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Gobbato R, Fornasaro S, Sergo V, Bonifacio A. Direct comparison of different protocols to obtain surface enhanced Raman spectra of human serum. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 317:124390. [PMID: 38749203 DOI: 10.1016/j.saa.2024.124390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/21/2024] [Accepted: 04/29/2024] [Indexed: 05/31/2024]
Abstract
Label-free Surface Enhanced Raman Spectroscopy (SERS) is a rapid technique that has been extensively applied in clinical diagnosis and biomedicine for the analysis of biofluids. The purpose of this approach relies on the ability to detect specific "metabolic fingerprints" of complex biological samples, but the full potential of this technique in diagnostics is yet to be exploited, mainly because of the lack of common analytical protocols for sample preparation and analysis. Variation of experimental parameters, such as substrate type, laser wavelength and sample processing can greatly influence spectral patterns, making results from different research groups difficult to compare. This study aims at making a step toward a standardization of the protocols in the analysis of human serum samples with Ag nanoparticles, by directly comparing the SERS spectra obtained from five different methods in which parameters like laser power, nanoparticle concentration, incubation/deproteinization steps and type of substrate used vary. Two protocols are the most used in the literature, and the other three are "in-house" protocols proposed by our group; all of them are employed to analyze the same human serum sample. The experimental results show that all protocols yield spectra that share the same overall spectral pattern, conveying the same biochemical information, but they significantly differ in terms of overall spectral intensity, repeatability, and preparation steps of the sample. A Principal Component Analysis (PCA) was performed revealing that protocol 3 and protocol 1 have the least variability in the dataset, while protocol 2 and 4 are the least repeatable.
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Affiliation(s)
- Roberto Gobbato
- Raman Spectroscopy Laboratory, Department of Engineering and Architecture, University of Trieste, Via Valerio 6a, 34127 Trieste, TS, Italy.
| | - Stefano Fornasaro
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, TS, Italy.
| | - Valter Sergo
- Raman Spectroscopy Laboratory, Department of Engineering and Architecture, University of Trieste, Via Valerio 6a, 34127 Trieste, TS, Italy.
| | - Alois Bonifacio
- Raman Spectroscopy Laboratory, Department of Engineering and Architecture, University of Trieste, Via Valerio 6a, 34127 Trieste, TS, Italy.
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2
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Eiamchai P, Juntagran C, Somboonsaksri P, Waiwijit U, Eisiri J, Samarnjit J, Kaewseekhao B, Limwichean S, Horprathum M, Reechaipichitkul W, Nuntawong N, Faksri K. Determination of latent tuberculosis infection from plasma samples via label-free SERS sensors and machine learning. Biosens Bioelectron 2024; 250:116063. [PMID: 38290379 DOI: 10.1016/j.bios.2024.116063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/02/2024] [Accepted: 01/22/2024] [Indexed: 02/01/2024]
Abstract
Effective diagnostic tools for screening of latent tuberculosis infection (LTBI) are lacking. We aim to investigate the performance of LTBI diagnostic approaches using label-free surface-enhanced Raman spectroscopy (SERS). We used 1000 plasma samples from Northeast Thailand. Fifty percent of the samples had tested positive in the interferon-gamma release assay (IGRA) and 50 % negative. The SERS investigations were performed on individually prepared protein specimens using the Raman-mapping technique over a 7 × 7 grid area under measurement conditions that took under 10 min to complete. The machine-learning analysis approaches were optimized for the best diagnostic performance. We found that the SERS sensors provide 81 % accuracy according to train-test split analysis and 75 % for LOOCV analysis from all samples, regardless of the batch-to-batch variation of the sample sets and SERS chip. The accuracy increased to 93 % when the logistic regression model was used to analyze the last three batches of samples, following optimization of the sample collection, SERS chips, and database. We demonstrated that SERS analysis with machine learning is a potential diagnostic tool for LTBI screening.
