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Han L, Ma F, He P, Zhou Q, Li Z, Sun S. Multi-spectroscopic characterization of organic salt components in medicinal plant. Food Chem 2024; 450:139195. [PMID: 38615525 DOI: 10.1016/j.foodchem.2024.139195] [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: 11/25/2023] [Revised: 03/23/2024] [Accepted: 03/28/2024] [Indexed: 04/16/2024]
Abstract
The characterization of structure of organic salts in complex mixtures has been a difficult problem in analytical chemistry. In the analysis of Scutellariae Radix (SR), the pharmacopoeia of many countries stipulates that the quality control component is baicalin (≥9% by high performance liquid chromatography (HPLC)). The component with highest response in SR was also baicalin detected by liquid chromatography-mass spectrometry (LC-MS). However, in the attenuated total reflection Fourier transform infrared spectroscopy, the carbonyl peak of glucuronic acid of baicalin did not appear in SR. The results of element analysis, time of flight secondary ion mass spectrometry, matrix assisted laser desorption ionization mass spectrometry and solid-state nuclear magnetic resonance all supported the existence of baicalin magnesium salt. Based on this, this study proposes an analysis strategy guided by infrared spectroscopy and combined with multi-spectroscopy techniques to analyze the structure of organic salt components in medicinal plant. It is meaningful for the research of mechanisms, development of new drugs, and quality control.
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Affiliation(s)
- Lingyu Han
- School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China; Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, China
| | - Fang Ma
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Ping He
- State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, China University of Mining and Technology-Beijing, Beijing 100083, China
| | - Qun Zhou
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, China.
| | - Zhanping Li
- Department of Chemistry, Key Laboratory of Organic Optoelectronics and Molecular Engineering of Ministry of Education, Tsinghua University, Beijing 100084, China.
| | - Suqin Sun
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, China.
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Hu D, Li Z, Wang R, Gao X, Mou M, Xiang N. Improved discrimination of COVID-19 based on data enhancement technology and an information balance feature selection (INB) method. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 308:123742. [PMID: 38113559 DOI: 10.1016/j.saa.2023.123742] [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: 07/25/2023] [Revised: 12/01/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023]
Abstract
The coronavirus disease (COVID-19) ravaged the world in late 2019 and posed a serious threat to human life and property destruction on a global scale. In this paper, the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) method was selected for balancing the data sample, and an information balance feature selection (INB) method was first proposed to realize the accurate discrimination of COVID-19 saliva samples based on the attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. The results of the experiment showed that the INB method obtained higher classification accuracy than the traditional feature selection methods in both the original spectrum and the second-order derivative spectrum, especially in the second-order derivative spectrum where all the indexes reached about 85 %. In addition, the combination of WGAN_GP data augmentation and the INB method resulted in an accuracy of 88.7 % for the original spectrum and even 90.6 % for the second-order derivative spectrum. According to these findings, classification research using the WGAN_GP data enhancement model may increase classification accuracy. Additionally, the ability to successfully separate COVID-19 indicates that the INB method to identify spectral data features is a workable method, which also offers a fresh viewpoint on feature selection.
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Affiliation(s)
- Dean Hu
- College of Information Science and Engineering, Northeastern University, Shenyang 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
| | - Zhigang Li
- College of Information Science and Engineering, Northeastern University, Shenyang 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China.
| | - Ruixin Wang
- College of Information Science and Engineering, Northeastern University, Shenyang 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
| | - Xuning Gao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110819, China
| | - Mingkai Mou
- College of Information Science and Engineering, Northeastern University, Shenyang 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
| | - Nan Xiang
- College of Information Science and Engineering, Northeastern University, Shenyang 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
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3
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Cheng Q, Li T. Complex-frequency waves: beat loss and win sensitivity. LIGHT, SCIENCE & APPLICATIONS 2024; 13:40. [PMID: 38296959 PMCID: PMC10831086 DOI: 10.1038/s41377-024-01388-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Recent experiments have demonstrated that synthesized complex-frequency waves can impart a virtual gain to molecule sensing systems, which can effectively restore information lost due to intrinsic molecular damping. The enhancement notably amplifies the signal of trace molecular vibrational fingerprints, thereby substantially improving the upper limit of sensitivity.
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Affiliation(s)
- Qingqing Cheng
- School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
- Department of Respiratory Diseases and Critical Medicine, Quzhou Hospital Affiliated to Wenzhou Medical University, Quzhou, 324000, China
| | - Tao Li
- National Laboratory of Solid State Microstructures, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China.
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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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das Chagas E Silva de Carvalho LF, de Lima Morais TM, Nogueira MS. Providing potential solutions by using FT-IR spectroscopy for biofluid analysis: Clinical impact of optical screening and diagnostic tests. Photodiagnosis Photodyn Ther 2023; 44:103753. [PMID: 37597683 DOI: 10.1016/j.pdpdt.2023.103753] [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: 05/17/2023] [Revised: 08/02/2023] [Accepted: 08/15/2023] [Indexed: 08/21/2023]
Abstract
BACKGROUND Currently, the potential of FT-IR spectroscopy for rapid diagnosis of many pathologies has been demonstrated by numerous research studies including those targeting COVID-19 detection. However, the number of clinicians aware of this potential and who are willing to use spectroscopy in their clinics and hospitals is still negligible. In addition, lack of awareness creates a huge gap between clinicians and researchers involved in clinical translation of current FT-IR technology hence hindering initiatives to bring basic and applied research together for the direct benefit of patients. METHODS Knowledge and medical training on FT-IR on the side of clinicians should be one of the first steps to be able to integrate it into the list of complementary exams which may be requested by health professionals. Countless FT-IR applications could have a life-changing impact on patients' lives, especially screening and diagnostic tests involving biofluids such as blood, saliva and urine which are routinely non-invasively or minimally-invasively. RESULTS Blood may be the most difficult to obtain by the invasive method of collection, but much can be evaluated in its components, and areas such as hematology, infectiology, oncology and endocrinology can be directly benefited. Urine with a relatively simple collection method can provide pertinent information from the entire urinary system, including the actual condition of the kidneys. Saliva collection can be simpler for the patient and can provide information on diseases affecting the mouth and digestive system and can be used to diagnose diseases such as oral cancer in its early-stages. An unavoidable second step is the active involvement of industries to design robust and portable instruments for specific purposes, as the medical community requires user-friendly instruments of advanced computational algorithms. A third step resides in the legal situation involving the global use of the technique as a new diagnostic modality. CONCLUSIONS It is important to note that decentralized funds for variety of technologies hinders the training of clinical and medical professionals for the use of newly arising technologies and affect the engagement of these professionals with technology developers. As a result of decentralized funding, research efforts are spread out over a range of technologies which take a long time to get validated and translated to the clinic. Partnership over similar groups of technologies and efforts to test the same technologies while overcoming barriers posed to technology validation in different areas around the globe may benefit the clinical/medical, research and industry community globally.
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Affiliation(s)
| | | | - Marcelo Saito Nogueira
- Tyndall National Institute, Lee Maltings, Dyke Parade, Cork T12 R5CP, Ireland; Department of Physics, University College Cork, College Road, Cork T12 K8AF, Ireland.
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Hackshaw KV, Yao S, Bao H, de Lamo Castellvi S, Aziz R, Nuguri SM, Yu L, Osuna-Diaz MM, Brode WM, Sebastian KR, Giusti MM, Rodriguez-Saona L. Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics. Biomedicines 2023; 11:2704. [PMID: 37893078 PMCID: PMC10604557 DOI: 10.3390/biomedicines11102704] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/01/2023] [Accepted: 10/03/2023] [Indexed: 10/29/2023] Open
Abstract
Post Acute Sequelae of SARS-CoV-2 infection (PASC or Long COVID) is characterized by lingering symptomatology post-initial COVID-19 illness that is often debilitating. It is seen in up to 30-40% of individuals post-infection. Patients with Long COVID (LC) suffer from dysautonomia, malaise, fatigue, and pain, amongst a multitude of other symptoms. Fibromyalgia (FM) is a chronic musculoskeletal pain disorder that often leads to functional disability and severe impairment of quality of life. LC and FM share several clinical features, including pain that often makes them indistinguishable. The aim of this study is to develop a metabolic fingerprinting approach using portable Fourier-transform mid-infrared (FT-MIR) spectroscopic techniques to diagnose clinically similar LC and FM. Blood samples were obtained from LC (n = 50) and FM (n = 50) patients and stored on conventional bloodspot protein saver cards. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. Through the deconvolution analysis of the spectral data, a distinct spectral marker at 1565 cm-1 was identified based on a statistically significant analysis, only present in FM patients. This IR band has been linked to the presence of side chains of glutamate. An OPLS-DA algorithm created using the spectral region 1500 to 1700 cm-1 enabled the classification of the spectra into their corresponding classes (Rcv > 0.96) with 100% accuracy and specificity. This high-throughput approach allows unique metabolic signatures associated with LC and FM to be identified, allowing these conditions to be distinguished and implemented for in-clinic diagnostics, which is crucial to guide future therapeutic approaches.
