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da Silva SMSD, Ferreira CL, Rizzato JMB, Toledo GDS, Furukawa M, Rovai ES, Nogueira MS, Carvalho LFDCESD. Infrared spectroscopy for fast screening of diabetes and periodontitis. Photodiagnosis Photodyn Ther 2024; 46:104106. [PMID: 38677501 DOI: 10.1016/j.pdpdt.2024.104106] [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: 02/21/2024] [Revised: 04/12/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024]
Abstract
SIGNIFICANCE FT-IR is an important and emerging tool, providing information related to the biochemical composition of biofluids. It is important to demonstrate that there is an efficacy in separating healthy and diseased groups, helping to establish FT-IR uses as fast screening tool. AIM Via saliva diagnosis evaluate the accuracy of FT-IR associate with machine learning model for classification among healthy (control group), diabetic (D) and periodontitis (P) patients and the association of both diseases (DP). APPROACH Eighty patients diagnosed with diabetes and periodontitis through conventional methods were recruited and allocated in one of the four groups. Saliva samples were collected from participants of each group (n = 20) and were processed using Bruker Alpha II spectrometer in a FT-IR spectral fingerprint region between 600 and-1800 cm-1, followed by data preprocessing and analysis using machine learning tools. RESULTS Various FTI-R peaks were detectable and attributed to specific vibrational modes, which were classified based on confusion matrices showed in paired groups. The highest true positive rates (TPR) appeared between groups C vs D (93.5 % ± 2.7 %), groups C vs. DP (89.2 % ± 4.1 %), and groups D and P (90.4 % ± 3.2 %). However, P vs DP presented higher TPR for DP (84.1 % ±3.1 %) while D vs. DP the highest rate for DP was 81.7 % ± 4.3 %. Analyzing all groups together, the TPR decreased. CONCLUSION The system used is portable and robust and can be widely used in clinical environments and hospitals as a new diagnostic technique. Studies in our groups are being conducted to solidify and expand data analysis methods with friendly language for healthcare professionals. It was possible to classify healthy patients in a range of 78-93 % of accuracy. Range over 80 % of accuracy between periodontitis and diabetes were observed. A general classification model with lower TPR instead of a pairwise classification would only have advantages in scenarios where no prior patient information is available regarding diabetes and periodontitis status.
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Affiliation(s)
| | | | | | | | - Monique Furukawa
- Science Health Post-graduate Program, University of Taubaté - UNITAU, SP, Brazil
| | - Emanuel Silva Rovai
- Department of Diagnosis and Surgery, Institute of Science and Technology of São José dos Campos, Universidade Estadual Paulista (Unesp), São José Dos Campos, SP, Brazil
| | - Marcelo Saito Nogueira
- Tyndall National Institute, University College Cork, Cork, Ireland; Department of Physics, University College Cork, Cork, Ireland.
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Karthikeyan S, Vazquez-Zapien GJ, Martinez-Cuazitl A, Delgado-Macuil RJ, Rivera-Alatorre DE, Garibay-Gonzalez F, Delgado-Gonzalez J, Valencia-Trujillo D, Guerrero-Ruiz M, Atriano-Colorado C, Lopez-Reyes A, Lopez-Mezquita DJ, Mata-Miranda MM. Two-trace two-dimensional correlation spectra (2T2D-COS) analysis using FTIR spectra to monitor the immune response by COVID-19. J Mol Med (Berl) 2024; 102:53-67. [PMID: 37947852 DOI: 10.1007/s00109-023-02390-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 09/22/2023] [Accepted: 10/20/2023] [Indexed: 11/12/2023]
Abstract
There is a growing trend in using saliva for SARS-CoV-2 detection with reasonable accuracy. We have studied the responses of IgA, IgG, and IgM in human saliva by directly comparing disease with control analyzing two-trace two-dimensional correlation spectra (2T2D-COS) employing Fourier transform infrared (FTIR) spectra. It explores the molecular-level variation between control and COVID-19 saliva samples. The advantage of 2T2D spectra is that it helps in discriminating remarkably subtle features between two simple pairs of spectra. It gives spectral information from highly overlapped bands associated with different systems. The clinical findings from 2T2D show the decrease of IgG and IgM salivary antibodies in the 50, 60, 65, and 75-years COVID-19 samples. Among the various COVID-19 populations studied the female 30-years group reveals defense mechanisms exhibited by IgM and IgA. Lipids and fatty acids decrease, resulting in lipid oxidation due to the SARS-CoV-2 in the samples studied. Study shows salivary thiocyanate plays defense against SARS-CoV-2 in the male population in 25 and 35 age groups. The receiver operation characteristics statistical method shows a sensitivity of 98% and a specificity of 94% for the samples studied. The measure of accuracy computed as F score and G score has a high value, supporting our study's validation. Thus, 2T2D-COS analysis can potentially monitor the progression of immunoglobulin's response function to COVID-19 with reasonable accuracy, which could help diagnose clinical trials. KEY MESSAGES: The molecular profile of salivary antibodies is well resolved and identified from 2T2D-COS FTIR spectra. The IgG antibody plays a significant role in the defense mechanism against SARS-CoV-2 in 25-40 years. 2T2D-COS reveals the absence of salivary thiocyanate in the 40-75 years COVID-19 population. The receiver operation characteristic (ROC) analysis validates our study with high sensitivity and specificity.
