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Eissa T, Leonardo C, Kepesidis KV, Fleischmann F, Linkohr B, Meyer D, Zoka V, Huber M, Voronina L, Richter L, Peters A, Žigman M. Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening. Cell Rep Med 2024; 5:101625. [PMID: 38944038 DOI: 10.1016/j.xcrm.2024.101625] [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: 10/11/2023] [Revised: 04/19/2024] [Accepted: 06/07/2024] [Indexed: 07/01/2024]
Abstract
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions, a large-scale analysis of a naturally heterogeneous potential patient population has not been attempted. Using a population-based cohort, here we analyze 5,184 blood plasma samples from 3,169 individuals using Fourier transform infrared (FTIR) spectroscopy. Applying a multi-task classification to distinguish between dyslipidemia, hypertension, prediabetes, type 2 diabetes, and healthy states, we find that the approach can accurately single out healthy individuals and characterize chronic multimorbid states. We further identify the capacity to forecast the development of metabolic syndrome years in advance of onset. Dataset-independent testing confirms the robustness of infrared signatures against variations in sample handling, storage time, and measurement regimes. This study provides the framework that establishes infrared molecular fingerprinting as an efficient modality for populational health diagnostics.
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Affiliation(s)
- Tarek Eissa
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; School of Computation, Information and Technology, Technical University of Munich (TUM), Garching, Germany.
| | - Cristina Leonardo
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
| | - Kosmas V Kepesidis
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Frank Fleischmann
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Daniel Meyer
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Viola Zoka
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Marinus Huber
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Liudmila Voronina
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
| | - Lothar Richter
- School of Computation, Information and Technology, Technical University of Munich (TUM), Garching, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany; School of Public Health, Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer, Ludwig Maximilian University of Munich (LMU), Munich, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich, Munich, Germany
| | - Mihaela Žigman
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany.
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Kaur M, Singh S, Kaur A. Structural changes in amide I and amide II regions of PCOS women analyzed by ATR-FTIR spectroscopy. Heliyon 2024; 10:e33494. [PMID: 39040335 PMCID: PMC11261041 DOI: 10.1016/j.heliyon.2024.e33494] [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: 02/16/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/24/2024] Open
Abstract
The etiology of PCOS is complex and frequently mis or undiagnosed, which may enhance morbidity and reduce the quality of life. Attenuated total reflection- Fourier transform infrared (ATR-FTIR) spectroscopy examines the structural fingerprints of the biochemical compounds and can provide distinct FTIR spectra of the PCOS cases and controls. The present study recruited 61 PCOS cases and 38 control women. The student's t-test was used to compare BMI, WHR, and lipid profile. The FTIR spectral region was compared among both groups using the Mann-Whitney U test and multivariate analysis involved principal component analysis (PCA) and hierarchical cluster analysis (HCA). FTIR spectra of different phenotypes of PCOS were also analyzed using multivariate analysis. In univariate analysis, PCOS women had significantly higher WHR (p = 0.007), BMI (p = 0.04), triglycerides (p = 0.04), and VLDL (p = 0.02) than the controls. The spectral regions of amide I (1700-1600 cm-1) and amide II (1580-1480 cm-1), were significantly greater in the PCOS group than in the controls (p < 0.01 and p < 0.001, respectively). The PCA and HCA revealed a distinct molecular fingerprint for phenotype A (PCOM + OA + HA) and phenotype B (HA + OA). Our study postulated that the spectral regions of amide I and amide II can distinguish between PCOS cases and control women and it may be used for the diagnosis of cases.
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Affiliation(s)
- Mandeep Kaur
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, 143005, India
| | - Sukhjashanpreet Singh
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, 143005, India
| | - Anupam Kaur
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, 143005, India
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Ranasinghe JC, Wang Z, Huang S. Unveiling brain disorders using liquid biopsy and Raman spectroscopy. NANOSCALE 2024; 16:11879-11913. [PMID: 38845582 DOI: 10.1039/d4nr01413h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.
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Affiliation(s)
- Jeewan C Ranasinghe
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Ziyang Wang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Shengxi Huang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
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Seredin P, Litvinova T, Ippolitov Y, Goloshchapov D, Peshkov Y, Kashkarov V, Ippolitov I, Chae B. A Study of the Association between Primary Oral Pathologies (Dental Caries and Periodontal Diseases) Using Synchrotron Molecular FTIR Spectroscopy in View of the Patient's Personalized Clinical Picture (Demographics and Anamnesis). Int J Mol Sci 2024; 25:6395. [PMID: 38928102 PMCID: PMC11204202 DOI: 10.3390/ijms25126395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/15/2024] [Accepted: 06/06/2024] [Indexed: 06/28/2024] Open
Abstract
In this exploratory study, we searched for associations between the two most common diseases of the oral cavity-dental caries and periodontal diseases-taking into account additional factors, such as personalized clinical pictures (the individual risk factors of the patient), based on the method of a multivariate data analysis of the molecular changes in the composition of human gingival crevicular fluid (GCF). For this purpose, a set of synchrotron Fourier-transform infrared spectroscopy (FTIR) spectra of gingival crevicular fluid samples from patients with different demographics, levels of dental caries development and periodontal diseases, and the presence/absence of concomitant chronic diseases were obtained and analyzed. Using a set of techniques (v-, F-, Chi-square tests; a principal component analysis (PCA); and the hierarchical clustering of principal components (HCPCs)) implemented in the R package FactoMineR allowed us to assess the relationship between the principal components (PCs) and characteristics of the respondents. By identifying the features (vibrational modes in the FTIR spectra) that contribute most to the differentiation of the spectral dataset, and by taking into account the interrelationships between the patients' characteristics, we were able to match specific biological markers (specific molecular groups) to the two factors of interest-two types of oral pathologies. The results obtained show that the observed changes in the quantitative and qualitative composition of the modes in the infrared (IR) spectra of the GCF samples from patients with different dental caries developments and periodontal diseases present confirm the difficulty of identifying patient-specific spectral information. At the same time, different periodontal pathologies are more closely associated with other characteristics of the patients than the level of their caries development. The multivariate analysis performed on the spectral dataset indicates the need to take into account not only the co-occurrence of oral diseases, but also some other factors. The lack of this consideration (typical in lots of studies in this area) may lead to misinterpretations and consequently to a loss of data when searching for biological markers of certain oral diseases.
