A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence

Karunakaran, Varsha; Joseph, Manu M.; Yadev, Induprabha; Sharma, Himanshu; Kottarathil, Shamna; Saurav, Sumeet; Sreejith, Remanan Pushpa; Anand, Veena; Beegum, Rosenara; David, S. Regi; Iype, Thomas; Devi, K.L. Sarada; Nizarudheen, A.; Sharmad, M.S.; Sharma, Rishi; Mukhiya, Ravindra; Thouti, Eshwar; Yoosaf, Karuvath; Joseph, Joshy; Devi, P. Sujatha; Savithri, S.; Agarwal, Ajay; Singh, Sanjay; Maiti, Kaustabh Kumar

doi:10.1016/j.jphotobiol.2022.112545

Cited by 19 publications

(16 citation statements)

References 31 publications

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“…In a unique study, Kim et al studied the efficacy of the Oxford–AstraZeneca vaccine by using SERS studies on tear samples and achieved excellent reproducibility and LOD in the femtomolar regime [ 266 ]. Machine learning algorithms such as PCA and SVM were used for the classification of normal and SARS-CoV-2 saliva samples with SERS data, with an accuracy of 95% [ 267 ]. Different respiratory viruses and their variants were identified using a silver-nanorods-based SERS sensor [ 268 ].…”

Section: Sers For Disease Diagnosismentioning

confidence: 99%

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

2023

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Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS’s full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

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Section: Sers For Disease Diagnosismentioning

confidence: 99%

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

2023

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“…Maiti et al have demonstrated a proof of concept model for non-invasive COVID-19 detection by identifying the Raman signatures of saliva collected from infected patients at various stages. Using multivariate analytical tools with the developed Raman database, the model have been found effective in distinguishing healthy samples as well as different stages of disease recovery (Karunakaran et al 2022 ). In another interesting work, the efficiency of COVID-19 vaccine has been verified from tear samples using SERS technique by synthesizing gold nanorods, nanoflowers, and nanospheres (Kim et al 2022 ).…”

Section: Sars-cov-2 Detectionmentioning

confidence: 99%

Raman spectroscopy for viral diagnostics

et al. 2023

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Raman spectroscopy offers the potential for fingerprinting biological molecules at ultra-low concentration and therefore has potential for the detection of viruses. Here we review various Raman techniques employed for the investigation of viruses. Different Raman techniques are discussed including conventional Raman spectroscopy, surface-enhanced Raman spectroscopy, Raman tweezer, tip-enhanced Raman Spectroscopy, and coherent anti-Stokes Raman scattering. Surface-enhanced Raman scattering can play an essential role in viral detection by multiplexing nanotechnology, microfluidics, and machine learning for ensuring spectral reproducibility and efficient workflow in sample processing and detection. The application of these techniques to diagnose the SARS-CoV-2 virus is also reviewed. Graphical abstract

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Section: Introductionmentioning

confidence: 99%

“…Notably, SERS has been instrumental in the field of COVID-19 diagnostics, 11 specifically in the identification of the SARS-CoV-2 virus within nasal swab samples, achieving an impressive accuracy of about 250 fg mL −1 . [12][13][14][15][16] Within the realm of environmental science, 17 SERS has been effectively employed for the monitoring of heavy metal levels and the detection of microplastics in water. 18,19 Moreover, SERS has proven effective in detecting and quantifying pesticides, [20][21][22][23][24][25][26] food additives, [27][28][29] drug residues, 30,31 and industrial discharges 32,33 within food and water samples.…”

Section: Introductionmentioning

confidence: 99%

Plasmonic-based Raman sensor for ultra-sensitive detection of pharmaceutical waste

Hamode,

Krause,

Shehadeh

et al. 2024

Environ. Sci.: Nano

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A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence

Cited by 19 publications

References 31 publications

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Raman spectroscopy for viral diagnostics

Plasmonic-based Raman sensor for ultra-sensitive detection of pharmaceutical waste

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