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Affiliation(s)
- Sivakumaran Karthikeyan
- Department of Physics, Dr. Ambedkar Government Arts College, Chennai, Tamil Nadu, 600039, India.
| | - Gustavo J Vazquez-Zapien
- Centro de Investigación y Desarrollo del Ejército y Fuerza Aérea Mexicanos, Secretaría de la Defensa Nacional, Mexico City, 11400, Mexico.
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico.
| | - Adriana Martinez-Cuazitl
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico
- Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Mexico City, 07320, Mexico
| | - Raul J Delgado-Macuil
- Centro de Investigación en Biotecnología Aplicada, Instituto Politécnico Nacional, Tlaxcala, 90700, Mexico
| | - Daniel E Rivera-Alatorre
- Centro de Investigación y Desarrollo del Ejército y Fuerza Aérea Mexicanos, Secretaría de la Defensa Nacional, Mexico City, 11400, Mexico
| | - Francisco Garibay-Gonzalez
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico
| | - Josemaria Delgado-Gonzalez
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico
| | - Daniel Valencia-Trujillo
- Servicio de Microbiología Clínica, Instituto Nacional de Enfermedades Respiratorias, Mexico City, 14080, Mexico
| | - Melissa Guerrero-Ruiz
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico
| | - Consuelo Atriano-Colorado
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico
| | - Alberto Lopez-Reyes
- Laboratorio de Gerociencias, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Secretaría de Salud, Mexico City, 14389, Mexico
| | | | - Monica M Mata-Miranda
- Escuela Militar de Medicina, Centro Militar de Ciencias de la Salud, Secretaría de la Defensa Nacional, Mexico City, 11200, Mexico.
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3
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Monaghan JF, Cullen D, Wynne C, Lyng FM, Meade AD. Effect of pre-analytical variables on Raman and FTIR spectral content of lymphocytes. Analyst 2023; 148:5422-5434. [PMID: 37750362 DOI: 10.1039/d3an00686g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
The use of Fourier transform infrared (FTIR) and Raman spectroscopy (RS) for the analysis of lymphocytes in clinical applications is increasing in the field of biomedicine. The pre-analytical phase, which is the most vulnerable stage of the testing process, is where most errors and sample variance occur; however, it is unclear how pre-analytical variables affect the FTIR and Raman spectra of lymphocytes. In this study, we evaluated how pre-analytical procedures undertaken before spectroscopic analysis influence the spectral integrity of lymphocytes purified from the peripheral blood of male volunteers (n = 3). Pre-analytical variables investigated were associated with (i) sample preparation, (blood collection systems, anticoagulant, needle gauges), (ii) sample storage (fresh or frozen), and (iii) sample processing (inter-operator variability, time to lymphocyte isolation). Although many of these procedural pre-analytical variables did not alter the spectral signature of the lymphocytes, evidence of spectral effects due to the freeze-thaw cycle, in vitro culture inter-operator variability and the time to lymphocyte isolation was observed. Although FTIR and RS possess clinical potential, their translation into a clinical environment is impeded by a lack of standardisation and harmonisation of protocols related to the preparation, storage, and processing of samples, which hinders uniform, accurate, and reproducible analysis. Therefore, further development of protocols is required to successfully integrate these techniques into current clinical workflows.
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Affiliation(s)
- Jade F Monaghan
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Daniel Cullen
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Claire Wynne
- School of Biological, Health and Sports Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland
| | - Fiona M Lyng
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Aidan D Meade
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
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Alkhuder K. Fourier-transform infrared spectroscopy: a universal optical sensing technique with auspicious application prospects in the diagnosis and management of autoimmune diseases. Photodiagnosis Photodyn Ther 2023; 42:103606. [PMID: 37187270 DOI: 10.1016/j.pdpdt.2023.103606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 04/27/2023] [Accepted: 05/09/2023] [Indexed: 05/17/2023]
Abstract
Autoimmune diseases (AIDs) are poorly understood clinical syndromes due to breakdown of immune tolerance towards specific types of self-antigens. They are generally associated with an inflammatory response mediated by lymphocytes T, autoantibodies or both. Ultimately, chronic inflammation culminates in tissue damages and clinical manifestations. AIDs affect 5% of the world population, and they represent the main cause of fatality in young to middle-aged females. In addition, the chronic nature of AIDs has a devastating impact on the patient's quality of life. It also places a heavy burden on the health care system. Establishing a rapid and accurate diagnosis is considered vital for an ideal medical management of these autoimmune disorders. However, for some AIDs, this task might be challenging. Vibrational spectroscopies, and more particularly Fourier-transform infrared (FTIR) spectroscopy, have emerged as universal analytical techniques with promising applications in the diagnosis of various types of malignancies and metabolic and infectious diseases. The high sensitivity of these optical sensing techniques and their minimal requirements for test reagents qualify them to be ideal analytical techniques. The aim of the current review is to explore the potential applications of FTIR spectroscopy in the diagnosis and management of most common AIDs. It also aims to demonstrate how this technique has contributed to deciphering the biochemical and physiopathological aspects of these chronic inflammatory diseases. The advantages that can be offered by this optical sensing technique over the traditional and gold standard methods used in the diagnosis of these autoimmune disorders have also been extensively discussed.