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Affiliation(s)
- Kevin V. Hackshaw
- Department of Internal Medicine, Division of Rheumatology, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
| | - Siyu Yao
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
| | - Haona Bao
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
| | - Silvia de Lamo Castellvi
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
- Campus Sescelades, Departament d’Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain
| | - Rija Aziz
- Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA; (R.A.); (M.M.O.-D.); (W.M.B.); (K.R.S.)
| | - Shreya Madhav Nuguri
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
| | - Lianbo Yu
- Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH 43210, USA;
| | - Michelle M. Osuna-Diaz
- Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA; (R.A.); (M.M.O.-D.); (W.M.B.); (K.R.S.)
| | - W. Michael Brode
- Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA; (R.A.); (M.M.O.-D.); (W.M.B.); (K.R.S.)
| | - Katherine R. Sebastian
- Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA; (R.A.); (M.M.O.-D.); (W.M.B.); (K.R.S.)
| | - M. Monica Giusti
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
| | - Luis Rodriguez-Saona
- Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA; (S.Y.); (H.B.); (S.d.L.C.); (S.M.N.); (M.M.G.); (L.R.-S.)
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Goulart ACC, Zângaro RA, Carvalho HC, Lednev IK, Silveira L. Diagnosing COVID-19 in nasopharyngeal secretion through Raman spectroscopy: a feasibility study. Lasers Med Sci 2023; 38:210. [PMID: 37698685 DOI: 10.1007/s10103-023-03871-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 08/29/2023] [Indexed: 09/13/2023]
Abstract
Since the beginning of the COVID-19 pandemic, the scientific community has sought to develop fast and accurate techniques for detecting the SARS-CoV-2 virus. Raman spectroscopy is a promising technique for diagnosing COVID-19 through serum samples. In the present study, the diagnosis of COVID-19 through nasopharyngeal secretion has been proposed. Raman spectra from nasopharyngeal secretion samples (15 Control, negative and 12 COVID-19, positive, assayed by immunofluorescence antigen test) were obtained in triplicate in a dispersive Raman spectrometer (830 nm, 350 mW), accounting for a total of 80 spectra. Using principal component analysis (PCA) the main spectral differences between the Control and COVID-19 samples were attributed to N and S proteins from the virus in the COVID-19 group. Features assigned to mucin (serine, threonine and proline amino acids) were observed in the Control group. A binary model based on partial least squares discriminant analysis (PLS-DA) differentiated COVID-19 versus Control samples with accuracy of 91%, sensitivity of 80% and specificity of 100%. Raman spectroscopy has a great potential for becoming a technique of choice for rapid and label-free evaluation of nasopharyngeal secretion for COVID-19 diagnosis.
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Affiliation(s)
| | - Renato Amaro Zângaro
- Universidade Anhembi Morumbi - UAM, R. Casa do Ator, 275, São Paulo, SP, 04546-001, Brazil
- Center for Innovation, Technology and Education - CITÉ, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil
| | - Henrique Cunha Carvalho
- Center for Innovation, Technology and Education - CITÉ, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil
- Federal University of Technology - Paraná - UTFPR, Via Marginal Rosalina Maria dos Santos, 1233, Bl. B, Campo Mourão, PR, 87301-899, Brazil
| | - Igor K Lednev
- Department of Chemistry, University at Albany - SUNY, 1400 Washington Av., Albany, NY, 12222, USA
| | - Landulfo Silveira
- Universidade Anhembi Morumbi - UAM, R. Casa do Ator, 275, São Paulo, SP, 04546-001, Brazil.
- Center for Innovation, Technology and Education - CITÉ, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil.
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8
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Guleken Z, Ceylan Z, Aday A, Bayrak AG, Hindilerden İY, Nalçacı M, Jakubczyk P, Jakubczyk D, Depciuch J. FTIR- based serum structure analysis in molecular diagnostics of essential thrombocythemia disease. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2023; 245:112734. [PMID: 37295134 DOI: 10.1016/j.jphotobiol.2023.112734] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/18/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023]
Abstract
Essential thrombocythemia (ET) reflects the transformation of a multipotent hematopoietic stem cell, but its molecular pathogenesis remains obscure. Nevertheless, tyrosine kinase, especially Janus kinase 2 (JAK2), has been implicated in myeloproliferative disorders other than chronic myeloid leukaemia. FTIR analysis was performed on the blood serum of 86 patients and 45 healthy volunteers as control with FTIR spectra-based machine learning methods and chemometrics. Thus, the study aimed to determine biomolecular changes and separation of ET and healthy control groups illustration by applying chemometrics and ML techniques to spectral data. The FTIR-based results showed that in ET disease with JAK2 mutation, there are alterations in functional groups associated with lipids, proteins and nucleic acids significantly. Moreover, in ET patients the lower amount of proteins with simultaneously higher amount of lipids was noted in comparison with the control one. Furthermore, the SVM-DA model showed 100% accuracy in calibration sets in both spectral regions and 100.0% and 96.43% accuracy in prediction sets for the 800-1800 cm-1 and 2700-3000 cm-1 spectral regions, respectively. While changes in the dynamic spectra showed that CH2 bending, amide II and CO vibrations could be used as a spectroscopy marker of ET. Finally, it was found a positive correlation between FTIR peaks and first bone marrow fibrosis degree, as well as the absence of JAK2 V617F mutation. The findings of this study contribute to a better understanding of the molecular pathogenesis of ET and identifying biomolecular changes and may have implications for early diagnosis and treatment of this disease.
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Affiliation(s)
- Zozan Guleken
- Department of Physiology, Faculty of Medicine, Gaziantep, Islam, Science and Technology University, 27220, Gaziantep, Turkey.
| | - Zeynep Ceylan
- Samsun University, Faculty of Engineering, Department of Industrial Engineering, Turkey
| | - Aynur Aday
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - Ayşe Gül Bayrak
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - İpek Yönal Hindilerden
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | - Meliha Nalçacı
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | | | - Dorota Jakubczyk
- Faculty of Mathematics and Applied Physics, Rzeszow University of Technology, Powstancow Warszawy 12, PL-35959 Rzeszow, Poland
| | - Joanna Depciuch
- Institute of Nuclear Physics, PAS, 31342 Krakow, Poland; Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093 Lublin, Poland
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9
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Zhang Q, Zhao L, Qi G, Zhang X, Tian C. Raman and fourier transform infrared spectroscopy techniques for detection of coronavirus (COVID-19): a mini review. Front Chem 2023; 11:1193030. [PMID: 37273513 PMCID: PMC10232992 DOI: 10.3389/fchem.2023.1193030] [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: 03/24/2023] [Accepted: 05/01/2023] [Indexed: 06/06/2023] Open
Abstract
Coronavirus pandemic has been a huge jeopardy to human health in various systems since it outbroke, early detection and prevention of further escalation has become a priority. The current popular approach is to collect samples using the nasopharyngeal swab method and then test for RNA using the real-time polymerase chain reaction, which suffers from false-positive results and a longer diagnostic time scale. Alternatively, various optical techniques, namely, optical sensing, spectroscopy, and imaging shows a great promise in virus detection. In this mini review, we briefly summarize the development progress of vibrational spectroscopy techniques and its applications in the detection of SARS-CoV family. Vibrational spectroscopy techniques such as Raman spectroscopy and infrared spectroscopy received increasing appreciation in bio-analysis for their speediness, accuracy and cost-effectiveness in detection of SARS-CoV. Further, an account of emerging photonics technologies of SARS-CoV-2 detection and future possibilities is also explained. The progress in the field of vibrational spectroscopy techniques for virus detection unambiguously show a great promise in the development of rapid photonics-based devices for COVID-19 detection.
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Affiliation(s)
- Qiuqi Zhang
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Lei Zhao
- Shandong Provincial Key Laboratory of Detection Technology for Tumor Markers, Collaborative Innovation Center of Tumor Marker Detection Technology, Equipment and Diagnosis-Therapy Integration in Universities of Shandong, College of Chemistry and Chemical Engineering, Linyi University, Linyi, China
| | - Guoliang Qi
- Shandong Provincial Key Laboratory of Detection Technology for Tumor Markers, Collaborative Innovation Center of Tumor Marker Detection Technology, Equipment and Diagnosis-Therapy Integration in Universities of Shandong, College of Chemistry and Chemical Engineering, Linyi University, Linyi, China
| | - Xiaoru Zhang
- Key Laboratory of Optic-Electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis and College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao, China
| | - Cheng Tian
- Shandong Provincial Key Laboratory of Detection Technology for Tumor Markers, Collaborative Innovation Center of Tumor Marker Detection Technology, Equipment and Diagnosis-Therapy Integration in Universities of Shandong, College of Chemistry and Chemical Engineering, Linyi University, Linyi, China
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10
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Li Z, Zhao Y, You T, Zhu J, Xia M, Lu P, Zhang X, Xu Y. Infrared Evanescent Wave Sensing Based on a Ge 10As 30Se 40Te 20 Fiber for Alcohol Detection. SENSORS (BASEL, SWITZERLAND) 2023; 23:4841. [PMID: 37430755 DOI: 10.3390/s23104841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/16/2023] [Accepted: 05/16/2023] [Indexed: 07/12/2023]
Abstract
Infrared evanescent wave sensing based on chalcogenide fiber is an emerging technology for qualitative and quantitative analysis of most organic compounds. Here, a tapered fiber sensor made from Ge10As30Se40Te20 glass fiber was reported. The fundamental modes and intensity of evanescent waves in fibers with different diameters were simulated with COMSOL. The 30 mm length tapered fiber sensors with different waist diameters, 110, 63, and 31 μm, were fabricated for ethanol detection. The sensor with a waist diameter of 31 μm has the highest sensitivity of 0.73 a.u./% and a limit of detection (LoD) of 0.195 vol.% for ethanol. Finally, this sensor has been used to analyze alcohols, including Chinese baijiu (Chinese distilled spirits), red wine, Shaoxing wine (Chinese rice wine), Rio cocktail, and Tsingtao beer. It is shown that the ethanol concentration is consistent with the nominal alcoholicity. Moreover, other components such as CO2 and maltose can be detected in Tsingtao beer, demonstrating the feasibility of its application in detecting food additives.