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Affiliation(s)
- Pavel Seredin
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
| | - Tatiana Litvinova
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
- Psycholinguistic Textual Modelling Lab, Voronezh State Pedagogical University, 394043 Voronezh, Russia
| | - Yuri Ippolitov
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
- Department of Pediatric Dentistry with Orthodontia, Voronezh State Medical University, 394006 Voronezh, Russia
| | - Dmitry Goloshchapov
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
| | - Yaroslav Peshkov
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
| | - Vladimir Kashkarov
- Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia; (T.L.)
| | - Ivan Ippolitov
- Department of Pediatric Dentistry with Orthodontia, Voronezh State Medical University, 394006 Voronezh, Russia
| | - Boknam Chae
- Pohang Accelerator Laboratory, Beamline Research Division, Pohang 37673, Republic of Korea
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Juchem CF, Corbellini VA, Horst A, Heidrich D. Infrared spectroscopy combined with chemometrics in transflectance mode: An alternative approach in the photodiagnosis of COVID-19 using saliva. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 312:124066. [PMID: 38428213 DOI: 10.1016/j.saa.2024.124066] [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: 07/28/2023] [Revised: 02/14/2024] [Accepted: 02/19/2024] [Indexed: 03/03/2024]
Abstract
The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has required the search for sensitive, rapid, specific, and lower-cost diagnostic methods to meet the high demand. The gold standard method of laboratory diagnosis is real-time reverse transcription polymerase chain reaction (RT-PCR). However, this method is costly and results can take time. In the literature, several studies have already described the potential of Fourier transform infrared spectroscopy (FTIR) as a tool in the biomedical field, including the diagnosis of viral infections, while being fast and inexpensive. In view of this, the objective of this study was to develop an FTIR model for the diagnosis of COVID-19. For this analysis, all private clients who had performed a face-to-face collection at the Univates Clinical Analysis Laboratory (LAC Univates) within a period of six months were invited to participate. Data from clients who agreed to participate in the study were collected, as well as nasopharyngeal secretions and a saliva sample. For the development of models, the RT-PCR result of nasopharyngeal secretions was used as a reference method. Absorptions with high discrimination (p < 0.001) between GI (28 patients, RT-PCR test positive to SARS-CoV-2 virus) and GII (173 patients who did not have the virus detected in the test) were most relevant at 3512 cm-1, 3385 cm-1 and 1321 cm-1 after 2nd derivative data transformation. To carry out the diagnostic modeling, chemometrics via FTIR and Discriminant Analysis of Orthogonal Partial Least Squares (OPLS-DA) by salivary transflectance mode with one latent variable and one orthogonal signal correction component were used. The model generated predictions with 100 % sensitivity, specificity and accuracy. With the proposed model, in a single application of an individual's saliva in the FTIR equipment, results related to the detection of SARS-CoV-2 can be obtained in a few minutes of spectral evaluation.
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Affiliation(s)
- Calebe Fernando Juchem
- Postgraduate Program in Medical Sciences, Universidade do Vale do Taquari - Univates, Lajeado, RS, Brazil
| | - Valeriano Antonio Corbellini
- Postgraduate Program in Health Promotion, Postgraduate Program in Environmental Technology, Universidade de Santa Cruz do Sul, Santa Cruz do Sul, RS, Brazil
| | - Andréa Horst
- Life Sciences Center, Universidade do Vale do Taquari - Univates, Lajeado, RS, Brazil
| | - Daiane Heidrich
- Postgraduate Program in Medical Sciences, Universidade do Vale do Taquari - Univates, Lajeado, RS, Brazil; Postgraduate Program in Biotechnology, Universidade do Vale do Taquari - Univates, Lajeado, RS, Brazil.
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Mateus Pereira de Souza N, Kimberli Abeg da Rosa D, de Moraes C, Caeran M, Bordin Hoffmann M, Pozzobon Aita E, Prochnow L, Lya Assmann da Motta A, Antonio Corbellini V, Rieger A. Structural characterization of DNA amplicons by ATR-FTIR spectroscopy as a guide for screening metainflammatory disorders in blood plasma. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123897. [PMID: 38266599 DOI: 10.1016/j.saa.2024.123897] [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: 11/05/2023] [Revised: 01/08/2024] [Accepted: 01/14/2024] [Indexed: 01/26/2024]
Abstract
Attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy is a promising rapid, reagent-free, and low-cost technique considered for clinical translation. It allows to characterize biofluids proteome, lipidome, and metabolome at once. Metainflammatory disorders share a constellation of chronic systemic inflammation, oxidative stress, aberrant adipogenesis, and hypoxia, that significantly increased cardiovascular and cancer risk. As a result, these patients have elevated concentration of cfDNA in the bloodstream. Considering this, DNA amplicons were analyzed by ATR-FTIR at 3 concentrations with 1:100 dilution: (IU/mL): 718, 7.18, and 0.0718. The generated IR spectrum was used as a guide for variable selection. The main peaks in the biofingerprint (1800-900 cm-1) give important information about the base, base-sugar, phosphate, and sugar-phosphate transitions of DNA. To validate our method of selecting variables in blood plasma, 38 control subjects and 12 with metabolic syndrome were used. Using the wavenumbers of the peaks in the biofingerprint of the DNA amplicons, was generated a discriminant analysis model with Mahalanobis distance in blood plasma, and 100 % discrimination accuracy was obtained. In addition, the interval 1475-1188 cm-1 showed the greatest sensitivity to variation in the concentration of DNA amplicons, so curve fitting with Gaussian funcion was performed, obtaining adjusted-R2 of 0.993. PCA with Mahalanobis distance in the interval 1475-1188 cm-1 obtained an accuracy of 96 % and PLS-DA modeling in the interval 1475-1088 cm-1 obtained AUC = 0.991 with sensitivity of 95 % and specificity of 100 %. Therefore, ATR-FTIR spectroscopy with variable selection guided by DNA IR peaks is a promising and efficient method to be applied in metainflammatory disorders.
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Affiliation(s)
| | - Dhuli Kimberli Abeg da Rosa
- Bioprocess Engineering and Biotechnology, State University of Rio Grande do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Caroline de Moraes
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Mariana Caeran
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Mairim Bordin Hoffmann
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Eduardo Pozzobon Aita
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Laura Prochnow
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Anna Lya Assmann da Motta
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Valeriano Antonio Corbellini
- Department of Sciences, Humanities, and Education, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil; Postgraduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil; Postgraduate Program in Environmental Technology, University of Santa Cruz do Sul, Rio Grande do Sul, Brazil.
| | - Alexandre Rieger
- Department of Life Sciences, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil; Postgraduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, Rio Grande do Sul, Brazil; Postgraduate Program in Environmental Technology, University of Santa Cruz do Sul, Rio Grande do Sul, Brazil.