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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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Tessaro L, Mutz YDS, Andrade JCD, Aquino A, Belem NKR, Silva FGS, Conte-Junior CA. ATR-FTIR spectroscopy and chemometrics as a quick and simple alternative for discrimination of SARS-CoV-2 infected food of animal origin. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 285:121883. [PMID: 36126622 PMCID: PMC9473138 DOI: 10.1016/j.saa.2022.121883] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/29/2022] [Accepted: 09/10/2022] [Indexed: 06/15/2023]
Abstract
Alternative routes such as virus transmission or cross-contamination by food have been suggested, due to reported cases of SARS-CoV-2 in frozen chicken wings and fish or seafood. Delay in routine testing due to the dependence on the PCR technique as the standard method leads to greater virus dissemination. Therefore, alternative detection methods such as FTIR spectroscopy emerge as an option. Here, we demonstrate a fast (3 min), simple and reagent-free methodology using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy for discrimination of food (chicken, beef and fish) contaminated with the SARS-CoV-2 virus. From the IR spectra of the samples, the "bio-fingerprint" (800 - 1900 cm-1) was selected to investigate the distinctions caused by the virus contamination. Exploratory analysis of the spectra, using Principal Component of Analysis (PCA), indicated the differentiation in the data due to the presence of single bands, marked as contamination from nucleic acids including viral RNA. Furthermore, the partial least squares discriminant analysis (PLS-DA) classification model allowed for discrimination of each matrix in its pure form and its contaminated counterpart with sensitivity, specificity and accuracy of 100 %. Therefore, this study indicates that the use of ATR-FTIR can offer a fast and low cost and not require chemical reagents and with minimal sample preparation to detect the SARS-CoV-2 virus in food matrices, ensuring food safety and non-dissemination by consumers.
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Affiliation(s)
- Leticia Tessaro
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21941-909, Brazil; COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro, RJ 21941-598, Brazil; Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil; Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil; Post-Graduation Program of Chemistry (PGQu), Institute of chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil.
| | - Yhan da Silva Mutz
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21941-909, Brazil; COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro, RJ 21941-598, Brazil; Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil; Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Jelmir Craveiro de Andrade
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21941-909, Brazil; COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro, RJ 21941-598, Brazil; Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil; Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil; Post-Graduation Program of Chemistry (PGQu), Institute of chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil
| | - Adriano Aquino
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21941-909, Brazil; COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro, RJ 21941-598, Brazil; Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil; Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Natasha Kilsy Rocha Belem
- Laboratory of Immunogenetics and Molecular Biology of the General Hospital and Maternity Hospital of Cuiabá, Brazil
| | | | - Carlos Adam Conte-Junior
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21941-909, Brazil; COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro, RJ 21941-598, Brazil; Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil; Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil; Post-Graduation Program of Chemistry (PGQu), Institute of chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro, RJ, Brazil.
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Pushpa S, Sukumaran RK, Savithri S. Robustness of FTIR-Based Ultrarapid COVID-19 Diagnosis Using PLS-DA. ACS OMEGA 2022; 7:47357-47371. [PMID: 36570187 PMCID: PMC9773962 DOI: 10.1021/acsomega.2c06786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
The World Health Organization (WHO) declared the Omicron variant (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for the Coronavirus disease 2019 (COVID-19) pandemic, as a variant of concern on 26 November 2021. By this time, 42% of the world's population had received at least one dose of the vaccine against COVID-19. As on 1 October 2022, only 68% of the world population got the first dose of the vaccine. Although the vaccination is incredibly protective against severe complications of the disease and death, the highly contagious Omicron variant, compared to the Delta variant (B.1.617.2), has led the whole world into more chaotic situations. Furthermore, the virus has a high mutation rate, and hence, the possibility of a new variant of concern in the future cannot be ruled out. To face such a challenging situation, paramount importance should be given to rapid diagnosis and isolation of the infected patient. Current diagnosis methods, including reverse transcription-polymerase chain reaction and rapid antigen tests, face significant burdens during a COVID-19 wave. However, studies reported ultrarapid, reagent-free, cost-efficient, and non-destructive diagnosis methods based on chemometrics for COVID-19 and COVID-19 severity diagnosis. These studies used a smaller sample cohort to construct the diagnosis model and failed to discuss the robustness of the model. The current study systematically evaluated the robustness of the diagnosis models trained using smaller (real and augmented spectra) and larger (augmented spectra) datasets. The Monte Carlo cross-validation and permutation test results suggest that diagnosis using models trained by larger datasets was accurate and statistically significant (Q 2 > 99% and AUROC = 100%).