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Affiliation(s)
- Pitak Eiamchai
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand.
| | - Chadatan Juntagran
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand.
| | - Pacharamon Somboonsaksri
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Uraiwan Waiwijit
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Jukgarin Eisiri
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Janejira Samarnjit
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Benjawan Kaewseekhao
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand
| | - Saksorn Limwichean
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Mati Horprathum
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Wipa Reechaipichitkul
- Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand; Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Noppadon Nuntawong
- National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand.
| | - Kiatichai Faksri
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand.
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Fornasaro S, Rapani A, Farina F, Ibishi M, Pisnoli G, Stacchi C, Sergo V, Bonifacio A, Di Lenarda R, Berton F. Spectroscopic insights into peri-implant mucositis and peri-implantitis: unveiling peri-implant crevicular fluid profiles using surface enhanced Raman scattering. Analyst 2024; 149:885-894. [PMID: 38179644 DOI: 10.1039/d3an01438j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
The precise identification and differentiation of peri-implant diseases, without the need for intrusive procedures, is crucial for the successful clinical treatment and overall durability of dental implants. This work introduces a novel approach that combines surface-enhanced Raman scattering (SERS) spectroscopy with advanced chemometrics to analyse peri-implant crevicular fluid (PICF) samples. The primary purpose is to offer an unbiased evaluation of implant health. A detailed investigation was performed on PICF samples obtained from a cohort of patients exhibiting different levels of peri-implant health, including those with healthy implants, implants impacted by peri-implantitis, and implants with peri-implant mucositis. The obtained SERS spectra were analysed using canonical-powered partial least squares (CPPLS) to identify unique chemical characteristics associated with each inflammatory state. Significantly, our research findings unveil the presence of a common inflammatory SERS spectral pattern in cases of peri-implantitis and peri-implant mucositis. Furthermore, the SERS-based scores obtained from CPPLS were combined with established clinical scores and subjected to a linear discriminant analysis (LDA) classifier. Repeated double cross-validation was used to validate the method's capacity to discriminate different implant conditions. The integrated approach showcased high sensitivity and specificity and an overall balanced accuracy of 92%, demonstrating its potential to serve as a non-invasive diagnostic tool for real-time implant monitoring and early detection of inflammatory conditions.
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Affiliation(s)
- Stefano Fornasaro
- University of Trieste, Department of Chemical and Pharmaceutical Sciences, via L. Giorgeri 1, 34127 Trieste, Italy.
| | - Antonio Rapani
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Federica Farina
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Marigona Ibishi
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Giulia Pisnoli
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Claudio Stacchi
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Valter Sergo
- Raman Spectroscopy Lab, Department of Engineering and Architecture, University of Trieste, via A. Valerio 6a, 34127 Trieste, Italy
| | - Alois Bonifacio
- Raman Spectroscopy Lab, Department of Engineering and Architecture, University of Trieste, via A. Valerio 6a, 34127 Trieste, Italy
| | - Roberto Di Lenarda
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
| | - Federico Berton
- Maxillofacial and Dental Surgical Clinic, Department of Medical, Surgical and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, 34125, Trieste, Italy
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Tian F, de Carvalho LFDCES, Casey A, Nogueira MS, Byrne HJ. Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:1216. [PMID: 37049309 PMCID: PMC10097234 DOI: 10.3390/nano13071216] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 06/19/2023]
Abstract
In recent years, the disease burden of hyperuricemia has been increasing, especially in high-income countries and the economically developing world with a Western lifestyle. Abnormal levels of uric acid and hypoxanthine are associated with many diseases, and therefore, to demonstrate improved methods of uric acid and hypoxanthine detection, three different bodily fluids were analysed using surface-enhanced Raman spectroscopy (SERS) and high-performance liquid chromatography (HPLC). Gold nanostar suspensions were mixed with series dilutions of uric acid and hypoxanthine, 3 kDa centrifugally filtered human blood serum, urine and saliva. The results show that gold nanostars enable the quantitative detection of the concentration of uric acid and hypoxanthine in the range 5-50 μg/mL and 50-250 ng/mL, respectively. The peak areas of HPLC and maximum peak intensity of SERS have strongly correlated, notably with the peaks of uric acid and hypoxanthine at 1000 and 640 cm-1, respectively. The r2 is 0.975 and 0.959 for uric acid and hypoxanthine, respectively. Each of the three body fluids has a number of spectral features in common with uric acid and hypoxanthine. The large overlap of the spectral bands of the SERS of uric acid against three body fluids at spectra peaks were at 442, 712, 802, 1000, 1086, 1206, 1343, 1436 and 1560 cm-1. The features at 560, 640, 803, 1206, 1290 and 1620 cm-1 from hypoxanthine were common to serum, saliva and urine. There is no statistical difference between HPLC and SERS for determination of the concentration of uric acid and hypoxanthine (p > 0.05). For clinical applications, 3 kDa centrifugal filtration followed by SERS can be used for uric acid and hypoxanthine screening is, which can be used to reveal the subtle abnormalities enhancing the great potential of vibrational spectroscopy as an analytical tool. Our work supports the hypnosis that it is possible to obtain the specific concentration of uric acid and hypoxanthine by comparing the SER signals of serum, saliva and urine. In the future, the analysis of other biofluids can be employed to detect biomarkers for the diagnosis of systemic pathologies.