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Oudahmane I, Sarkees E, Taha F, Vanmansart J, Vuiblet V, Larre S, Piot O. To what extent does freezing impact the mid-infrared signature of urine? Case of patients attending urology department. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 309:123820. [PMID: 38168660 DOI: 10.1016/j.saa.2023.123820] [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: 08/21/2023] [Revised: 11/30/2023] [Accepted: 12/26/2023] [Indexed: 01/05/2024]
Abstract
Urine is a very interesting and attractive biofluid for biomarker discovery and medical diagnosis research due to its non-invasiveness collection and richness of potential biomarkers. Fourier-Transform Infrared (FTIR) spectroscopy applied on urine samples is a promising tool that could be used as a screening method for various diseases. However, during method development, frozen urine is more accessible, especially for inter-laboratory studies, whereas in routine application fresh urine is more convenient. Here, the objective of our work is to evaluate the freezing impact on mid-infrared signature of urine samples. Therefore, both fresh and frozen urine samples from twenty patients were analysed in a dried form. These samples were collected from patients consulting for cystoscopy examination. Simultaneously, centrifugation was also conducted on 10 of all included patients. Principal component analysis (PCA) revealed that patient inter-variabilities are higher than variability due to the freezing step. Then, Euclidean distance between fresh and frozen urine of each patient highlighted that the impact of freezing is different from one patient to another. Adding the centrifugation step slightly minimized intra-patient variability compared to not centrifugated samples. This study contributes to define experimental conditions for urine analysis development for translational application in biomedical field.
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Affiliation(s)
- Imane Oudahmane
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France
| | - Elie Sarkees
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France
| | - Fayek Taha
- Department of Urology, CHU de Reims, Reims, France
| | - Jade Vanmansart
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France
| | - Vincent Vuiblet
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France; Department of Biopathology, CHU de Reims, Reims, France
| | - Stéphane Larre
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France; Department of Urology, CHU de Reims, Reims, France
| | - Olivier Piot
- BioSpecT EA7506 Laboratory, Université de Reims Champagne-Ardenne, Reims, France; Cellular and Tissular Imaging Platform (PICT), Université de Reims Champagne-Ardenne, Reims, France.
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Li YP, Lu TY, Huang FR, Zhang WM, Chen ZQ, Guang PW, Deng LY, Yang XH. Differential diagnosis of Crohn's disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning. World J Gastroenterol 2024; 30:1377-1392. [PMID: 38596500 PMCID: PMC11000079 DOI: 10.3748/wjg.v30.i10.1377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/02/2024] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Crohn's disease (CD) is often misdiagnosed as intestinal tuberculosis (ITB). However, the treatment and prognosis of these two diseases are dramatically different. Therefore, it is important to develop a method to identify CD and ITB with high accuracy, specificity, and speed. AIM To develop a method to identify CD and ITB with high accuracy, specificity, and speed. METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB. Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis. RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm-1 and 1234 cm-1 bands, and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy, specificity, and sensitivity of 91.84%, 92.59%, and 90.90%, respectively, for the differential diagnosis of CD and ITB. CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level, and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.
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Affiliation(s)
- Yuan-Peng Li
- College of Physical Science and Technology, Guangxi Normal University, Guilin, Guangxi 541004, China
| | - Tian-Yu Lu
- Department of Gastroenterology, The Affiliated Hospital of South University of Science and Technology, Shenzhen 518000, Guangdong Province, China
| | - Fu-Rong Huang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Wei-Min Zhang
- Department of Gastroenterology, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou 510632, Guangdong Province, China
| | - Zhen-Qiang Chen
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Pei-Wen Guang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Liang-Yu Deng
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
| | - Xin-Hao Yang
- Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
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Pacher G, Franca T, Lacerda M, Alves NO, Piranda EM, Arruda C, Cena C. Diagnosis of Cutaneous Leishmaniasis Using FTIR Spectroscopy and Machine Learning: An Animal Model Study. ACS Infect Dis 2024; 10:467-474. [PMID: 38189234 DOI: 10.1021/acsinfecdis.3c00430] [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] [Indexed: 01/09/2024]
Abstract
Cutaneous leishmaniasis (CL) is a polymorphic and spectral skin disease caused by Leishmania spp. protozoan parasites. CL is difficult to diagnose because conventional methods are time-consuming, expensive, and low-sensitive. Fourier transform infrared spectroscopy (FTIR) with machine learning (ML) algorithms has been explored as an alternative to achieve fast and accurate results for many disease diagnoses. Besides the high accuracy demonstrated in numerous studies, the spectral variations between infected and noninfected groups are too subtle to be noticed. Since variability in sample set characteristics (such as sex, age, and diet) often leads to significant data variance and limits the comprehensive understanding of spectral characteristics and immune responses, we investigate a novel methodology for diagnosing CL in an animal model study. Blood serum, skin lesions, and draining popliteal lymph node samples were collected from Leishmania (Leishmania) amazonensis-infected BALB/C mice under experimental conditions. The FTIR method and ML algorithms accurately differentiated between infected (CL group) and noninfected (control group) samples. The best overall accuracy (∼72%) was obtained in an external validation test using principal component analysis and support vector machine algorithms in the 1800-700 cm-1 range for blood serum samples. The accuracy achieved in analyzing skin lesions and popliteal lymph node samples was satisfactory; however, notable disparities emerged in the validation tests compared to results obtained from blood samples. This discrepancy is likely attributed to the elevated sample variability resulting from molecular compositional differences. According to the findings, the successful functioning of prediction models is mainly related to data analysis rather than the differences in the molecular composition of the samples.