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Affiliation(s)
- Sreejith
Remanan Pushpa
- Material
Science and Technology Division, CSIR-National
Institute for Interdisciplinary Science and Technology, Industrial Estate P.O., Thiruvananthapuram695019, Kerala, India
- Academy
of Scientific and Innovative Research (AcSIR), Ghaziabad201002, India
| | - Rajeev Kumar Sukumaran
- Microbial
Processes and Technology Division, CSIR-National
Institute for Interdisciplinary Science and Technology, Industrial Estate P.O., Thiruvananthapuram695019, Kerala, India
- Academy
of Scientific and Innovative Research (AcSIR), Ghaziabad201002, India
| | - Sivaraman Savithri
- Material
Science and Technology Division, CSIR-National
Institute for Interdisciplinary Science and Technology, Industrial Estate P.O., Thiruvananthapuram695019, Kerala, India
- Academy
of Scientific and Innovative Research (AcSIR), Ghaziabad201002, India
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Contributions of vibrational spectroscopy to virology: A review. CLINICAL SPECTROSCOPY 2022; 4:100022. [PMCID: PMC9093054 DOI: 10.1016/j.clispe.2022.100022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/30/2022] [Accepted: 05/04/2022] [Indexed: 06/17/2023]
Abstract
Vibrational spectroscopic techniques, both infrared absorption and Raman scattering, are high precision, label free analytical techniques which have found applications in fields as diverse as analytical chemistry, pharmacology, forensics and archeometrics and, in recent times, have attracted increasing attention for biomedical applications. As analytical techniques, they have been applied to the characterisation of viruses as early as the 1970 s, and, in the context of the coronavirus disease 2019 (COVID-19) pandemic, have been explored in response to the World Health Organisation as novel methodologies to aid in the global efforts to implement and improve rapid screening of viral infection. This review considers the history of the application of vibrational spectroscopic techniques to the characterisation of the morphology and chemical compositions of viruses, their attachment to, uptake by and replication in cells, and their potential for the detection of viruses in population screening, and in infection response monitoring applications. Particular consideration is devoted to recent efforts in the detection of severe acute respiratory syndrome coronavirus 2, and monitoring COVID-19.
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Diagnostic performance of attenuated total reflection Fourier-transform infrared spectroscopy for detecting COVID-19 from routine nasopharyngeal swab samples. Sci Rep 2022; 12:20358. [PMID: 36437268 PMCID: PMC9701801 DOI: 10.1038/s41598-022-24751-z] [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: 03/23/2022] [Accepted: 11/21/2022] [Indexed: 11/28/2022] Open
Abstract
Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with machine learning-based partial least squares discriminant analysis (PLS-DA) was applied to study if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could be detected from nasopharyngeal swab samples originally collected for polymerase chain reaction (PCR) analysis. Our retrospective study included 558 positive and 558 negative samples collected from Northern Finland. Overall, we found moderate diagnostic performance for ATR-FTIR when PCR analysis was used as the gold standard: the average area under the receiver operating characteristics curve (AUROC) was 0.67-0.68 (min. 0.65, max. 0.69) with 20, 10 and 5 k-fold cross validations. Mean accuracy, sensitivity and specificity was 0.62-0.63 (min. 0.60, max. 0.65), 0.61 (min. 0.58, max. 0.65) and 0.64 (min. 0.59, max. 0.67) with 20, 10 and 5 k-fold cross validations. As a conclusion, our study with relatively large sample set clearly indicate that measured ATR-FTIR spectrum contains specific information for SARS-CoV-2 infection (P < 0.001 for AUROC in label permutation test). However, the diagnostic performance of ATR-FTIR remained only moderate, potentially due to low concentration of viral particles in the transport medium. Further studies are needed before ATR-FTIR can be recommended for fast screening of SARS-CoV-2 from nasopharyngeal swab samples.
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Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization. Cancers (Basel) 2022; 14:cancers14225715. [PMID: 36428806 PMCID: PMC9688116 DOI: 10.3390/cancers14225715] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 11/07/2022] [Accepted: 11/09/2022] [Indexed: 11/23/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO2), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO2, lipid and water data were achieved particularly well within the wavelength ranges 350-590 nm and 600-1230 nm for the short-SDD probe, and 380-400 nm, 420-610 nm, and 650-950 nm for the long-SDD probe.
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11
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Zhang D, Guo Y, Zhang L, Wang Y, Peng S, Duan S, Geng L, Zhang X, Wang W, Yang M, Wu G, Chen J, Feng Z, Wang X, Wu Y, Jiang H, Zhang Q, Sun J, Li S, He Y, Xiao M, Xu Y, Wang H, Liu P, Zhou Q, Luo H. Integrated System for On-Site Rapid and Safe Screening of COVID-19. Anal Chem 2022; 94:13810-13819. [PMID: 36184789 PMCID: PMC9578365 DOI: 10.1021/acs.analchem.2c02337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/22/2022] [Indexed: 12/04/2022]
Abstract
Since the outbreak of coronavirus disease 2019 (COVID-19), the epidemic has been spreading around the world for more than 2 years. Rapid, safe, and on-site detection methods of COVID-19 are in urgent demand for the control of the epidemic. Here, we established an integrated system, which incorporates a machine-learning-based Fourier transform infrared spectroscopy technique for rapid COVID-19 screening and air-plasma-based disinfection modules to prevent potential secondary infections. A partial least-squares discrimination analysis and a convolutional neural network model were built using the collected infrared spectral dataset containing 857 training serum samples. Furthermore, the sensitivity, specificity, and prediction accuracy could all reach over 94% from the results of the field test regarding 968 blind testing samples. Additionally, the disinfection modules achieved an inactivation efficiency of 99.9% for surface and airborne tested bacteria. The proposed system is conducive and promising for point-of-care and on-site COVID-19 screening in the mass population.