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Affiliation(s)
- Furong Tian
- FOCAS Research Institute, Technological University Dublin Camden Row, D08CKP1 Dublin, Ireland; (A.C.)
| | - Luis Felipe das Chagas e Silva de Carvalho
- FOCAS Research Institute, Technological University Dublin Camden Row, D08CKP1 Dublin, Ireland; (A.C.)
- Centro Universitario Braz Cubas, Mogi das Cruzes 08773-380, Brazil
- Universidade de Taubate, Taubate 12080-000, Brazil
| | - Alan Casey
- FOCAS Research Institute, Technological University Dublin Camden Row, D08CKP1 Dublin, Ireland; (A.C.)
| | - Marcelo Saito Nogueira
- Tyndall National Institute, Lee Maltings Complex, Dyke Parade, T12R5CP Cork, Ireland;
- Department of Physics, University College Cork, College Road, T12K8AF Cork, Ireland
| | - Hugh J. Byrne
- FOCAS Research Institute, Technological University Dublin Camden Row, D08CKP1 Dublin, Ireland; (A.C.)
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Chisanga M, Williams H, Boudreau D, Pelletier JN, Trottier S, Masson JF. Label-Free SERS for Rapid Differentiation of SARS-CoV-2-Induced Serum Metabolic Profiles in Non-Hospitalized Adults. Anal Chem 2023; 95:3638-3646. [PMID: 36763490 PMCID: PMC9940618 DOI: 10.1021/acs.analchem.2c04514] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
COVID-19 represents a multi-system infectious disease with broad-spectrum manifestations, including changes in host metabolic processes connected to the disease pathogenesis. Understanding biochemical dysregulation patterns as a consequence of COVID-19 illness promises to be crucial for tracking disease course and clinical outcomes. Surface-enhanced Raman scattering (SERS) has attracted considerable interest in biomedical diagnostics for the sensitive detection of intrinsic profiles of unique fingerprints of serum biomolecules indicative of SARS-CoV-2 infection in a label-free format. Here, we applied label-free SERS and chemometrics for rapid interrogation of temporal metabolic dynamics in longitudinal sera of mildly infected non-hospitalized patients (n = 22), at 4 and 16 weeks post PCR-positive diagnosis, and compared them with negative controls (n = 8). SERS spectral markers revealed distinct metabolic profiles in patient sera that significantly deviated from the healthy metabolic state at the two sampling time intervals. Multivariate and univariate analyses of the spectral data identified abundance dynamics in amino acids, lipids, and protein vibrations as the key spectral features underlying the metabolic differences detected in convalescent samples and perhaps associated with patient recovery progression. A validation study performed using spontaneous Raman spectroscopy yielded spectral data results that corroborated SERS spectral findings and confirmed the detected disease-specific molecular phenotypes in clinical samples. Label-free SERS promises to be a valuable analytical technique for rapid screening of the metabolic phenotype induced by SARS-CoV-2 infection to allow appropriate healthcare intervention.