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Affiliation(s)
- Gabriela Pacher
- Laboratório de Parasitologia Humana, Instituto de Biociências, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Thiago Franca
- Laboratório de Óptica e Fotônica (SISFOTON-UFMS), Instituto de Física, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Miller Lacerda
- Laboratório de Óptica e Fotônica (SISFOTON-UFMS), Instituto de Física, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Natália O Alves
- Laboratório de Parasitologia Humana, Instituto de Biociências, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Eliane M Piranda
- Laboratório de Parasitologia Humana, Instituto de Biociências, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Carla Arruda
- Laboratório de Parasitologia Humana, Instituto de Biociências, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
| | - Cícero Cena
- Laboratório de Óptica e Fotônica (SISFOTON-UFMS), Instituto de Física, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79070-900, Brazil
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10
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Voronina L, Fleischmann F, Šimunović J, Ludwig C, Novokmet M, Žigman M. Probing Blood Plasma Protein Glycosylation with Infrared Spectroscopy. Anal Chem 2024. [PMID: 38324652 PMCID: PMC10882574 DOI: 10.1021/acs.analchem.3c03589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The health state of an individual is closely linked to the glycosylation patterns of his or her blood plasma proteins. However, obtaining this information requires cost- and time-efficient analytical methods. We put forward infrared spectroscopy, which allows label-free analysis of protein glycosylation but so far has only been applied to analysis of individual proteins. Although spectral information does not directly provide the molecular structure of the glycans, it is sensitive to changes therein and covers all types of glycosidic linkages. Combining single-step ion exchange chromatography with infrared spectroscopy, we developed a workflow that enables the separation and analysis of major protein classes in blood plasma. Our results demonstrate that infrared spectroscopy can identify different patterns and global levels of glycosylation of intact plasma proteins. To showcase the strengths and limitations of the proposed approach, we compare the glycoforms of human and bovine alpha-1-acid glycoproteins, which exhibit highly variable global levels of glycosylation. To independently evaluate our conclusions, the glycan moieties of human alpha-1-acid glycoprotein were further analyzed using an established glycomics workflow. Importantly, the chromatographic separation of blood plasma improves the detection of aberrant glycoforms of a given protein as compared to infrared spectroscopy of bulk plasma. The presented approach allows a time-efficient comparison of glycosylation patterns of multiple plasma proteins, opening new avenues for biomedical probing.
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Affiliation(s)
- Liudmila Voronina
- Ludwig Maximilian University of Munich, Garching 85748, Germany
- Max Planck Institute of Quantum Optics, Garching 85748, Germany
| | - Frank Fleischmann
- Ludwig Maximilian University of Munich, Garching 85748, Germany
- Max Planck Institute of Quantum Optics, Garching 85748, Germany
| | - Jelena Šimunović
- Glycoscience Research Laboratory, Genos Ltd., Zagreb 10000, Croatia
| | - Christina Ludwig
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich (TUM), Freising 85354, Germany
| | - Mislav Novokmet
- Glycoscience Research Laboratory, Genos Ltd., Zagreb 10000, Croatia
| | - Mihaela Žigman
- Ludwig Maximilian University of Munich, Garching 85748, Germany
- Max Planck Institute of Quantum Optics, Garching 85748, Germany
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11
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Thiéfin G, Bertrand D, Untereiner V, Garnotel R, Bronowicki JP, Sockalingum GD. Serum infrared spectral profile is predictive of the degree of hepatic fibrosis in chronic hepatitis C patients. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 305:123433. [PMID: 37774586 DOI: 10.1016/j.saa.2023.123433] [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: 04/25/2023] [Revised: 09/15/2023] [Accepted: 09/18/2023] [Indexed: 10/01/2023]
Abstract
Assessment of liver fibrosis is crucial to guide the therapeutic strategy in patients with chronic liver disease. We investigated the potential of serum Fourier transform infrared (FTIR) spectroscopy for assessing the degree of hepatic fibrosis in patients with chronic hepatitis C (CHC). The study was conducted on dried serum samples from 94 CHC patients at different histological stages of hepatic fibrosis: METAVIR F0 (n = 20), F1 (n = 17), F2 (n = 20), F3 (n = 20) and F4 (n = 17). Transmission FTIR spectra were acquired in the 4000-400 cm-1 range. Wavenumbers were selected by genetic algorithm (GA) according to their diagnostic performance as assessed by a partial least squares discriminant analysis (PLS-DA) model using a training and a validation set to differentiate severe stages of fibrosis from mild or moderate ones. The GA procedure was applied 50 times on randomly selected sets. Furthermore, the best set of wavenumbers was re-tested in 1000 randomly selected validation sets. Wavenumbers selected by GA corresponded to functional groups present in lipids, proteins, and carbohydrates. This model allowed to identify patients with cirrhosis (METAVIR F4), patients with advanced fibrosis (METAVIR F3 and F4), and patients with significant fibrosis (METAVIR F2, F3 and F4), with AUROC (Area Under the Receiver Operating Characteristic) of 0.88, 0.85 and 0.85, respectively. Thus, serum FTIR spectroscopy appears to have a strong potential as a new diagnostic tool for assessing the degree of fibrosis in patients with chronic liver disease.
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Affiliation(s)
- Gérard Thiéfin
- Université de Reims Champagne-Ardenne, BioSpecT-EA7506, UFR de Pharmacie, 51097 Reims, France; Service d'Hépato-Gastroentérologie et de Cancérologie Digestive, Centre Hospitalier Universitaire de Reims, 51092 Reims, France
| | | | - Valérie Untereiner
- Université de Reims Champagne-Ardenne, Plateforme en Imagerie Cellulaire et Tissulaire (PICT), 51097 Reims Cedex, France
| | - Roselyne Garnotel
- Université de Reims Champagne-Ardenne, BioSpecT-EA7506, UFR de Pharmacie, 51097 Reims, France; Laboratoire de Biochimie-Pharmacologie-Toxicologie, Centre Hospitalier Universitaire de Reims, 51092, Reims, France
| | - Jean-Pierre Bronowicki
- Service d'Hépato-Gastroentérologie, CHRU de Nancy-Brabois, Vandœuvre-lès-Nancy, 54511, France
| | - Ganesh D Sockalingum
- Université de Reims Champagne-Ardenne, BioSpecT-EA7506, UFR de Pharmacie, 51097 Reims, France.
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12
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Raposo-Neto JJ, Kowalski-Neto E, Luiz WB, Fonseca EA, Cedro AKCL, Singh MN, Martin FL, Vassallo PF, Campos LCG, Barauna VG. Near-Infrared Spectroscopy with Supervised Machine Learning as a Screening Tool for Neutropenia. J Pers Med 2023; 14:9. [PMID: 38276224 PMCID: PMC10817549 DOI: 10.3390/jpm14010009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 12/05/2023] [Accepted: 12/12/2023] [Indexed: 01/27/2024] Open
Abstract
The use of non-invasive tools in conjunction with artificial intelligence (AI) to detect diseases has the potential to revolutionize healthcare. Near-infrared spectroscopy (NIR) is a technology that can be used to analyze biological samples in a non-invasive manner. This study evaluated the use of NIR spectroscopy in the fingertip to detect neutropenia in solid-tumor oncologic patients. A total of 75 patients were enrolled in the study. Fingertip NIR spectra and complete blood counts were collected from each patient. The NIR spectra were pre-processed using Savitzky-Golay smoothing and outlier detection. The pre-processed data were split into training/validation and test sets using the Kennard-Stone method. A toolbox of supervised machine learning classification algorithms was applied to the training/validation set using a stratified 5-fold cross-validation regimen. The algorithms included linear discriminant analysis (LDA), logistic regression (LR), random forest (RF), multilayer perceptron (MLP), and support vector machines (SVMs). The SVM model performed best in the validation step, with 85% sensitivity, 89% negative predictive value (NPV), and 64% accuracy. The SVM model showed 67% sensitivity, 82% NPV, and 57% accuracy on the test set. These results suggest that NIR spectroscopy in the fingertip, combined with machine learning methods, can be used to detect neutropenia in solid-tumor oncology patients in a non-invasive and timely manner. This approach could help reduce exposure to invasive tests and prevent neutropenic patients from inadvertently undergoing chemotherapy.