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Affiliation(s)
- Dongheyu Zhang
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Yuntao Guo
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Liyang Zhang
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Yao Wang
- Department
of Clinical Laboratory, Peking Union Medical
College Hospital, Chinese Academy of Medical Sciences, Beijing100730, China
| | - Siqi Peng
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Simeng Duan
- Department
of Clinical Laboratory, Peking Union Medical
College Hospital, Chinese Academy of Medical Sciences, Beijing100730, China
| | - Lin Geng
- JINSP
Co., Ltd., Beijing100083, China
| | | | - Wei Wang
- Shanghai
Customs Port Clinic, Shanghai International
Travel Healthcare Center, Shanghai200335, China
| | - Mengjie Yang
- Chinese
Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing102206, China
| | - Guizhen Wu
- Chinese
Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing102206, China
| | - Jiayi Chen
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Zihao Feng
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Xinyuan Wang
- Holy-shine
Technology Co., Ltd., Beijing100045, China
| | - Yue Wu
- Holy-shine
Technology Co., Ltd., Beijing100045, China
| | - Haotian Jiang
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Qikang Zhang
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Jingjun Sun
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
| | - Shenwei Li
- Shanghai
Customs Port Clinic, Shanghai International
Travel Healthcare Center, Shanghai200335, China
| | - Yuping He
- Shanghai
Customs Port Clinic, Shanghai International
Travel Healthcare Center, Shanghai200335, China
| | - Meng Xiao
- Department
of Clinical Laboratory, Peking Union Medical
College Hospital, Chinese Academy of Medical Sciences, Beijing100730, China
| | - Yingchun Xu
- Department
of Clinical Laboratory, Peking Union Medical
College Hospital, Chinese Academy of Medical Sciences, Beijing100730, China
| | | | - Peipei Liu
- Chinese
Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing102206, China
| | - Qun Zhou
- Department
of Chemistry, Tsinghua University, Beijing100084, China
| | - Haiyun Luo
- Department
of Electrical Engineering, Tsinghua University, Beijing100084, China
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12
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Lv R, Wang Z, Ma Y, Li W, Tian J. Machine Learning Enhanced Optical Spectroscopy for Disease Detection. J Phys Chem Lett 2022; 13:9238-9249. [PMID: 36173116 DOI: 10.1021/acs.jpclett.2c02193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Optical spectroscopy plays an important role in disease detection. Improving the sensitivity and specificity of spectral detection has great importance in the development of accurate diagnosis. The development of artificial intelligence technology provides a great opportunity to improve the detection accuracy through machine learning methods. In this Perspective, we focus on the combination of machine learning methods with the optical spectroscopy methods widely used for disease detection, including absorbance, fluorescence, scattering, FTIR, terahertz, etc. By comparing the spectral analysis with different machine learning methods, we illustrate that the support vector machine and convolutional neural network are most effective, which have potential to further improve the classification accuracy to distinguish disease subtypes if these machine learning methods are used. This Perspective broadens the scope of optical spectroscopy enhanced by machine learning and will be useful for the development of disease detection.
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Affiliation(s)
- Ruichan Lv
- Interdisciplinary Research Center of Smart Sensor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Zhan Wang
- Interdisciplinary Research Center of Smart Sensor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yaqun Ma
- Interdisciplinary Research Center of Smart Sensor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Wenjing Li
- Interdisciplinary Research Center of Smart Sensor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jie Tian
- Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
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13
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Calvo-Gomez O, Calvo H, Cedillo-Barrón L, Vivanco-Cid H, Alvarado-Orozco JM, Fernandez-Benavides DA, Arriaga-Pizano L, Ferat-Osorio E, Anda-Garay JC, López-Macias C, López MG. Potential of ATR-FTIR-Chemometrics in Covid-19: Disease Recognition. ACS OMEGA 2022; 7:30756-30767. [PMID: 36092630 PMCID: PMC9453986 DOI: 10.1021/acsomega.2c01374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic has caused major disturbances to human health and economy on a global scale. Although vaccination campaigns and important advances in treatments have been developed, an early diagnosis is still crucial. While PCR is the golden standard for diagnosing SARS-CoV-2 infection, rapid and low-cost techniques such as ATR-FTIR followed by multivariate analyses, where dimensions are reduced for obtaining valuable information from highly complex data sets, have been investigated. Most dimensionality reduction techniques attempt to discriminate and create new combinations of attributes prior to the classification stage; thus, the user needs to optimize a wealth of parameters before reaching reliable and valid outcomes. In this work, we developed a method for evaluating SARS-CoV-2 infection and COVID-19 disease severity on infrared spectra of sera, based on a rather simple feature selection technique (correlation-based feature subset selection). Dengue infection was also evaluated for assessing whether selectivity toward a different virus was possible with the same algorithm, although independent models were built for both viruses. High sensitivity (94.55%) and high specificity (98.44%) were obtained for assessing SARS-CoV-2 infection with our model; for severe COVID-19 disease classification, sensitivity is 70.97% and specificity is 94.95%; for mild disease classification, sensitivity is 33.33% and specificity is 94.64%; and for dengue infection assessment, sensitivity is 84.27% and specificity is 94.64%.