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Affiliation(s)
- Zijian Li
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - Yongkun Zhao
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - Tianxiang You
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - Jihong Zhu
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
- State Key Laboratory of Optical Fiber and Cable Manufacture Technology, Yangtze Optical Fibre and Cable Joint Stock Limited Company (YOFC), Wuhan 430073, China
| | - Mengling Xia
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - Ping Lu
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
- School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - Xianghua Zhang
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
- Institut Des Sciences Chimiques de Rennes UMR 6226, Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1, 35042 Rennes, France
| | - Yinsheng Xu
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
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11
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Dou J, Dawuti W, Zheng X, Zhu Y, Lin R, Lü G, Zhang Y. Rapid discrimination of Brucellosis in sheep using serum Fourier transform infrared spectroscopy combined with PCA-LDA algorithm. Photodiagnosis Photodyn Ther 2023; 42:103567. [PMID: 37084931 DOI: 10.1016/j.pdpdt.2023.103567] [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: 02/25/2023] [Revised: 04/09/2023] [Accepted: 04/11/2023] [Indexed: 04/23/2023]
Abstract
Brucellosis in sheep is an infectious disease caused by Brucella melitensis in sheep. The current conventional serological methods for screening Brucella-infected sheep have the disadvantage of time consuming and low accuracy, so a simple, rapid and highly accurate screening method is needed. The aim of this study was to evaluate the feasibility of diagnosing Brucella-infected sheep by serum samples based on the Fourier transform infrared (FTIR) spectroscopy. In this study, FTIR spectroscopy of serum from Brucella-infected sheep (n=102) and healthy sheep (n=125) revealed abnormal protein and lipid metabolism in serum from Brucella-infected sheep compared to healthy sheep. Principal component analysis-Linear discriminant analysis (PCA-LDA) method was used to differentiate the FTIR spectra of serum from Brucella-infected sheep and healthy sheep in the protein band (3700-3090 cm-1) and lipid band (3000-2800 cm-1), and its overall diagnostic accuracy was 100% (sensitivity 100%, specificity 100%). In conclusion, our results suggest that serum FTIR spectroscopy combined with PCA-LDA algorithm has great potential for brucellosis in sheep screening.
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Affiliation(s)
- Jingrui Dou
- School of Public Health, Xinjiang Medical University, Urumqi 830054, China; State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
| | - Wubulitalifu Dawuti
- School of Public Health, Xinjiang Medical University, Urumqi 830054, China; State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
| | - Xiangxiang Zheng
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Yousen Zhu
- Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi Xinjiang 830054, China
| | - Renyong Lin
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
| | - Guodong Lü
- School of Public Health, Xinjiang Medical University, Urumqi 830054, China; State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China.
| | - Yujiang Zhang
- School of Public Health, Xinjiang Medical University, Urumqi 830054, China; The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi 830002, China.
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12
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Li Y, Zhao S, Xu Z, Qiao X, Li M, Li Y, Luo X. Peptide nucleic acid and antifouling peptide based biosensor for the non-fouling detection of COVID-19 nucleic acid in saliva. Biosens Bioelectron 2023; 225:115101. [PMID: 36708624 DOI: 10.1016/j.bios.2023.115101] [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: 11/03/2022] [Revised: 12/24/2022] [Accepted: 01/23/2023] [Indexed: 01/26/2023]
Abstract
The electrochemical biosensor with outstanding sensitivity and low cost is regarded as a viable alternative to current clinical diagnostic techniques for various disease biomarkers. However, their actual analytical use in complex biological samples is severely hampered due to the biofouling, as they are also highly sensitive to nonspecific adsorption on the sensing interfaces. Herein, we have constructed a non-fouling electrochemical biosensor based on antifouling peptides and the electroneutral peptide nucleic acid (PNA), which was used as the recognizing probe for the specific binding of the viral RNA of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Different from the negatively charged DNA probes that will normally weaken the biosensors' antifouling capabilities owing to the charge attraction of positively charged biomolecules, the neutral PNA probe will generate no side-effects on the biosensor. The biosensor demonstrated remarkable sensitivity in detecting SARS-CoV-2 viral RNA, possessing a broad linear range (1.0 fM - 1.0 nM) and a detection limit down to 0.38 fM. Furthermore, the sensing performance of the constructed electrochemical biosensor in human saliva was nearly similar to that in pure buffer, indicating satisfying antifouling capability. The combination of PNA probes with antifouling peptides offered a new strategy for the development of non-fouling sensing systems capable of assaying trace disease biomarkers in complicated biological media.
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Affiliation(s)
- Yanxin Li
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Shuju Zhao
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Zhenying Xu
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Xiujuan Qiao
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Mingxuan Li
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Youke Li
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China
| | - Xiliang Luo
- Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, Shandong Key Laboratory of Biochemical Analysis, College of Chemistry and Molecular Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China.
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13
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Karas BY, Sitnikova VE, Nosenko TN, Dedkov VG, Arsentieva NA, Gavrilenko NV, Moiseev IS, Totolian AA, Kajava AV, Uspenskaya MV. ATR-FTIR spectrum analysis of plasma samples for rapid identification of recovered COVID-19 individuals. JOURNAL OF BIOPHOTONICS 2023:e202200166. [PMID: 36869427 DOI: 10.1002/jbio.202200166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 01/08/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
The development of fast, cheap and reliable methods to determine seroconversion against infectious agents is of great practical importance. In the context of the COVID-19 pandemic, an important issue is to study the rate of formation of the immune layer in the population of different regions, as well as the study of the formation of post-vaccination immunity in individuals after vaccination. Currently, the main method for this kind of research is enzyme immunoassay (ELISA, enzyme-linked immunosorbent assay). This technique is sufficiently sensitive and specific, but it requires significant time and material costs. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in blood plasma to detect seroconversion against SARS-CoV-2. The study included samples of 60 patients. Clear spectral differences in plasma samples from recovered COVID-19 patients and conditionally healthy donors were identified using multivariate and statistical analysis. The results showed that ATR-FTIR spectroscopy, combined with principal components analysis (PCA) and linear discriminant analysis (LDA) or artificial neural network (ANN), made it possible to efficiently identify specimens from recovered COVID-19 patients. We built classification models based on PCA associated with LDA and ANN. Our analysis led to 87% accuracy for PCA-LDA model and 91% accuracy for ANN, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective tool for detecting seroconversion against SARS-CoV-2. This approach could be used as an alternative to ELISA.