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Affiliation(s)
- José Joaquim Raposo-Neto
- Department of Health Sciences, State University of Santa Cruz, Ilhéus 45662-900, Brazil;
- Laboratory of Applied Pathology and Genetics, State University of Santa Cruz, Ilhéus 45662-900, Brazil; (W.B.L.); (E.A.F.); (A.K.C.L.C.)
| | - Eduardo Kowalski-Neto
- Department of Health Sciences, State University of Santa Cruz, Ilhéus 45662-900, Brazil;
| | - Wilson Barros Luiz
- Laboratory of Applied Pathology and Genetics, State University of Santa Cruz, Ilhéus 45662-900, Brazil; (W.B.L.); (E.A.F.); (A.K.C.L.C.)
- Department of Biological Science, State University of Santa Cruz, Ilhéus 45662-900, Brazil
| | - Estherlita Almeida Fonseca
- Laboratory of Applied Pathology and Genetics, State University of Santa Cruz, Ilhéus 45662-900, Brazil; (W.B.L.); (E.A.F.); (A.K.C.L.C.)
- Department of Biological Science, State University of Santa Cruz, Ilhéus 45662-900, Brazil
| | - Anna Karla Costa Logrado Cedro
- Laboratory of Applied Pathology and Genetics, State University of Santa Cruz, Ilhéus 45662-900, Brazil; (W.B.L.); (E.A.F.); (A.K.C.L.C.)
- Department of Biological Science, State University of Santa Cruz, Ilhéus 45662-900, Brazil
| | - Maneesh N. Singh
- Biocel UK Ltd., Hull HU10 6TS, UK; (M.N.S.); (F.L.M.)
- Chesterfield Royal Hospital, Chesterfield S44 5BL, UK
| | - Francis L. Martin
- Biocel UK Ltd., Hull HU10 6TS, UK; (M.N.S.); (F.L.M.)
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Whinney Heys Road, Blackpool FY3 8NR, UK
| | - Paula Frizera Vassallo
- Clinical Hospital Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil;
| | - Luciene Cristina Gastalho Campos
- Department of Health Sciences, State University of Santa Cruz, Ilhéus 45662-900, Brazil;
- Laboratory of Applied Pathology and Genetics, State University of Santa Cruz, Ilhéus 45662-900, Brazil; (W.B.L.); (E.A.F.); (A.K.C.L.C.)
- Department of Biological Science, State University of Santa Cruz, Ilhéus 45662-900, Brazil
| | - Valerio Garrone Barauna
- Department of Physiological Science, Federal University of Espírito Santo, Vitória 29932-540, Brazil;
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13
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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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14
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Mitu B, Trojan V, Halámková L. Sex Determination of Human Nails Based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy in Forensic Context. SENSORS (BASEL, SWITZERLAND) 2023; 23:9412. [PMID: 38067785 PMCID: PMC10708700 DOI: 10.3390/s23239412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023]
Abstract
This study reports on the successful use of a machine learning approach using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy for the classification and prediction of a donor's sex from the fingernails of 63 individuals. A significant advantage of ATR FT-IR is its ability to provide a specific spectral signature for different samples based on their biochemical composition. The infrared spectrum reveals unique vibrational features of a sample based on the different absorption frequencies of the individual functional groups. This technique is fast, simple, non-destructive, and requires only small quantities of measured material with minimal-to-no sample preparation. However, advanced multivariate techniques are needed to elucidate multiplex spectral information and the small differences caused by donor characteristics. We developed an analytical method using ATR FT-IR spectroscopy advanced with machine learning (ML) based on 63 donors' fingernails (37 males, 26 females). The PLS-DA and ANN models were established, and their generalization abilities were compared. Here, the PLS scores from the PLS-DA model were used for an artificial neural network (ANN) to create a classification model. The proposed ANN model showed a greater potential for predictions, and it was validated against an independent dataset, which resulted in 92% correctly classified spectra. The results of the study are quite impressive, with 100% accuracy achieved in correctly classifying donors as either male or female at the donor level. Here, we underscore the potential of ML algorithms to leverage the selectivity of ATR FT-IR spectroscopy and produce predictions along with information about the level of certainty in a scientifically defensible manner. This proof-of-concept study demonstrates the value of ATR FT-IR spectroscopy as a forensic tool to discriminate between male and female donors, which is significant for forensic applications.
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Affiliation(s)
- Bilkis Mitu
- Department of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409, USA;
| | - Václav Trojan
- Cannabis Facility, International Clinical Research Centre, St. Anne’s University Hospital, 602 00 Brno, Czech Republic;
- Department of Natural Drugs, Faculty of Pharmacy, Masaryk University, 612 00 Brno, Czech Republic
| | - Lenka Halámková
- Department of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409, USA;
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15
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Condino F, Crocco MC, Pirritano D, Petrone A, Del Giudice F, Guzzi R. A Linear Predictor Based on FTIR Spectral Biomarkers Improves Disease Diagnosis Classification: An Application to Multiple Sclerosis. J Pers Med 2023; 13:1596. [PMID: 38003911 PMCID: PMC10672539 DOI: 10.3390/jpm13111596] [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: 09/27/2023] [Revised: 11/02/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that can lead to long-term disability. The diagnosis of MS is not simple and requires many instrumental and clinical tests. Sampling easily collected biofluids using spectroscopic approaches is becoming of increasing interest in the medical field to integrate and improve diagnostic procedures. Here we present a statistical approach where we combine a number of spectral biomarkers derived from the ATR-FTIR spectra of blood plasma samples of healthy control subjects and MS patients, to obtain a linear predictor useful for discriminating between the two groups of individuals. This predictor provides a simple tool in which the contribution of different molecular components is summarized and, as a result, the sensitivity (80%) and specificity (93%) of the identification are significantly improved compared to those obtained with typical classification algorithms. The strategy proposed can be very helpful when applied to the diagnosis of diseases whose presence is reflected in a minimal way in the analyzed biofluids (blood and its derivatives), as it is for MS as well as for other neurological disorders.