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Affiliation(s)
- Octavio Calvo-Gomez
- Centro
de Investigación y de Estudios Avanzados del IPN, Km. 9.6 Libramiento Norte Carretera
Irapuato León, 36824 Irapuato, Guanajuato, Mexico
| | - Hiram Calvo
- Center
for Computing Research, Instituto Politécnico
Nacional, 07738 Mexico City, Mexico
| | - Leticia Cedillo-Barrón
- Centro
de Investigación y de Estudios Avanzados del IPN. Avenida IPN #2508, Col. San Pedro
Zacatenco, CP 07360 Mexico, Distrito Federal, Mexico
| | - Héctor Vivanco-Cid
- Laboratorio
Multidisciplinario en Ciencias Biomédicas, Instituto de Investigaciones
Médico-Biológicas, Universidad
Veracruzana, 91000Veracruz, Mexico
| | - Juan Manuel Alvarado-Orozco
- Centro
de Ingeniería y Desarrollo Industrial, Avenida Playa Pie de la Cuesta No.
702, Desarrollo San Pablo, 76125 Santiago de Querétaro, Mexico
| | - David Andrés Fernandez-Benavides
- Centro
de Ingeniería y Desarrollo Industrial, Avenida Playa Pie de la Cuesta No.
702, Desarrollo San Pablo, 76125 Santiago de Querétaro, Mexico
| | - Lourdes Arriaga-Pizano
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Eduardo Ferat-Osorio
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Juan Carlos Anda-Garay
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Constantino López-Macias
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Mercedes G. López
- Centro
de Investigación y de Estudios Avanzados del IPN, Km. 9.6 Libramiento Norte Carretera
Irapuato León, 36824 Irapuato, Guanajuato, Mexico
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14
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Pandey SK, Mohanta GC, Kumar V, Gupta K. Diagnostic Tools for Rapid Screening and Detection of SARS-CoV-2 Infection. Vaccines (Basel) 2022; 10:1200. [PMID: 36016088 PMCID: PMC9414050 DOI: 10.3390/vaccines10081200] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/19/2022] [Accepted: 07/25/2022] [Indexed: 12/11/2022] Open
Abstract
The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has severely impacted human health and the health management system globally. The ongoing pandemic has required the development of more effective diagnostic strategies for restricting deadly disease. For appropriate disease management, accurate and rapid screening and isolation of the affected population is an efficient means of containment and the decimation of the disease. Therefore, considerable efforts are being directed toward the development of rapid and robust diagnostic techniques for respiratory infections, including SARS-CoV-2. In this article, we have summarized the origin, transmission, and various diagnostic techniques utilized for the detection of the SARS-CoV-2 virus. These higher-end techniques can also detect the virus copy number in asymptomatic samples. Furthermore, emerging rapid, cost-effective, and point-of-care diagnostic devices capable of large-scale population screening for COVID-19 are discussed. Finally, some breakthrough developments based on spectroscopic diagnosis that could revolutionize the field of rapid diagnosis are discussed.
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Affiliation(s)
- Satish Kumar Pandey
- Department of Biotechnology, School of Life Sciences, Mizoram University (Central University), Aizawl 796004, India
| | - Girish C. Mohanta
- Materials Science and Sensor Applications, CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh 160030, India;
| | - Vinod Kumar
- Department of Dermatology, Venerology and Leprology, Post Graduate Institute of Medical Education & Research, Chandigarh 160012, India;
| | - Kuldeep Gupta
- Russel H. Morgan, Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
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15
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Guleken Z, Tuyji Tok Y, Jakubczyk P, Paja W, Pancerz K, Shpotyuk Y, Cebulski J, Depciuch J. Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level. MEASUREMENT : JOURNAL OF THE INTERNATIONAL MEASUREMENT CONFEDERATION 2022; 196:111258. [PMID: 35493849 PMCID: PMC9040476 DOI: 10.1016/j.measurement.2022.111258] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/20/2022] [Accepted: 04/22/2022] [Indexed: 05/07/2023]
Abstract
In this research, blood samples of 47 patients infected by COVID were analyzed. The samples were taken on the 1st, 3rd and 6th month after the detection of COVID infection. Total antibody levels were measured against the SARS-CoV-2 N antigen and surrogate virus neutralization by serological methods. To differentiate COVID patients with different antibody levels, Fourier Transform InfraRed (FTIR) and Raman spectroscopy methods were used. The spectroscopy data were analyzed by multivariate analysis, machine learning and neural network methods. It was shown, that analysis of serum using the above-mentioned spectroscopy methods allows to differentiate antibody levels between 1 and 6 months via spectral biomarkers of amides II and I. Moreover, multivariate analysis showed, that using Raman spectroscopy in the range between 1317 cm-1 and 1432 cm-1, 2840 cm-1 and 2956 cm-1 it is possible to distinguish patients after 1, 3, and 6 months from COVID with a sensitivity close to 100%.