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Affiliation(s)
- Boris Y Karas
- Institute BioEngineering, ITMO University, St. Petersburg, Russia
| | - Vera E Sitnikova
- Institute BioEngineering, ITMO University, St. Petersburg, Russia
| | | | - Vladimir G Dedkov
- Saint-Petersburg Pasteur Institute, Federal Service on Consumers' Rights Protection and Human Well-Being Surveillance, St. Petersburg, Russia
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Natalia A Arsentieva
- Saint-Petersburg Pasteur Institute, Federal Service on Consumers' Rights Protection and Human Well-Being Surveillance, St. Petersburg, Russia
| | - Natalia V Gavrilenko
- Raisa Gorbacheva memorial Research Institute for Pediatric Oncology, Hematology and Transplantation, Pavlov First Saint Petersburg State Medical University, St. Petersburg, Russia
| | - Ivan S Moiseev
- Raisa Gorbacheva memorial Research Institute for Pediatric Oncology, Hematology and Transplantation, Pavlov First Saint Petersburg State Medical University, St. Petersburg, Russia
| | - Areg A Totolian
- Saint-Petersburg Pasteur Institute, Federal Service on Consumers' Rights Protection and Human Well-Being Surveillance, St. Petersburg, Russia
| | - Andrey V Kajava
- Centre de Recherche en Biologie cellulaire de Montpellier, Université Montpellier, Montpellier, France
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14
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Crocco MC, Moyano MFH, Annesi F, Bruno R, Pirritano D, Del Giudice F, Petrone A, Condino F, Guzzi R. ATR-FTIR spectroscopy of plasma supported by multivariate analysis discriminates multiple sclerosis disease. Sci Rep 2023; 13:2565. [PMID: 36782055 PMCID: PMC9924868 DOI: 10.1038/s41598-023-29617-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/07/2023] [Indexed: 02/15/2023] Open
Abstract
Multiple sclerosis (MS) is one of the most common neurodegenerative diseases showing various symptoms both of physical and cognitive type. In this work, we used attenuated total reflection Fourier transformed infrared (ATR-FTIR) spectroscopy to analyze plasma samples for discriminating MS patients from healthy control individuals, and identifying potential spectral biomarkers helping the diagnosis through a quick non-invasive blood test. The cohort of the study consists of 85 subjects, including 45 MS patients and 40 healthy controls. The differences in the spectral features both in the fingerprint region (1800-900 cm-1) and in the high region (3050-2800 cm-1) of the infrared spectra were highlighted also with the support of different chemometric methods, to capture the most significant wavenumbers for the differentiation. The results show an increase in the lipid/protein ratio in MS patients, indicating changes in the level (metabolism) of these molecular components in the plasma. Moreover, the multivariate tools provided a promising rate of success in the diagnosis, with 78% sensitivity and 83% specificity obtained through the random forest model in the fingerprint region. The MS diagnostic tools based on biomarkers identification on blood (and blood component, like plasma or serum) are very challenging and the specificity and sensitivity values obtained in this work are very encouraging. Overall, the results obtained suggest that ATR-FTIR spectroscopy on plasma samples, requiring minimal or no manipulation, coupled with statistical multivariate approaches, is a promising analytical tool to support MS diagnosis through the identification of spectral biomarkers.
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Affiliation(s)
- Maria Caterina Crocco
- Molecular Biophysics Laboratory, Department of Physics, University of Calabria, 87036, Rende, Italy
- STAR Research Infrastructure, University of Calabria, 87036, Rende, CS, Italy
| | | | | | - Rosalinda Bruno
- Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036, Rende, CS, Italy
| | - Domenico Pirritano
- Neurological and Stroke Unit, Multiple Sclerosis Clinic, Annunziata Hospital, 87100, Cosenza, Italy
- SOC Neurologia-Azienda Ospedaliera Pugliese-Ciaccio, 88100, Catanzaro, Italy
| | - Francesco Del Giudice
- Neurological and Stroke Unit, Multiple Sclerosis Clinic, Annunziata Hospital, 87100, Cosenza, Italy
- SOC Neurologia-Ospedale Jazzolino, Azienda Ospedaliera Provinciale, 89900, Vibo Valentia, Italy
| | - Alfredo Petrone
- Neurological and Stroke Unit, Multiple Sclerosis Clinic, Annunziata Hospital, 87100, Cosenza, Italy
| | - Francesca Condino
- Department of Economics, Statistics and Finance "Giovanni Anania", University of Calabria, Arcavacata di Rende, CS, Italy
| | - Rita Guzzi
- Molecular Biophysics Laboratory, Department of Physics, University of Calabria, 87036, Rende, Italy.
- CNR-Nanotec Rende, Via P. Bucci, 87036, Rende, Italy.
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15
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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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16
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Machine learning-assisted optical nano-sensor arrays in microorganism analysis. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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17
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Banerjee A, Halder A, Jadhav P, Sarkar A, Hole A, Shastri JS, Agrawal S, Chilakapati MK, Srivastava S. SARS-CoV-2 severity classification from plasma sample using confocal Raman spectroscopy. JOURNAL OF RAMAN SPECTROSCOPY : JRS 2023; 54:124-132. [PMID: 36713977 PMCID: PMC9874663 DOI: 10.1002/jrs.6461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/05/2022] [Accepted: 10/10/2022] [Indexed: 06/18/2023]
Abstract
The world is on the brink of facing coronavirus's (COVID-19) fourth wave as the mutant forms of viruses are escaping neutralizing antibodies in spite of being vaccinated. As we have already witnessed that it has encumbered our health system, with hospitals swamped with infected patients observed during the viral outbreak. Rapid triage of patients infected with SARS-CoV-2 is required during hospitalization to prioritize and provide the best point of care. Traditional diagnostics techniques such as RT-PCR and clinical parameters such as symptoms, comorbidities, sex and age are not enough to identify the severity of patients. Here, we investigated the potential of confocal Raman microspectroscopy as a powerful tool to generate an expeditious blood-based test for the classification of COVID-19 disease severity using 65 patients plasma samples from cohorts infected with SARS-CoV-2. We designed an easy manageable blood test where we used a small volume (8 μl) of inactivated whole plasma samples from infected patients without any extra solvent usage in plasma processing. Raman spectra of plasma samples were acquired and multivariate exploratory analysis PC-LDA (principal component based linear discriminant analysis) was used to build a model, which segregated the severe from the non-severe COVID-19 group with a sensitivity of 83.87%, specificity of 70.60% and classification efficiency of 76.92%. Among the bands expressed in both the cohorts, the study led to the identification of Raman fingerprint regions corresponding to lipids (1661, 1742), proteins amide I and amide III (1555, 1247), proteins (Phe) (1006, 1034), and nucleic acids (760) to be differentially expressed in severe COVID-19 patient's samples. In summary, the current study exhibits the potential of confocal Raman to generate simple, rapid, and less expensive blood tests to triage the severity of patients infected with SARS-CoV-2.
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Affiliation(s)
- Arghya Banerjee
- Department of Biosciences and BioengineeringIndian Institute of Technology BombayMumbaiIndia
| | - Ankit Halder
- Department of Biosciences and BioengineeringIndian Institute of Technology BombayMumbaiIndia
| | - Priyanka Jadhav
- Advanced Centre for Treatment Research and Education in Cancer (ACTREC)Tata Memorial Centre (TMC)Navi MumbaiIndia
- Homi Bhabha National InstituteTraining School Complex, Anushakti NagarMumbaiIndia
| | - Anushka Sarkar
- Department of Life SciencesPresidency University (Main Campus)KolkataIndia
| | - Arti Hole
- Advanced Centre for Treatment Research and Education in Cancer (ACTREC)Tata Memorial Centre (TMC)Navi MumbaiIndia
| | | | | | - Murali Krishna Chilakapati
- Advanced Centre for Treatment Research and Education in Cancer (ACTREC)Tata Memorial Centre (TMC)Navi MumbaiIndia
| | - Sanjeeva Srivastava
- Department of Biosciences and BioengineeringIndian Institute of Technology BombayMumbaiIndia
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18
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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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19
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Tessaro L, da Silva Mutz Y, Lelis CA, Andrade JCD, Aquino A, Panzenhagen P, Ochioni AC, Sousa Vieira IR, Conte-Junior CA. Combination of RT-LAMP and fluorescence spectroscopy using chemometric techniques for an ultra-sensitive and rapid alternative for the detection of SARS-CoV-2. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:4922-4930. [PMID: 36426753 DOI: 10.1039/d2ay01502a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The increased spread of COVID-19 caused by SARS-CoV-2 has made it necessary to develop more efficient, fast, accurate, specific, sensitive and easy-to-use detection platforms to overcome the disadvantages of gold standard methods (RT-qPCR). Here an approach was developed for the detection of the SARS-CoV-2 virus using the loop-mediated isothermal amplification (LAMP) technique for SARS-CoV-2 RNA target amplification in samples of nasopharyngeal swabs. The discrimination between positive and negative SARS-CoV-2 samples was achieved by using fluorescence spectra generated by the excitation of the LAMP's DNA intercalator dye at λ497 nm in a fluorescence spectrophotometer and chemometric tools. Exploratory analysis of the 83 sample spectra using principal component analysis (PCA) indicated a trend in differentiation between positive and negative samples resulting from the peak emission of the fluorescent dye. The classification was performed by partial least squares discriminant analysis (PLS-DA) achieving a sensitivity, a specificity and an accuracy of 100%, 95% and 89%, respectively for the discrimination between negative and positive samples from 1.58 to 0.25 ng L-1 after LAMP amplification. Therefore, this study indicates that the use of the LAMP technique in fluorescence spectroscopy may offer a fast (<1 hour), sensitive and low-cost method.
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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), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
| | - Carini Aparecida Lelis
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
| | - Pedro Panzenhagen
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
| | - Alan Clavelland Ochioni
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
| | - Italo Rennan Sousa Vieira
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
| | - Carlos Adam Conte-Junior
- Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), University City, Rio de Janeiro RJ, 21941-909, Brazil
- COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), University City, 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
- Department of Biochemistry, Institute of Chemistry, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, 21941-901, Brazil
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20
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Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers. Biomolecules 2022; 12:biom12121815. [PMID: 36551243 PMCID: PMC9775374 DOI: 10.3390/biom12121815] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 11/24/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022] Open
Abstract
Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.