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Affiliation(s)
- Francesca Condino
- Department of Economics, Statistics and Finance ”Giovanni Anania”, University of Calabria, 87036 Rende, Italy;
| | - Maria Caterina Crocco
- STAR Research Infrastructure, University of Calabria, 87036 Rende, Italy;
- Department of Physics, Molecular Biophysics Laboratory, University of Calabria, 87036 Rende, Italy
| | - Domenico Pirritano
- SOC Neurologia, Azienda Ospedaliero-Universitaria Renato Dulbecco, 88100 Catanzaro, Italy;
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
| | - Alfredo Petrone
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
| | - Francesco Del Giudice
- UOC Neurologia, Azienda Ospedaliera dell’Annunziata, 87100 Cosenza, Italy; (A.P.); (F.D.G.)
- SOC Neurologia, Ospedale Jazzolino, Azienda Ospedaliera Provinciale, 89900 Vibo Valentia, Italy
| | - Rita Guzzi
- STAR Research Infrastructure, University of Calabria, 87036 Rende, Italy;
- CNR-NANOTEC, Department of Physics, University of Calabria, 87036 Rende, Italy
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16
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Hossain MI, Nanda SS, Cho S, Lee B, Kim BJ, Choi JY, Yi DK. Gold Nanorod Density-Dependent Label-Free Bacteria Sensing on a Flake-like 3D Graphene-Based Device by SERS. BIOSENSORS 2023; 13:962. [PMID: 37998137 PMCID: PMC10669247 DOI: 10.3390/bios13110962] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 10/21/2023] [Accepted: 10/25/2023] [Indexed: 11/25/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) is an effective technique for biosensing, enabling label-free detection of biomolecules with enhanced sensitivity. There is a tremendous probability of signal failure in Raman frequencies because of the scattering of the Raman radiation in liquids, effective SERS improvement is required to reduce this issue when considering liquid specimens. We examined a liquid bacterial sample, investigating the electrostatic interactions of the bacterial samples with gold nanorods (AuNRs) and graphene. We established a voltage-gated 3D graphene functionalized with an AuNR-based device on the silicon substrate for SERS measurements when the applied voltage ranges from 0 to 3 V. Moreover, AuNRs density-susceptible bacterial sample analysis with varied concentrations of bacterial samples has also been described. Using bacterial SERS analysis, the bacterial components amide II (1555-1565 cm-1) and amide III (1250-1350 cm-1) have been discovered for both bacteria, Gram-positive, Listeria monocytogenes and Gram-negative, Salmonella typhi. Our fabricated device affords an interesting label-free, rapid, and reproducible bacterial sample analysis based on the density of the AuNRs when functionalizing flake-like 3D graphene, which can help facilitate label-free bacteria sensing platforms.
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Affiliation(s)
- Md Imran Hossain
- Department of Chemistry, Myongji University, Yongin 17058, Republic of Korea; (M.I.H.)
| | - Sitansu Sekhar Nanda
- Department of Chemistry, Myongji University, Yongin 17058, Republic of Korea; (M.I.H.)
| | - Sooheon Cho
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Bom Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Bum Jun Kim
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jae-Young Choi
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Dong Kee Yi
- Department of Chemistry, Myongji University, Yongin 17058, Republic of Korea; (M.I.H.)
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17
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Mokari A, Guo S, Bocklitz T. Exploring the Steps of Infrared (IR) Spectral Analysis: Pre-Processing, (Classical) Data Modelling, and Deep Learning. Molecules 2023; 28:6886. [PMID: 37836728 PMCID: PMC10574384 DOI: 10.3390/molecules28196886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/13/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023] Open
Abstract
Infrared (IR) spectroscopy has greatly improved the ability to study biomedical samples because IR spectroscopy measures how molecules interact with infrared light, providing a measurement of the vibrational states of the molecules. Therefore, the resulting IR spectrum provides a unique vibrational fingerprint of the sample. This characteristic makes IR spectroscopy an invaluable and versatile technology for detecting a wide variety of chemicals and is widely used in biological, chemical, and medical scenarios. These include, but are not limited to, micro-organism identification, clinical diagnosis, and explosive detection. However, IR spectroscopy is susceptible to various interfering factors such as scattering, reflection, and interference, which manifest themselves as baseline, band distortion, and intensity changes in the measured IR spectra. Combined with the absorption information of the molecules of interest, these interferences prevent direct data interpretation based on the Beer-Lambert law. Instead, more advanced data analysis approaches, particularly artificial intelligence (AI)-based algorithms, are required to remove the interfering contributions and, more importantly, to translate the spectral signals into high-level biological/chemical information. This leads to the tasks of spectral pre-processing and data modeling, the main topics of this review. In particular, we will discuss recent developments in both tasks from the perspectives of classical machine learning and deep learning.
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Affiliation(s)
- Azadeh Mokari
- Leibniz Institute of Photonic Technology, Member of Research Alliance “Leibniz Health Technologies”, 07745 Jena, Germany (S.G.)
- Institute of Physical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Shuxia Guo
- Leibniz Institute of Photonic Technology, Member of Research Alliance “Leibniz Health Technologies”, 07745 Jena, Germany (S.G.)
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Member of Research Alliance “Leibniz Health Technologies”, 07745 Jena, Germany (S.G.)
- Institute of Physical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany
- Institute of Computer Science, Faculty of Mathematics, Physics & Computer Science, University Bayreuth, Universitaet sstraße 30, 95447 Bayreuth, Germany
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18
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Duckworth E, Mortimer M, Al‐Sarireh B, Kanamarlapudi V, Roy D. Frontline clinical diagnosis-FTIR on pancreatic cancer. Cancer Med 2023; 12:17340-17345. [PMID: 37466344 PMCID: PMC10501286 DOI: 10.1002/cam4.6346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 06/23/2023] [Accepted: 07/05/2023] [Indexed: 07/20/2023] Open
Abstract
OBJECTIVE Accurate, easily accessible and economically viable cancer diagnostic tools are pivotal in improving the abysmal 5% survival rate of pancreatic cancer. METHODS A novel, affordable, non-invasive diagnostic method has been developed by combining measurement precision of infrared spectroscopy with classification using machine learning tools. RESULTS Diagnosis accuracy as high as 90% has been achieved. The study investigated urine and blood from pancreas cancer patients and healthy volunteers, and significantly improved accuracy by focusing on sweet-spots within blood plasma fractions containing molecules within a narrow range of molecular weights.