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Affiliation(s)
- Zozan Guleken
- Uskudar University, Faculty of Medicine, Department of Physiology, Turkey
| | - Yeşim Tuyji Tok
- Department of Medical Microbiology, Cerrahpaşa Medical Faculty, İstanbul University-Cerrahpaşa, Turkey
| | | | - Wiesław Paja
- Institute of Computer Science, University of Rzeszow, Poland
| | - Krzysztof Pancerz
- Institute of Philosophy, John Paul II Catholic University of Lublin, Poland
| | | | | | - Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Science, 31-342 Krakow, Poland
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16
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Raypah ME, Faris AN, Mohd Azlan M, Yusof NY, Suhailin FH, Shueb RH, Ismail I, Mustafa FH. Near-Infrared Spectroscopy as a Potential COVID-19 Early Detection Method: A Review and Future Perspective. SENSORS 2022; 22:s22124391. [PMID: 35746172 PMCID: PMC9229781 DOI: 10.3390/s22124391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/16/2022] [Accepted: 05/23/2022] [Indexed: 02/05/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic is a worldwide health anxiety. The rapid dispersion of the infection globally results in unparalleled economic, social, and health impacts. The pathogen that causes COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A fast and low-cost diagnosis method for COVID-19 disease can play an important role in controlling its proliferation. Near-infrared spectroscopy (NIRS) is a quick, non-destructive, non-invasive, and inexpensive technique for profiling the chemical and physical structures of a wide range of samples. Furthermore, the NIRS has the advantage of incorporating the internet of things (IoT) application for the effective control and treatment of the disease. In recent years, a significant advancement in instrumentation and spectral analysis methods has resulted in a remarkable impact on the NIRS applications, especially in the medical discipline. To date, NIRS has been applied as a technique for detecting various viruses including zika (ZIKV), chikungunya (CHIKV), influenza, hepatitis C, dengue (DENV), and human immunodeficiency (HIV). This review aims to outline some historical and contemporary applications of NIRS in virology and its merit as a novel diagnostic technique for SARS-CoV-2.
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Affiliation(s)
- Muna E. Raypah
- School of Physics, Universiti Sains Malaysia, George Town 11800, Pulau Pinang, Malaysia;
| | - Asma Nadia Faris
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia Health Campus, Kubang Kerian 16150, Kelantan, Malaysia; (A.N.F.); (M.M.A.); (N.Y.Y.); (R.H.S.)
| | - Mawaddah Mohd Azlan
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia Health Campus, Kubang Kerian 16150, Kelantan, Malaysia; (A.N.F.); (M.M.A.); (N.Y.Y.); (R.H.S.)
| | - Nik Yusnoraini Yusof
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia Health Campus, Kubang Kerian 16150, Kelantan, Malaysia; (A.N.F.); (M.M.A.); (N.Y.Y.); (R.H.S.)
| | - Fariza Hanim Suhailin
- Department of Physics, Faculty of Science, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia;
| | - Rafidah Hanim Shueb
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia Health Campus, Kubang Kerian 16150, Kelantan, Malaysia; (A.N.F.); (M.M.A.); (N.Y.Y.); (R.H.S.)
- Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
| | - Irneza Ismail
- Advanced Devices & System (ADS) Research Group, Department of Electrical & Electronic Engineering, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Bandar Baru Nilai, Nilai 71800, Negeri Sembilan, Malaysia
- Correspondence: (I.I.); (F.H.M.); Tel.: +60-7986569 (I.I.); +60-9-7672432 (F.H.M.)
| | - Fatin Hamimi Mustafa
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia Health Campus, Kubang Kerian 16150, Kelantan, Malaysia; (A.N.F.); (M.M.A.); (N.Y.Y.); (R.H.S.)
- Correspondence: (I.I.); (F.H.M.); Tel.: +60-7986569 (I.I.); +60-9-7672432 (F.H.M.)
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17
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Bandeira CCS, Madureira KCR, Rossi MB, Gallo JF, da Silva APMA, Torres VL, de Lima VA, Júnior NK, Almeida JD, Zerbinati RM, Braz-Silva PH, Lindoso JAL, da Silva Martinho H. Micro-Fourier-transform infrared reflectance spectroscopy as tool for probing IgG glycosylation in COVID-19 patients. Sci Rep 2022; 12:4269. [PMID: 35277543 PMCID: PMC8914452 DOI: 10.1038/s41598-022-08156-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 02/23/2022] [Indexed: 12/13/2022] Open
Abstract
It has been reported that patients diagnosed with COVID-19 become critically ill primarily around the time of activation of the adaptive immune response. However the role of antibodies in the worsening of disease is not obvious. Higher titers of anti-spike immunoglobulin IgG1 associated with low fucosylation of the antibody Fc tail have been associated to excessive inflammatory response. In contrast it has been also reported that NP-, S-, RBD- specific IgA, IgG, and IgM are not associated with SARS-CoV-2 viral load, indicating that there is no obvious correlation between antibody response and viral antigen detection. In the present work the micro-Fourier-transform infrared reflectance spectroscopy (micro-FTIR) was employed to investigate blood serum samples of healthy and COVID-19-ill (mild or oligosymptomatic) individuals (82 healthcare workers volunteers in “Instituto de Infectologia Emilio Ribas”, São Paulo, Brazil). The molecular-level-sensitive, multiplexing quantitative and qualitative FTIR data probed on 1 µL of dried biofluid was compared to signal-to-cutoff index of chemiluminescent immunoassays CLIA and ELISA (IgG antibodies against SARS-CoV-2). Our main result indicated that 1702–1785 \documentclass[12pt]{minimal}
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\begin{document}$$\hbox {cm}^{-1}$$\end{document}cm-1 spectral window (carbonyl C=O vibration) is a spectral marker of the degree of IgG glycosylation, allowing to probe distinctive sub-populations of COVID-19 patients, depending on their degree of severity. The specificity was 87.5 % while the detection rate of true positive was 100%. The computed area under the receiver operating curve was equivalent to CLIA, ELISA and other ATR-FTIR methods (\documentclass[12pt]{minimal}
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\begin{document}$$>0.85$$\end{document}>0.85). In summary, overall discrimination of healthy and COVID-19 individuals and severity prediction as well could be potentially implemented using micro-FTIR reflectance spectroscopy on blood serum samples. Considering the minimal and reagent-free sample preparation procedures combined to fast (few minutes) outcome of FTIR we can state that this technology is suitable for fast screening of immune response of individuals with COVID-19. It would be an important tool in prospective studies, helping investigate the physiology of the asymptomatic, oligosymptomatic, or severe individuals and measure the extension of infection dissemination in patients.