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21
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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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22
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Comparison of the Immune Response in Vaccinated People Positive and Negative to SARS-CoV-2 Employing FTIR Spectroscopy. Cells 2022; 11:cells11233884. [PMID: 36497139 PMCID: PMC9740721 DOI: 10.3390/cells11233884] [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: 10/18/2022] [Revised: 11/21/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
Various immunopathological events characterize the systemic acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Moreover, it has been reported that coronavirus disease 2019 (COVID-19) vaccination and infection by SARS-CoV-2 induce humoral immunity mediated by B-cell-derived antibodies and cellular immunity mediated by T cells and memory B cells. Immunoglobulins, cytokines, and chemokines play an important role in shaping immunity in response to infection and vaccination. Furthermore, different vaccines have been developed to prevent COVID-19. Therefore, this research aimed to analyze and compare Fourier-transform infrared (FTIR) spectra of vaccinated people with a positive (V-COVID-19 group) or negative (V-Healthy group) real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) test, evaluating the immunoglobulin and cytokine content as an immunological response through FTIR spectroscopy. Most individuals that integrated the V-Healthy group (88.1%) were asymptomatic; on the contrary, only 28% of the V-COVID-19 group was asymptomatic. Likewise, 68% of the V-COVID-19 group had at least one coexisting illness. Regarding the immunological response analyzed through FTIR spectroscopy, the V-COVID-19 group showed a greater immunoglobulins G, A, and M (IgG, IgA, and IgM) content, as well as the analyzed cytokines interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-ɑ), and interleukins 1β, 6, and 10 (IL-1β, IL-6, and IL-10). Therefore, we can state that it was possible to detect biochemical changes through FTIR spectroscopy associated with COVID-19 immune response in vaccinated people.
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23
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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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24
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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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25
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Spectroscopic methods for COVID-19 detection and early diagnosis. Virol J 2022; 19:152. [PMID: 36138463 PMCID: PMC9502632 DOI: 10.1186/s12985-022-01867-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 08/16/2022] [Indexed: 11/10/2022] Open
Abstract
The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.
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26
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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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27
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A new strategy based on PCA for inter-batches quality consistency evaluation. J Pharm Biomed Anal 2022; 217:114838. [DOI: 10.1016/j.jpba.2022.114838] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 04/15/2022] [Accepted: 05/13/2022] [Indexed: 11/21/2022]
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28
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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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29
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Joshi N, Shukla S, Narayan RJ. Novel photonic methods for diagnosis of
SARS‐CoV
‐2 infection. TRANSLATIONAL BIOPHOTONICS 2022; 4:e202200001. [PMID: 35602265 PMCID: PMC9111306 DOI: 10.1002/tbio.202200001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/27/2022] [Accepted: 03/02/2022] [Indexed: 11/08/2022] Open
Affiliation(s)
- Naveen Joshi
- Department of Materials Science and Engineering North Carolina State University Raleigh NC USA
| | - Shubhangi Shukla
- Joint Department of Biomedical Engineering, North Carolina State University Raleigh NC USA
| | - Roger J. Narayan
- Joint Department of Biomedical Engineering, North Carolina State University Raleigh NC USA
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30
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Sur UK, Santra C. Spectroscopy: a versatile sensing tool for cost-effective and rapid detection of novel coronavirus (COVID-19). EMERGENT MATERIALS 2022; 5:249-260. [PMID: 35252760 PMCID: PMC8883019 DOI: 10.1007/s42247-022-00358-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
UNLABELLED The deadly novel coronavirus SARS-CoV-2 is responsible for COVID-19, which was first recognized in Wuhan, China, in December 2019. Rapid identification at primary stage of the novel coronavirus, SARS-CoV-2, is important to restrict it and prevent the pandemic. Real-time RT-PCR assays are the best diagnostic tests presently available for SARS-CoV-2 detection, which are highly sensitive, even though expensive equipment and trained technicians are necessary. Furthermore, the method has moderately long time bound. This deadly viral infection can also be detected by applying various spectroscopic techniques as spectroscopy can provide fast, precise identification and monitoring, leading to the overall understanding of its mutation rates, which will further facilitate antiviral drug development as well as vaccine development. It is an innovative and non-invasive technique for combating the spread of novel coronavirus. This review article demonstrates the application of various spectroscopic techniques to detect COVID-19 rapidly. Different spectroscopy-based detection protocols and additional development of new, novel sensors and biosensors along with diagnostic kits had been described here stressing the status of sensitive diagnostic systems to handle with the COVID-19 outbreak. GRAPHICAL ABSTRACT Spectroscopy: A versatile sensing tool for cost-effective and rapid detection of novel Coronavirus (COVID-19).
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Affiliation(s)
- Ujjal Kumar Sur
- Department of Chemistry, Behala College, University of Calcutta, Parnashree, Kolkata, 700060 West Bengal India
| | - Chittaranjan Santra
- Department of Chemistry (Ex), Netaji Nagar Day College, Kolkata, 700092 India
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31
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Kim G, Choi D, Chae SY, Bera R, Park S, Lee J, Min SH, Choi HK, Kim J, Huh J, Choi K, Lim M, Kim HI, Cho M, Jeong KS. Midwavelength Infrared Colloidal Nanowire Laser. J Phys Chem Lett 2022; 13:1431-1437. [PMID: 35119872 DOI: 10.1021/acs.jpclett.1c04154] [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: 06/14/2023]
Abstract
Realizing bright colloidal infrared emitters in the midwavelength infrared (or mid-IR), which can be used for low-power IR light-emitting diodes (LEDs), sensors, and deep-tissue imaging, has been a challenge for the last few decades. Here, we present colloidal tellurium nanowires with strong emission intensity at room temperature and even lasing at 3.6 μm (ω) under cryotemperature. Furthermore, the second-harmonic field at 1.8 μm (2ω) and the third-harmonic field at 1.2 μm (3ω) are successfully generated thanks to the intrinsic property of the tellurium nanowire. These unique optical features have never been reported for colloidal tellurium nanocrystals. With the colloidal midwavelength infrared (MWIR) Te nanowire laser, we demonstrate its potential in biomedical applications. MWIR lasing has been clearly observed from nanowires embedded in a human neuroblastoma cell, which could further realize deep-tissue imaging and thermotherapy in the near future.
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Affiliation(s)
| | | | | | - Rajesh Bera
- Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), Seoul 02841, Republic of Korea
| | - Seongchul Park
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Korea
| | | | | | - Han-Kyu Choi
- Department of Chemistry, Kunsan National University, Gunsan 54150, Republic of Korea
| | - Juyeong Kim
- Department of Chemistry and Research Institute of Natural Sciences, Gyeongsang National University, Jinju 52828, Republic of Korea
| | | | | | - Manho Lim
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Korea
| | | | - Minhaeng Cho
- Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), Seoul 02841, Republic of Korea
| | - Kwang Seob Jeong
- Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), Seoul 02841, Republic of Korea
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32
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Nascimento MC, Marcarini WD, Folli GS, da Silva Filho WG, Barbosa LL, Paulo EH, Vassallo PF, Mill JG, Barauna V, Martin FL, de Castro ER, Romão W, Filgueiras PR. Noninvasive Diagnostic for COVID-19 from Saliva Biofluid via FTIR Spectroscopy and Multivariate Analysis. Anal Chem 2022; 94:2425-2433. [PMID: 35076208 PMCID: PMC8805707 DOI: 10.1021/acs.analchem.1c04162] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/13/2022] [Indexed: 01/22/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the worst global health crisis in living memory. The reverse transcription polymerase chain reaction (RT-qPCR) is considered the gold standard diagnostic method, but it exhibits limitations in the face of enormous demands. We evaluated a mid-infrared (MIR) data set of 237 saliva samples obtained from symptomatic patients (138 COVID-19 infections diagnosed via RT-qPCR). MIR spectra were evaluated via unsupervised random forest (URF) and classification models. Linear discriminant analysis (LDA) was applied following the genetic algorithm (GA-LDA), successive projection algorithm (SPA-LDA), partial least squares (PLS-DA), and a combination of dimension reduction and variable selection methods by particle swarm optimization (PSO-PLS-DA). Additionally, a consensus class was used. URF models can identify structures even in highly complex data. Individual models performed well, but the consensus class improved the validation performance to 85% accuracy, 93% sensitivity, 83% specificity, and a Matthew's correlation coefficient value of 0.69, with information at different spectral regions. Therefore, through this unsupervised and supervised framework methodology, it is possible to better highlight the spectral regions associated with positive samples, including lipid (∼1700 cm-1), protein (∼1400 cm-1), and nucleic acid (∼1200-950 cm-1) regions. This methodology presents an important tool for a fast, noninvasive diagnostic technique, reducing costs and allowing for risk reduction strategies.
