 101042 (2022).   DOI
6 M. Jermyn, K. Mok, J. Mercier, J. Desroches, J. Pichette, K. Saint-Arnaud, L. Bernstein, M. C. Guiot, K. Petrecca, and F. Leblond, "Intraoperative brain cancer detection with Raman spectroscopy in humans," Sci. Transl. Med. 7, 274ra19 (2015).   DOI
7 W. Lee, Y. Kinosita, Y. Oh, N. Mikami, H. Yang, M. Miyata, T. Nishizaka, and D. Kim, "Three-dimensional superlocalization imaging of gliding Mycoplasma mobile by extraordinary light transmission through arrayed nanoholes," ACS Nano 9, 10896-10908 (2015).   DOI
8 R. Prucek, A. Panacek, Z. Gajdova, R. Vecerova, L. Kvitek, J. Gallo, and M. Kolar, "Specific detection of Staphylococcus aureus infection and marker for Alzheimer disease by surface enhanced Raman spectroscopy using silver and gold nanoparticle-coated magnetic polystyrene beads," Sci. Rep. 11, 6240 (2021).   DOI
9 K. A. Willets and R. P. Van Duyne, "Localized surface plasmon resonance spectroscopy and sensing," Annu. Rev. Phys. Chem. 58, 267-297 (2007).   DOI
10 K. Kim, J. Yajima, Y. Oh, W. Lee, S. Oowada, T. Nishizaka, and D. Kim, "Nanoscale localization sampling based on nanoantenna arrays for super-resolution imaging of fluorescent monomers on sliding microtubules," Small 8, 892-900 (2012).   DOI
11 S. Sadigh-Eteghad, B. Sabermarouf, A. Majdi, M. Talebi, M. Farhoudi, and J. Mahmoudi, "Amyloid-beta: a crucial factor in Alzheimer's disease," Med. Princ. Pract. 24, 1-10 (2015).
12 H. Lee, W. J. Rhee, G. Moon, S. Im, T. Son, J.-S. Shin, and D. Kim, "Plasmon-enhanced fluorescence correlation spectroscopy for super-localized detection of nanoscale subcellular dynamics," Biosens. Bioelectron. 184, 113219 (2021).   DOI
13 H. Lee, K. Kang, K. Mochizuki, C. Lee, K.-A. Toh, S. A. Lee, K. Fujita, and D. Kim, "Surface plasmon localization-based super-resolved Raman microscopy," Nano Lett. 20, 8951-8958 (2020).   DOI
14 F. Panza, M. Lozupone, G. Logroscino, and B. P. Imbimbo, "A critical appraisal of amyloid-β-targeting therapies for Alzheimer disease," Nat. Rev. Neurol. 15, 73-88 (2019).   DOI
15 K. Kim, W. Lee, K. Chung, H. Lee, T. Son, Y. Oh, Y.-F. Xiao, D. H. Kim, and D. Kim, "Molecular overlap with optical nearfields based on plasmonic nanolithography for ultrasensitive label-free detection by light-matter colocalization," Biosens. Bioelectron. 96, 89-98 (2017).   DOI
16 R. Michael, C. Otto, A. Lenferink, E. Gelpi, G. A. Montenegro, J. Rosandic, F. Tresserra, R. I. Barraquer, and G. F. Vrensen, "Absence of amyloid-beta in lenses of Alzheimer patients: a confocal Raman microspectroscopic study," Exp. Eye Res. 119, 44-53 (2014).   DOI
17 C. Carlomagno, M. Cabinio, S. Picciolini, A. Gualerzi, F. Baglio, and M. Bedoni, "SERS-based biosensor for Alzheimer disease evaluation through the fast analysis of human serum," J. Biophotonics 13, e201960033 (2020).
18 K. Kim, J.-W. Choi, K. Ma, R. Lee, K.-H. Yoo, C.-O. Yun, and D. Kim, "Nanoislands-based random activation of fluorescence for visualizing endocytotic internalization of adenovirus," Small 6, 1293-1299 (2010).   DOI
19 T. Son, D. Lee, C. Lee, G. Moon, G. E. Ha, H. Lee, H. Kwak, E. Cheong, and D. Kim, "Superlocalized three-dimensional live imaging of mitochondrial dynamics in neurons using plasmonic nanohole arrays," ACS Nano 13, 3063-3074 (2019).   DOI
20 M. Kirsch, G. Schackert, R. Salzer, and C. Krafft, "Raman spectroscopic imaging for in vivo detection of cerebral brain metastases," Anal. Bioanal. Chem. 398, 1707-1713 (2010).   DOI
21 K. Hrubesova, M. Fouskova, L. Habartova, Z. Fisar, R. Jirak, J. Raboch, and V. Setnicka, "Search for biomarkers of Alzheimer's disease: Recent insights, current challenges and future prospects," Clin. Biochem. 72, 39-51 (2019).   DOI
22 E. Ryzhikova, N. M. Ralbovsky, V. Sikirzhytski, O. Kazakov, L. Halamkova, J. Quinn, E. A. Zimmerman, and I. K. Lednev, "Raman spectroscopy and machine learning for biomedical applications: Alzheimer's disease diagnosis based on the analysis of cerebrospinal fluid," Spectrochim. Acta A: Mol. Biomol. Spectrosc. 248, 119188 (2021).   DOI
23 C. S. Garcia, M. N. Abedin, S. K. Sharm, A. K. Misra, S. Ismail, U. Singh, T. F. Refaat, H. E. Ali, and S. Sandford, "Remote pulsed laser Raman spectroscopy system for detecting water, ice, and hydrous minerals," Proc. SPIE 6302, 630215 (2006).
24 W. G. Tharp and I. N. Sarkar, "Origins of amyloid-β," BMC Genom. 14, 290 (2013).   DOI
25 C. Haass and D. J. Selkoe, "Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid betapeptide," Nat. Rev. Mol. Cell Biol. 8, 101-112 (2007).   DOI
26 M. Paraskevaidi, C. L. M. Morais, D. E. Halliwell, D. M. A. Mann, D. Allsop, P. L. Martin-Hirsch, and F. L. Martin, "Raman spectroscopy to diagnose Alzheimer's disease and dementia with lewy bodies in blood," ACS Chem. Neurosci. 9, 2786-2794 (2018).   DOI
27 M. Okada, N. I. Smith, A. F. Palonpon, H. Endo, S. Kawata, M. Sodeoka, and K. Fujita, "Label-free Raman observation of cytochrome c dynamics during apoptosis," Proc. Natl. Acad. Sci. 109, 28-32 (2012).   DOI
28 H. Lee, H. Yoo, G. Moon, K.-A. Toh, K. Mochizuki, K. Fujita, and D. Kim, "Super-resolved Raman microscopy using random structured light illumination: concept and feasibility," J. Chem. Phys. 155, 144202 (2021).   DOI
29 N. M. Ralbovsky, L. Halamkova, K. Wall, C. Anderson-Hanley, and I. K. Lednev, "Screening for Alzheimer's disease using saliva: a new approach based on machine learning and Raman hyperspectroscopy," J. Alzheimer's Dis. 71, 1351-1359 (2019).   DOI