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Affiliation(s)
| | | | - Meire Bocoli Rossi
- Instituto de Infectologia Emilio Ribas, São Paulo, Sp, 01246-900, Brazil
| | | | | | | | - Vinicius Alves de Lima
- Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, SP, 05403-000, Brazil
| | - Norival Kesper Júnior
- Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, SP, 05403-000, Brazil
| | - Janete Dias Almeida
- Departamento de Biociências e Diagnêstico, Instituto de Ciência e Tecnologia, Universidade Estadual Paulista, São José dos Campos, SP, 12245-000, Brazil
| | - Rodrigo Melim Zerbinati
- Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, SP, 05403-000, Brazil
| | - Paulo Henrique Braz-Silva
- Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, SP, 05403-000, Brazil.,Faculdade de Odontologia Departamento de Estomatologia, Universidade de São Paulo, São Paulo, SP, 05508-000, Brazil
| | - José Angelo Lauletta Lindoso
- Instituto de Infectologia Emilio Ribas, São Paulo, Sp, 01246-900, Brazil.,Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, SP, 05403-000, Brazil.,Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, 01255-090, Brazil
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18
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Schorer V, Haas J, Stach R, Kokoric V, Groß R, Muench J, Hummel T, Sobek H, Mennig J, Mizaikoff B. Towards the direct detection of viral materials at the surface of protective face masks via infrared spectroscopy. Sci Rep 2022; 12:2309. [PMID: 35145194 PMCID: PMC8831636 DOI: 10.1038/s41598-022-06335-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 01/21/2022] [Indexed: 11/29/2022] Open
Abstract
The ongoing COVID-19 pandemic represents a considerable risk for the general public and especially for health care workers. To avoid an overloading of the health care system and to control transmission chains, the development of rapid and cost-effective techniques allowing for the reliable diagnosis of individuals with acute respiratory infections are crucial. Uniquely, the present study focuses on the development of a direct face mask sampling approach, as worn (i.e., used) disposable face masks contain exogenous environmental constituents, as well as endogenously exhaled breath aerosols. Optical techniques—and specifically infrared (IR) molecular spectroscopic techniques—are promising tools for direct virus detection at the surface of such masks. In the present study, a rapid and non-destructive approach for monitoring exposure scenarios via medical face masks using attenuated total reflection infrared spectroscopy is presented. Complementarily, IR external reflection spectroscopy was evaluated in comparison for rapid mask analysis. The utility of a face mask-based sampling approach was demonstrated by differentiating water, proteins, and virus-like particles sampled onto the mask. Data analysis using multivariate statistical algorithms enabled unambiguously classifying spectral signatures of individual components and biospecies. This approach has the potential to be extended towards the rapid detection of SARS-CoV-2—as shown herein for the example of virus-like particles which are morphologically equivalent to authentic virus—without any additional sample preparation or elaborate testing equipment at laboratory facilities. Therefore, this strategy may be implemented as a routine large-scale monitoring routine, e.g., at health care institutions, nursing homes, etc. ensuring the health and safety of medical personnel.
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Affiliation(s)
- Vanessa Schorer
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081, Ulm, Germany
| | - Julian Haas
- Hahn-Schickard, Sedanstraße 14, 89077, Ulm, Germany
| | - Robert Stach
- Hahn-Schickard, Sedanstraße 14, 89077, Ulm, Germany
| | | | - Rüdiger Groß
- Institute of Molecular Virology, Ulm University Medical Center, Meyerhofstr. 1, 89081, Ulm, Germany
| | - Jan Muench
- Institute of Molecular Virology, Ulm University Medical Center, Meyerhofstr. 1, 89081, Ulm, Germany
| | - Tim Hummel
- Labor Dr. Merk & Kollegen GmbH, Beim Braunland 1, 88416, Ochsenhausen, Germany.,Boehringer Ingelheim Therapeutics GmbH, Beim Braunland 1, 88416, Ochsenhausen, Germany
| | - Harald Sobek
- Labor Dr. Merk & Kollegen GmbH, Beim Braunland 1, 88416, Ochsenhausen, Germany
| | - Jan Mennig
- Labor Dr. Merk & Kollegen GmbH, Beim Braunland 1, 88416, Ochsenhausen, Germany
| | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081, Ulm, Germany. .,Hahn-Schickard, Sedanstraße 14, 89077, Ulm, Germany.
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