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19
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Schulze HG, Rangan S, Vardaki MZ, Blades MW, Turner RFB, Piret JM. Two-Dimensional Clustering of Spectral Changes for the Interpretation of Raman Hyperspectra. APPLIED SPECTROSCOPY 2023; 77:835-847. [PMID: 36238996 PMCID: PMC10466967 DOI: 10.1177/00037028221133851] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
Two-dimensional correlation spectroscopy (2D-COS) is a technique that permits the examination of synchronous and asynchronous changes present in hyperspectral data. It produces two-dimensional correlation coefficient maps that represent the mutually correlated changes occurring at all Raman wavenumbers during an implemented perturbation. To focus our analysis on clusters of wavenumbers that tend to change together, we apply a k-means clustering to the wavenumber profiles in the perturbation domain decomposition of the two-dimensional correlation coefficient map. These profiles (or trends) reflect peak intensity changes as a function of the perturbation. We then plot the co-occurrences of cluster members two-dimensionally in a manner analogous to a two-dimensional correlation coefficient map. Because wavenumber profiles are clustered based on their similarity, two-dimensional cluster member spectra reveal which Raman peaks change in a similar manner, rather than how much they are correlated. Furthermore, clustering produces a discrete partitioning of the wavenumbers, thus a two-dimensional cluster member spectrum exhibits a discrete presentation of related Raman peaks as opposed to the more continuous representations in a two-dimensional correlation coefficient map. We demonstrate first the basic principles of the technique with the aid of synthetic data. We then apply it to Raman spectra obtained from a polystyrene perchlorate model system followed by Raman spectra from mammalian cells fixed with different percentages of methanol. Both data sets were designed to produce differential changes in sample components. In both cases, all the peaks pertaining to a given component should then change in a similar manner. We observed that component-based profile clustering did occur for polystyrene and perchlorate in the model system and lipids, nucleic acids, and proteins in the mammalian cell example. This confirmed that the method can translate to "real world" samples. We contrast these results with two-dimensional correlation spectroscopy results. To supplement interpretation, we present the cluster-segmented mean spectrum of the hyperspectral data. Overall, this technique is expected to be a valuable adjunct to two-dimensional correlation spectroscopy to further facilitate hyperspectral data interpretation and analysis.
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Affiliation(s)
| | - Shreyas Rangan
- Michael Smith Laboratories, The University of British Columbia, Vancouver, BC, Canada
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Martha Z. Vardaki
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
| | - Michael W. Blades
- Department of Chemistry, The University of British Columbia, Vancouver, BC, Canada
| | - Robin F. B. Turner
- Michael Smith Laboratories, The University of British Columbia, Vancouver, BC, Canada
- Department of Chemistry, The University of British Columbia, Vancouver, BC, Canada
- Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - James M. Piret
- Michael Smith Laboratories, The University of British Columbia, Vancouver, BC, Canada
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
- Department of Chemical and Biological Engineering, The University of British Columbia, Vancouver, BC, Canada
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20
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Delrue C, De Bruyne S, Speeckaert MM. Unlocking the Diagnostic Potential of Saliva: A Comprehensive Review of Infrared Spectroscopy and Its Applications in Salivary Analysis. J Pers Med 2023; 13:907. [PMID: 37373896 DOI: 10.3390/jpm13060907] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/20/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
Infrared (IR) spectroscopy is a noninvasive and rapid analytical technique that provides information on the chemical composition, structure, and conformation of biomolecules in saliva. This technique has been widely used to analyze salivary biomolecules, owing to its label-free advantages. Saliva contains a complex mixture of biomolecules including water, electrolytes, lipids, carbohydrates, proteins, and nucleic acids which are potential biomarkers for several diseases. IR spectroscopy has shown great promise for the diagnosis and monitoring of diseases such as dental caries, periodontitis, infectious diseases, cancer, diabetes mellitus, and chronic kidney disease, as well as for drug monitoring. Recent advancements in IR spectroscopy, such as Fourier-transform infrared (FTIR) spectroscopy and attenuated total reflectance (ATR) spectroscopy, have further enhanced its utility in salivary analysis. FTIR spectroscopy enables the collection of a complete IR spectrum of the sample, whereas ATR spectroscopy enables the analysis of samples in their native form, without the need for sample preparation. With the development of standardized protocols for sample collection and analysis and further advancements in IR spectroscopy, the potential for salivary diagnostics using IR spectroscopy is vast.
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Affiliation(s)
- Charlotte Delrue
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Sander De Bruyne
- Department of Clinical Biology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Marijn M Speeckaert
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
- Research Foundation-Flanders (FWO), 1000 Brussels, Belgium
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Herrera-Domínguez M, Lim K, Aguilar-Hernández I, García-García A, Minteer SD, Ornelas-Soto N, Garcia-Morales R. Detection of Acetaminophen in Groundwater by Laccase-Based Amperometric Biosensors Using MoS 2 Modified Carbon Paper Electrodes. SENSORS (BASEL, SWITZERLAND) 2023; 23:4633. [PMID: 37430547 DOI: 10.3390/s23104633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 07/12/2023]
Abstract
The use of enzyme-based biosensors for the detection and quantification of analytes of interest such as contaminants of emerging concern, including over-the-counter medication, provides an attractive alternative compared to more established techniques. However, their direct application to real environmental matrices is still under investigation due to the various drawbacks in their implementation. Here, we report the development of bioelectrodes using laccase enzymes immobilized onto carbon paper electrodes modified with nanostructured molybdenum disulfide (MoS2). The laccase enzymes were two isoforms (LacI and LacII) produced and purified from the fungus Pycnoporus sanguineus CS43 that is native to Mexico. A commercial purified enzyme from the fungus Trametes versicolor (TvL) was also evaluated to compare their performance. The developed bioelectrodes were used in the biosensing of acetaminophen, a drug widely used to relieve fever and pain, and of which there is recent concern about its effect on the environment after its final disposal. The use of MoS2 as a transducer modifier was evaluated, and it was found that the best detection was achieved using a concentration of 1 mg/mL. Moreover, it was found that the laccase with the best biosensing efficiency was LacII, which achieved an LOD of 0.2 µM and a sensitivity of 0.108 µA/µM cm2 in the buffer matrix. Moreover, the performance of the bioelectrodes in a composite groundwater sample from Northeast Mexico was analyzed, achieving an LOD of 0.5 µM and a sensitivity of 0.015 µA/µM cm2. The LOD values found are among the lowest reported for biosensors based on the use of oxidoreductase enzymes, while the sensitivity is the highest currently reported.