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Affiliation(s)
- Márcia
H. C. Nascimento
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Wena D. Marcarini
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Gabriely S. Folli
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Walter G. da Silva Filho
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Leonardo L. Barbosa
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Ellisson Henrique
de Paulo
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Paula F. Vassallo
- Clinical
Hospital, Universidade Federal de Minas
Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - José G. Mill
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | - Valério
G. Barauna
- Department
of Physiological Sciences, Universidade
Federal do Espírito Santo (UFES), Vitória, Espírito Santo 29040-090, Brazil
| | | | - Eustáquio
V. R. de Castro
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
| | - Wanderson Romão
- Instituto
Federal de Educação, Ciência
e Tecnologia do Espírito Santo, Vila Velha 29106-010, Brazil
| | - Paulo R. Filgueiras
- Chemometrics
Laboratory of the Center of Competence in Petroleum Chemistry −
NCQP, Universidade Federal do Espírito
Santo (UFES), Vitória, Espírito Santo 29075-910, Brazil
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33
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Wang M, Lin Y, Lu J, Sun Z, Deng Y, Wang L, Yi Y, Li J, Yang J, Li G. Visual naked-eye detection of SARS-CoV-2 RNA based on covalent organic framework capsules. CHEMICAL ENGINEERING JOURNAL (LAUSANNE, SWITZERLAND : 1996) 2022; 429:132332. [PMID: 34539223 PMCID: PMC8433056 DOI: 10.1016/j.cej.2021.132332] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/16/2021] [Accepted: 09/05/2021] [Indexed: 05/17/2023]
Abstract
The ongoing outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted that new diagnosis technologies are crucial for controlling the spread of the disease. Especially in the resources-limit region, conveniently operated detection methods such as "naked-eye" detection are urgently required that no instrument is needed. Herein, we have designed a novel and facile strategy to fabricate covalent organic framework (COF) capsules, which can be utilized to establish a new colorimetric assay for naked-eye detection of SARS-CoV-2 RNA. Specifically, we employ the digestible ZIF-90 as the sacrificial template to prepare the hollow COF capsules for horseradish peroxidase (HRP) encapsulation. The fabricated COF capsules can provide an appropriate microenvironment for the enzyme molecules, which may improve the conformational freedom of enzymes, enhance the mass transfer, and endow the enzyme with high environmental resistance. With such design, the proposed assay exhibits outstanding analytical performance for the detection of SARS-CoV-2 RNA in the linear range from 5 pM to 50 nM with a detection limit of 0.28 pM which can go parallel to qTR-PCR analysis. Our method also possesses excellent selectivity and reproducibility. Moreover, this method can also be served to analyze the clinical samples, and can successfully differentiate COVID-19 patients from healthy people, suggesting the promising potential in clinical diagnosis.
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Affiliation(s)
- Minghui Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Yuxin Lin
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Jianyang Lu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Zhaowei Sun
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Ying Deng
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Lei Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Yongxiang Yi
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing 210003, PR China
| | - Jinlong Li
- The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing 210003, PR China
| | - Jie Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
| | - Genxi Li
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, PR China
- Center for Molecular Recognition and Biosensing, School of Life Sciences, Shanghai University, Shanghai 200444, PR China
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34
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Praja RK, Wongwattanakul M, Tippayawat P, Phoksawat W, Jumnainsong A, Sornkayasit K, Leelayuwat C. Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Discriminates the Elderly with a Low and High Percentage of Pathogenic CD4+ T Cells. Cells 2022; 11:cells11030458. [PMID: 35159268 PMCID: PMC8834052 DOI: 10.3390/cells11030458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/21/2022] [Accepted: 01/27/2022] [Indexed: 02/07/2023] Open
Abstract
In the aging process, the presence of interleukin (IL)-17-producing CD4+CD28-NKG2D+T cells (called pathogenic CD4+ T cells) is strongly associated with inflammation and the development of various diseases. Thus, their presence needs to be monitored. The emergence of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy empowered with machine learning is a breakthrough in the field of medical diagnostics. This study aimed to discriminate between the elderly with a low percentage (LP; ≤3%) and a high percentage (HP; ≥6%) of pathogenic CD4+CD28-NKG2D+IL17+ T cells by utilizing ATR-FTIR coupled with machine learning algorithms. ATR spectra of serum, exosome, and HDL from both groups were explored in this study. Only exosome spectra in the 1700–1500 cm−1 region exhibited possible discrimination for the LP and HP groups based on principal component analysis (PCA). Furthermore, partial least square-discriminant analysis (PLS-DA) could differentiate both groups using the 1700–1500 cm−1 region of exosome ATR spectra with 64% accuracy, 69% sensitivity, and 61% specificity. To obtain better classification performance, several spectral models were then established using advanced machine learning algorithms, including J48 decision tree, support vector machine (SVM), random forest (RF), and neural network (NN). Herein, NN was considered to be the best model with an accuracy of 100%, sensitivity of 100%, and specificity of 100% using serum spectra in the region of 1800–900 cm−1. Exosome spectra in the 1700–1500 and combined 3000–2800 and 1800–900 cm−1 regions using the NN algorithm gave the same accuracy performance of 95% with a variation in sensitivity and specificity. HDL spectra with the NN algorithm also showed excellent test performance in the 1800–900 cm−1 region with 97% accuracy, 100% sensitivity, and 95% specificity. This study demonstrates that ATR-FTIR coupled with machine learning algorithms can be used to study immunosenescence. Furthermore, this approach can possibly be applied to monitor the presence of pathogenic CD4+ T cells in the elderly. Due to the limited number of samples used in this study, it is necessary to conduct a large-scale study to obtain more robust classification models and to assess the true clinical diagnostic performance.
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Affiliation(s)
- Rian Ka Praja
- Biomedical Sciences Program, Graduate School, Khon Kaen University, Khon Kaen 40002, Thailand;
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
| | - Molin Wongwattanakul
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
| | - Patcharaporn Tippayawat
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
- Department of Clinical Microbiology, Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Wisitsak Phoksawat
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand;
- Research and Diagnostic Center for Emerging Infectious Diseases, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Amonrat Jumnainsong
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
- Department of Clinical Immunology and Transfusion Sciences, Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Kanda Sornkayasit
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
| | - Chanvit Leelayuwat
- The Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand; (M.W.); (P.T.); (A.J.); (K.S.)
- Department of Clinical Immunology and Transfusion Sciences, Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand
- Correspondence:
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35
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Guleken Z, Jakubczyk P, Wiesław P, Krzysztof P, Bulut H, Öten E, Depciuch J, Tarhan N. Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications. Talanta 2022; 237:122916. [PMID: 34736654 PMCID: PMC8491955 DOI: 10.1016/j.talanta.2021.122916] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/19/2021] [Accepted: 09/29/2021] [Indexed: 01/08/2023]
Abstract
Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH2 scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.
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Affiliation(s)
- Zozan Guleken
- Department of Physiology, Uskudar University Faculty of Medicine, Istanbul, Turkey.
| | | | - Paja Wiesław
- College of Natural Sciences, University of Rzeszów, Poland
| | | | - Huri Bulut
- Department of Medical Biochemistry, Faculty of Medicine Istinye University, Istanbul, Turkey
| | - Esra Öten
- Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital, Department of Obstetrics and Gynecology, Turkey
| | - Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Science, 31-342, Krakow, Poland.
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36
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Ramoji A, Pahlow S, Pistiki A, Rueger J, Shaik TA, Shen H, Wichmann C, Krafft C, Popp J. Understanding Viruses and Viral Infections by Biophotonic Methods. TRANSLATIONAL BIOPHOTONICS 2022. [DOI: 10.1002/tbio.202100008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Anuradha Ramoji
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
- Center for Sepsis Control and Care Jena University Hospital, Am Klinikum 1, 07747 Jena Germany
| | - Susanne Pahlow
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
- InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena Germany
| | - Aikaterini Pistiki
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
| | - Jan Rueger
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
| | - Tanveer Ahmed Shaik
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
| | - Haodong Shen
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
- InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena Germany
| | - Christina Wichmann
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
- InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena Germany
| | - Christoph Krafft
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
| | - Juergen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4 Jena Germany
- Leibniz Institute of Photonic Technology Jena (a member of Leibniz Health Technologies) , Albert‐Einstein Str. 9 Jena Germany
- Center for Sepsis Control and Care Jena University Hospital, Am Klinikum 1, 07747 Jena Germany
- InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena Germany
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37
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Ami D, Duse A, Mereghetti P, Cozza F, Ambrosio F, Ponzini E, Grandori R, Lunetta C, Tavazzi S, Pezzoli F, Natalello A. Tear-Based Vibrational Spectroscopy Applied to Amyotrophic Lateral Sclerosis. Anal Chem 2021; 93:16995-17002. [PMID: 34905686 PMCID: PMC8717331 DOI: 10.1021/acs.analchem.1c02546] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
![]()
Biofluid analysis
by optical spectroscopy techniques is attracting
considerable interest due to its potential to revolutionize diagnostics
and precision medicine, particularly for neurodegenerative diseases.