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Affiliation(s)
- Malama Chisanga
- Department
of Chemistry, Québec Centre for Advanced Materials (QCAM),
Regroupement Québécois sur les Matériaux de Pointe
(RQMP), and Centre Interdisciplinaire de Recherche sur le Cerveau
et l’Apprentissage (CIRCA), Université
de Montréal, CP 6128 Succ. Centre-Ville, Montreal, Québec H3C 3J7, Canada
| | - Hannah Williams
- Department
of Chemistry, Québec Centre for Advanced Materials (QCAM),
Regroupement Québécois sur les Matériaux de Pointe
(RQMP), and Centre Interdisciplinaire de Recherche sur le Cerveau
et l’Apprentissage (CIRCA), Université
de Montréal, CP 6128 Succ. Centre-Ville, Montreal, Québec H3C 3J7, Canada
| | - Denis Boudreau
- Department
of Chemistry and Centre for Optics, Photonics and Lasers (COPL), Université Laval, 1045, av. de la Médecine, Québec, Québec G1V 0A6, Canada
| | - Joelle N. Pelletier
- Department
of Chemistry, Department of Biochemistry and PROTEO, Québec
Network for Research on Protein Function, Engineering and Applications, Université de Montréal, CP 6128 Succ. Centre-Ville, Montreal, Québec H3C 3J7, Canada
| | - Sylvie Trottier
- Centre
de Recherche du Centre Hospitalier Universitaire de Québec
and Département de Microbiologie-Infectiologie et d’Immunologie, Université Laval, 2705, boulevard Laurier, Québec, Québec G1V 4G2, Canada
| | - Jean-Francois Masson
- Department
of Chemistry, Québec Centre for Advanced Materials (QCAM),
Regroupement Québécois sur les Matériaux de Pointe
(RQMP), and Centre Interdisciplinaire de Recherche sur le Cerveau
et l’Apprentissage (CIRCA), Université
de Montréal, CP 6128 Succ. Centre-Ville, Montreal, Québec H3C 3J7, Canada,. Phone: +1-514-343-7342
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Wang Z, Hong Y, Yan H, Luo H, Zhang Y, Li L, Lu S, Chen Y, Wang D, Su Y, Yin G. Fabrication of optoplasmonic particles through electroless deposition and the application in SERS-based screening of nodule-involved lung cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 279:121483. [PMID: 35700612 DOI: 10.1016/j.saa.2022.121483] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/02/2022] [Accepted: 06/04/2022] [Indexed: 06/15/2023]
Abstract
In this work, a core-satellite optoplasmonic particle containing a silica microsphere covered with gold nanoparticles (AuNPs) was developed through wet chemistry synthesis in aqueous phase. The electroless deposition and galvanic replacement were employed to anchor AuNPs onto silica sphere surface. The escalated as well as expanded electric field enhancement within the dielectric-metallic interface was analyzed through finite difference time domain (FDTD) simulation. The numerical models and the surface-enhancement Raman spectroscopy (SERS) measurements over blood serum both support that the equatorial plane is the preferred collecting plane for improved signal intensity and stability. The nanocomposite emerged lower relative standard deviation (RSD) in repetitive measurement compared to AuNPs. In practice, this hybrid structure was applied for lung cancer diagnosis based on serum SERS spectra analysis of the patients diagnosed with nodules. The prediction with the aid of principal component analysis (PCA) and support-vector machine (SVM) was attempted for the classification of healthy, benign and relatively malignant sample groups. The accuracy of distinguish benign samples from malignant ones reaches over 90%. These advantages make the structure a promising SERS substrate for the early screening of cancer based on the non-invasive biological samples.
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Affiliation(s)
- Zehua Wang
- School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yan Hong
- School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Huan Yan
- School of Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Huaichao Luo
- Department of Clinical Laboratory, Sichuan Cancer Hospitall, Chengdu 610042, China
| | - Yating Zhang
- School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lintao Li
- Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610042, China
| | - Shun Lu
- Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610042, China
| | - Yuanming Chen
- School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Dongsheng Wang
- Department of Clinical Laboratory, Sichuan Cancer Hospitall, Chengdu 610042, China
| | - Yuanzhang Su
- School of Automation Engineering & School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Gang Yin
- Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610042, China.
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