However, the lack of effective biomarkers combined with the unaccomplished
identification of convenient biofluids has drastically hampered optical
advancements in clinical diagnosis and monitoring of neurodegenerative
disorders. Here, we show that vibrational spectroscopy applied to
human tears opens a new route, offering a non-invasive, label-free
identification of a devastating disease such as amyotrophic lateral
sclerosis (ALS). Our proposed approach has been validated using two
widespread techniques, namely, Fourier transform infrared (FTIR) and
Raman microspectroscopies. In conjunction with multivariate analysis,
this vibrational approach made it possible to discriminate between
tears from ALS patients and healthy controls (HCs) with high specificity
(∼97% and ∼100% for FTIR and Raman spectroscopy, respectively)
and sensitivity (∼88% and ∼100% for FTIR and Raman spectroscopy,
respectively). Additionally, the investigation of tears allowed us
to disclose ALS spectroscopic markers related to protein and lipid
alterations, as well as to a reduction of the phenylalanine level,
in comparison with HCs. Our findings show that vibrational spectroscopy
is a new potential ALS diagnostic approach and indicate that tears
are a reliable and non-invasive source of ALS biomarkers.
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Affiliation(s)
- Diletta Ami
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
| | - Alessandro Duse
- Department of Materials Science, University of Milano-Bicocca, Via R. Cozzi 55, 20125 Milano, Italy.,COMiB Research Centre in Optics and Optometry, Via R. Cozzi 55, 20125 Milano, Italy
| | | | - Federica Cozza
- COMiB Research Centre in Optics and Optometry, Via R. Cozzi 55, 20125 Milano, Italy.,NEuroMuscular Omnicentre (NEMO), Serena Onlus Foundation, Piazza Ospedale Maggiore 3, 20162 Milano, Italy
| | - Francesca Ambrosio
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
| | - Erika Ponzini
- Department of Materials Science, University of Milano-Bicocca, Via R. Cozzi 55, 20125 Milano, Italy.,COMiB Research Centre in Optics and Optometry, Via R. Cozzi 55, 20125 Milano, Italy
| | - Rita Grandori
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
| | - Christian Lunetta
- NEuroMuscular Omnicentre (NEMO), Serena Onlus Foundation, Piazza Ospedale Maggiore 3, 20162 Milano, Italy.,NEMO Lab, Piazza Ospedale Maggiore 3, 20162 Milano, Italy
| | - Silvia Tavazzi
- Department of Materials Science, University of Milano-Bicocca, Via R. Cozzi 55, 20125 Milano, Italy.,COMiB Research Centre in Optics and Optometry, Via R. Cozzi 55, 20125 Milano, Italy
| | - Fabio Pezzoli
- Department of Materials Science, University of Milano-Bicocca, Via R. Cozzi 55, 20125 Milano, Italy
| | - Antonino Natalello
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
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38
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Goulart ACC, Zângaro RA, Carvalho HC, Silveira L. Diagnosing COVID-19 in human sera with detected immunoglobulins IgM and IgG by means of Raman spectroscopy. JOURNAL OF RAMAN SPECTROSCOPY : JRS 2021; 52:2671-2682. [PMID: 34518728 PMCID: PMC8427108 DOI: 10.1002/jrs.6235] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/30/2021] [Accepted: 07/31/2021] [Indexed: 05/05/2023]
Abstract
The severe COVID-19 pandemic requires the development of novel, rapid, accurate, and label-free techniques that facilitate the detection and discrimination of SARS-CoV-2 infected subjects. Raman spectroscopy has been used to diagnose COVID-19 in serum samples of suspected patients without clinical symptoms of COVID-19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID-19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID-19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID-19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID-19). A discriminant model based on partial least squares regression (PLS-DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID-19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID-19 infection.
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Affiliation(s)
| | - Renato Amaro Zângaro
- Biomedical Engineering ProgramUniversidade Anhembi Morumbi – UAMSão PauloState of São PauloBrazil
- Laboratory of Vibrational SpectroscopyCenter for Innovation, Technology and Education – CITÉSão José dos CamposState of São PauloBrazil
| | - Henrique Cunha Carvalho
- Laboratory of Vibrational SpectroscopyCenter for Innovation, Technology and Education – CITÉSão José dos CamposState of São PauloBrazil
| | - Landulfo Silveira
- Biomedical Engineering ProgramUniversidade Anhembi Morumbi – UAMSão PauloState of São PauloBrazil
- Laboratory of Vibrational SpectroscopyCenter for Innovation, Technology and Education – CITÉSão José dos CamposState of São PauloBrazil
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39
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Dogan A, Gurbanov R, Severcan M, Severcan F. CoronaVac (Sinovac) COVID-19 vaccine-induced molecular changes in healthy human serum by infrared spectroscopy coupled with chemometrics. Turk J Biol 2021; 45:549-558. [PMID: 34803453 PMCID: PMC8573849 DOI: 10.3906/biy-2105-65] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 07/30/2021] [Indexed: 12/25/2022] Open
Abstract
From the beginning of the COVID-19 coronavirus pandemic in December of 2019, the disease has infected millions of people worldwide and caused hundreds of thousands of deaths. Since then, several vaccines have been developed. One of those vaccines is inactivated CoronaVac-Sinovac COVID-19 vaccine. In this proof of concept study, we first aimed to determine CoronaVac-induced biomolecular changes in healthy human serum using infrared spectroscopy. Our second aim was to see whether the vaccinated group can be separated or not from the non-vaccinated group by applying chemometric techniques to spectral data. The results revealed that the vaccine administration induced significant changes in some functional groups belonging to lipids, proteins and nucleic acids. In addition, the non-vaccinated and vaccinated groups were successfully separated from each other by principal component analysis (PCA) and linear discriminant analysis (LDA). This proof-of-concept study will encourage future studies on CoronaVac as well as other vaccines and will lead to make a comparison between different vaccines to establish a better understanding of the vaccination outcomes on serum biomolecules.
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Affiliation(s)
- Ayca Dogan
- Department of Physiology, Faculty of Medicine, Altinbaş University, İstanbul Turkey
| | - Rafig Gurbanov
- Biotechnology Application and Research Center, Bilecik Şeyh Edebali University, Bilecik Turkey
| | - Mete Severcan
- Department of Electrical and Electronics Engineering, Faculty of Engineering and Natural Sciences, Altınbaş University, İstanbul Turkey
| | - Feride Severcan
- Department of Biophysics, Faculty of Medicine, Altınbaş University, İstanbul Turkey
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40
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Soares JC, Soares AC, Angelim MKSC, Proença-Modena JL, Moraes-Vieira PM, Mattoso LHC, Oliveira ON. Diagnostics of SARS-CoV-2 infection using electrical impedance spectroscopy with an immunosensor to detect the spike protein. Talanta 2021; 239:123076. [PMID: 34876273 PMCID: PMC8607795 DOI: 10.1016/j.talanta.2021.123076] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 11/09/2021] [Accepted: 11/16/2021] [Indexed: 11/04/2022]
Abstract
Mass testing for the diagnostics of COVID-19 has been hampered in many countries owing to the high cost of the methodologies to detect genetic material of SARS-CoV-2. In this paper, we report on a low-cost immunosensor capable of detecting the spike protein of SARS-CoV-2, including in samples of inactivated virus. Detection is performed with electrical impedance spectroscopy using an immunosensor that contains a monolayer film of carboxymethyl chitosan as matrix, coated with an active layer of antibodies specific to the spike protein. In addition to a low limit of detection of 0.179 fg/mL within an almost linear behavior from 10−20 g/mL to 10−14 g/mL, the immunosensor was highly selective. For the samples with the spike protein could be distinguished in multidimensional projection plots from samples with other biomarkers and analytes that could be interfering species for healthy and infected patients. The excellent analytical performance of the immunosensors was validated with the distinction between control samples and those containing inactivated SARS-CoV-2 at different concentrations. The mechanism behind the immunosensor performance is the specific antibody-protein interaction, as confirmed with the changes induced in C–H stretching and protein bands in polarization-modulated infrared reflection absorption spectra (PM-IRRAS). Because impedance spectroscopy measurements can be made with low-cost portable instruments, the immunosensor proposed here can be applied in point-of-care diagnostics for mass testing even in places with limited resources.
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Affiliation(s)
- Juliana C Soares
- São Carlos Institute of Physics (IFSC), University of São Paulo (USP), 13566-590, São Carlos, Brazil
| | - Andrey C Soares
- Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970, São Carlos, SP, Brazil
| | - Monara Kaelle S C Angelim
- Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas, 13083-862, Campinas, SP, Brazil
| | - Jose Luiz Proença-Modena
- Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas, 13083-862, Campinas, SP, Brazil; Experimental Medicine Research Cluster (EMRC), University of Campinas, 13083-862, Campinas, SP, Brazil
| | - Pedro M Moraes-Vieira
- Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas, 13083-862, Campinas, SP, Brazil; Experimental Medicine Research Cluster (EMRC), University of Campinas, 13083-862, Campinas, SP, Brazil; Obesity and Comorbilities Research Center (OCRC), University of Campinas, 13083-862, Campinas, SP, Brazil
| | - Luiz H C Mattoso
- Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970, São Carlos, SP, Brazil
| | - Osvaldo N Oliveira
- São Carlos Institute of Physics (IFSC), University of São Paulo (USP), 13566-590, São Carlos, Brazil.
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41
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Forsberg P, Hollman P, Karlsson M. High sensitivity infrared spectroscopy with a diamond waveguide on aluminium nitride. Analyst 2021; 146:6981-6989. [PMID: 34661204 DOI: 10.1039/d1an01009c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Mid-infrared waveguide spectroscopy promises highly sensitive detection and characterization of organic molecules. Different material combinations for waveguides and cladding have been demonstrated with promising results, each with its own strengths and weaknesses in terms of sensitivity, transmission window and robustness. In this article we present a 5 μm thick diamond planar waveguide on aluminium nitride cladding, using a new fabrication and polishing method. Diamond has a very wide transmission window in the infrared, and its hardness and high chemical stability allows for chemistries and cleaning protocols that may damage other materials. With an aluminium nitride cladding the waveguide has a useable range between 1000 and 1900 cm-1, which we demonstrate using a tunable quantum cascade laser (QCL). This is a large improvement over silicon dioxide cladding. Compared to previously demonstrated free-standing diamond waveguides, the robustness of the sensor is greatly improved, which allows for a thinner diamond layer and increased sensitivity. The new waveguide was used in a QCL-based optical setup to detect acetone in deuterium oxide and isopropyl alcohol in water. The measurements showed higher sensitivity and lower noise level than previous demonstrations of mid-infrared diamond waveguides, resulting in a two orders of magnitude lower detectable concentration.
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Affiliation(s)
- Pontus Forsberg
- Department of Materials Science and Engineering, Uppsala University, Box 35, 751 03 Uppsala, Sweden.
| | - Patrik Hollman
- Nova Diamant AB, Tryffelvägen 17, 756 46 Uppsala, Sweden
| | - Mikael Karlsson
- Department of Materials Science and Engineering, Uppsala University, Box 35, 751 03 Uppsala, Sweden.
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42
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The Application of NIRS to Determine Animal Physiological Traits for Wildlife Management and Conservation. REMOTE SENSING 2021. [DOI: 10.3390/rs13183699] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The ability to measure and monitor wildlife populations is important for species management and conservation. The use of near-infrared spectroscopy (NIRS) to rapidly detect physiological traits from wildlife scat and other body materials could play an important role in the conservation of species. Previous research has demonstrated the potential for NIRS to detect diseases such as the novel COVID-19 from saliva, parasites from feces, and numerous other traits from animal skin, hair, and scat, such as cortisol metabolites, diet quality, sex, and reproductive status, that may be useful for population monitoring. Models developed from NIRS data use light reflected from a sample to relate the variation in the sample’s spectra to variation in a trait, which can then be used to predict that trait in unknown samples based on their spectra. The modelling process involves calibration, validation, and evaluation. Data sampling, pre-treatments, and the selection of training and testing datasets can impact model performance. We review the use of NIRS for measuring physiological traits in animals that may be useful for wildlife management and conservation and suggest future research to advance the application of NIRS for this purpose.
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GARİP USTAOĞLU Ş, KAYGUSUZ H, BİLGİN MD, SEVERCAN F. Novel approaches for COVID-19 diagnosis and treatment: a nonsystematic review. Turk J Biol 2021; 45:358-371. [PMID: 34803440 PMCID: PMC8573842 DOI: 10.3906/biy-2105-45] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/19/2021] [Indexed: 12/13/2022] Open
Abstract
Since COVID-19 pandemic has been continuously rising and spreading, several original contributions and review articles on COVID-19 started to appear in the literature. The review articles are mainly focus on the current status of the pandemic along with current status of the corona diagnosis and treatment process. Due to some disadvantages of the currently used methods, the improvement on the novel promising diagnosis and treatment methods of corona virus is very important issue. In this review, after briefly discussing the status of current diagnosis and treatment methods, we present to the scientific community, novel promising methods in the diagnosis and treatment of COVID-19. As with other novel approaches, first, the diagnosis potential of mass spectroscopy and optical spectroscopic methods such as UV/visible, infrared, and Raman spectroscopy coupled with chemometrics will be discussed for the corona virus infected samples based on the relevant literature. In vibrational spectroscopy studies, due to complexity of the data, multivariate analysis methods are also applied to data. The application of multivariate analysis tools that can be used to extract useful information from the data for diagnostic and characterisation purposes is also included in this review. The reviewed methods include hierarchical cluster analysis, principal component analysis, linear and quadratic discriminant analysis, support vector machine algorithm, and one form of neural networks namely deep learning method. Second, novel treatment methods such as photodynamic therapy and the use of nanoparticles in the in-corona virus therapy will be discussed. Finally, the advantages of novel promising diagnosis and treatment methods in COVID-19, over standard methods will be discussed. One of the main aims of this paper is to encourage the scientific community to explore the potential of this novel tools for their use in corona virus characterization, diagnosis, and treatment.
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Affiliation(s)
- Şebnem GARİP USTAOĞLU
- Department of Medical Biochemistry, Faculty of Medicine, Altınbaş University, İstanbulTurkey
| | - Hakan KAYGUSUZ
- Department of Basic Sciences, Faculty of Engineering and Natural Sciences, Altınbaş University, İstanbulTurkey
- Sabanci University SUNUM Nanotechnology Research Center, İstanbulTurkey
| | - Mehmet Dinçer BİLGİN
- Department of Biophysics, Faculty of Medicine, Aydın Adnan Menderes University, AydınTurkey
| | - Feride SEVERCAN
- Department of Biophysics, Faculty of Medicine, Altınbaş University, İstanbulTurkey
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44
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Banerjee A, Gokhale A, Bankar R, Palanivel V, Salkar A, Robinson H, Shastri JS, Agrawal S, Hartel G, Hill MM, Srivastava S. Rapid Classification of COVID-19 Severity by ATR-FTIR Spectroscopy of Plasma Samples. Anal Chem 2021; 93:10391-10396. [PMID: 34279898 PMCID: PMC8315140 DOI: 10.1021/acs.analchem.1c00596] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/29/2021] [Indexed: 12/24/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic continues to ravage the world, with many hospitals overwhelmed by the large number of patients presenting during major outbreaks. A rapid triage for COVID-19 patient requiring hospitalization and intensive care is urgently needed. Age and comorbidities have been associated with a higher risk of severe COVID-19 but are not sufficient to triage patients. Here, we investigated the potential of attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy as a rapid blood test for classification of COVID-19 disease severity using a cohort of 160 COVID-19 patients. A simple plasma processing and ATR-FTIR data acquisition procedure was established using 75% ethanol for viral inactivation. Next, partial least-squares-discriminant analysis (PLS-DA) models were developed and tested using data from 130 and 30 patients, respectively. Addition of the ATR-FTIR spectra to the clinical parameters (age, sex, diabetes mellitus, and hypertension) increased the area under the ROC curve (C-statistics) for both the training and test data sets, from 69.3% (95% CI 59.8-78.9%) to 85.7% (78.6-92.8%) and 77.8% (61.3-94.4%) to 85.1% (71.3-98.8%), respectively. The independent test set achieved 69.2% specificity (42.4-87.3%) and 94.1% sensitivity (73.0-99.0%). Diabetes mellitus was the strongest predictor in the model, followed by FTIR regions 1020-1090 and 1588-1592 cm-1. In summary, this study demonstrates the potential of ATR-FTIR spectroscopy as a rapid, low-cost COVID-19 severity triage tool to facilitate COVID-19 patient management during an outbreak.
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Affiliation(s)
- Arghya Banerjee
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
| | - Abhiram Gokhale
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
| | - Renuka Bankar
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
| | - Viswanthram Palanivel
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
| | - Akanksha Salkar
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
| | - Harley Robinson
- QIMR
Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia
| | - Jayanthi S. Shastri
- Kasturba
Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra 400034, India
| | - Sachee Agrawal
- Kasturba
Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra 400034, India
| | - Gunter Hartel
- QIMR
Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia
| | - Michelle M. Hill
- QIMR
Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia
| | - Sanjeeva Srivastava
- Department
of Biosciences and Bioengineering, Indian
Institute of Technology Bombay, Powai, Mumbai 400 076, India
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45
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Lovergne L, Ghosh D, Schuck R, Polyzos AA, Chen AD, Martin MC, Barnard ES, Brown JB, McMurray CT. An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms. Sci Rep 2021; 11:15598. [PMID: 34341363 PMCID: PMC8329289 DOI: 10.1038/s41598-021-93686-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/24/2021] [Indexed: 12/29/2022] Open
Abstract
Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.
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Affiliation(s)
- Lila Lovergne
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dhruba Ghosh
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
| | - Renaud Schuck
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Aris A Polyzos
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Andrew D Chen
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
| | - Michael C Martin
- Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Edward S Barnard
- Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - James B Brown
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Cynthia T McMurray
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
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