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Affiliation(s)
- Marcela Herrera-Domínguez
- Laboratorio de Nanotecnología Ambiental, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
| | - Koun Lim
- Department of Chemistry and Materials Science & Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Iris Aguilar-Hernández
- Laboratorio de Nanotecnología Ambiental, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
| | - Alejandra García-García
- Laboratorio de Síntesis y Modificación de Nanoestructuras y Materiales Bidimensionales, Centro de Investigación en Materiales Avanzados S.C., Unidad Monterrey, Parque PIIT, Apodaca 66628, NL, Mexico
| | - Shelley D Minteer
- Department of Chemistry and Materials Science & Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Nancy Ornelas-Soto
- Laboratorio de Nanotecnología Ambiental, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
| | - Raúl Garcia-Morales
- Centro de Nanociencias y Nanotecnología, Universidad Nacional Autónoma de México, Carretera Tijuana-Ensenada Km. 107, Ensenada 22860, BC, Mexico
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22
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Delrue C, De Bruyne S, Speeckaert MM. The Potential Use of Near- and Mid-Infrared Spectroscopy in Kidney Diseases. Int J Mol Sci 2023; 24:ijms24076740. [PMID: 37047712 PMCID: PMC10094824 DOI: 10.3390/ijms24076740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/25/2023] [Accepted: 04/03/2023] [Indexed: 04/08/2023] Open
Abstract
Traditional renal biomarkers such as serum creatinine and albuminuria/proteinuria are rather insensitive since they change later in the course of the disease. In order to determine the extent and type of kidney injury, as well as to administer the proper therapy and enhance patient management, new techniques for the detection of deterioration of the kidney function are urgently needed. Infrared spectroscopy is a label-free and non-destructive technique having the potential to be a vital tool for quick and inexpensive routine clinical diagnosis of kidney disorders. The aim of this review is to provide an overview of near- and mid-infrared spectroscopy applications in patients with acute kidney injury and chronic kidney disease (e.g., diabetic nephropathy and glomerulonephritis).
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Affiliation(s)
- Charlotte Delrue
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Sander De Bruyne
- Department of Diagnostic Sciences, Ghent University Hospital, 9000 Ghent, Belgium
| | - Marijn M. Speeckaert
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
- Research Foundation-Flanders (FWO), 1000 Brussels, Belgium
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23
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Liang X, Wang G, Li Z, Chen R, Wu H, Li H, Shen C, Deng M, Hao Z, Wu S, Yu K, Wei X, Liu R, Zhang K, Sun Q, Wang Z. Accurate identification of traumatic lung injury (TLI) by ATR-FTIR spectroscopy combined with chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 288:122186. [PMID: 36481535 DOI: 10.1016/j.saa.2022.122186] [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: 09/22/2022] [Revised: 11/23/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
Abstract
Traumatic lung injury (TLI), which is a common mechanical injury, is receiving increasing attention because of its serious hazards. In forensic practices, accurately identifying TLI is of great importance for investigations and case trials. The main goal of this research was to identify TLI utilizing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics. The macroscopic appearance of lung tissue showed that identifying TLI in lung tissue at the decomposition stage is not feasible by only visualization, and significant pulmonary hypostasis was observed in the lungs regardless of whether the lung tissue was injured. Average spectra and principal component analysis (PCA) suggested that the biochemical difference between injured lung tissue samples from the TLI group and noninjured lung tissue samples from the negative control group was mainly attributed to the different structures and contents of proteins. Partial least squares discriminant analysis (PLS-DA) was then utilized to identify TLI with an accuracy of 96.4% and 98.6% based on the training set and the test set, respectively. Next, we focused on samples that were misclassified in the model and proposed that the misclassification could be caused by the pulmonary hypostasis effect. Therefore, two additional PCA and PLS-DA models were created to identify the pulmonary hypostatic areas between the TLI group and the negative control group and the nonpulmonary hypostatic areas between the TLI group and the negative control group. The PCA results indicated that the biochemical difference between the two groups was still associated with proteins, and the two PLS-DA models achieved 100% accuracy based on both the training and test sets. This result indicated that when pulmonary hypostasis was considered and the lung tissue was divided into pulmonary hypostatic areas and nonpulmonary hypostatic areas for separate comparisons, TLI identification was achieved with a greater accuracy than that obtained when the two areas were combined. This research confirms that the combined application of ATR-FTIR spectroscopy and chemometrics can be utilized to accurately identify TLI.
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Affiliation(s)
- Xinggong Liang
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Gongji Wang
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Zefeng Li
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Run Chen
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Hao Wu
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Huiyu Li
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Chen Shen
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Mingyan Deng
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Zeyi Hao
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Shuo Wu
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Kai Yu
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Xin Wei
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Ruina Liu
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Kai Zhang
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Qinru Sun
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
| | - Zhenyuan Wang
- Department of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
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24
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Kunitake JA, Sudilovsky D, Johnson LM, Loh HC, Choi S, Morris PG, Jochelson MS, Iyengar NM, Morrow M, Masic A, Fischbach C, Estroff LA. Biomineralogical signatures of breast microcalcifications. SCIENCE ADVANCES 2023; 9:eade3152. [PMID: 36812311 PMCID: PMC9946357 DOI: 10.1126/sciadv.ade3152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Microcalcifications, primarily biogenic apatite, occur in cancerous and benign breast pathologies and are key mammographic indicators. Outside the clinic, numerous microcalcification compositional metrics (e.g., carbonate and metal content) are linked to malignancy, yet microcalcification formation is dependent on microenvironmental conditions, which are notoriously heterogeneous in breast cancer. We interrogate multiscale heterogeneity in 93 calcifications from 21 breast cancer patients using an omics-inspired approach: For each microcalcification, we define a "biomineralogical signature" combining metrics derived from Raman microscopy and energy-dispersive spectroscopy. We observe that (i) calcifications cluster into physiologically relevant groups reflecting tissue type and local malignancy; (ii) carbonate content exhibits substantial intratumor heterogeneity; (iii) trace metals including zinc, iron, and aluminum are enhanced in malignant-localized calcifications; and (iv) the lipid-to-protein ratio within calcifications is lower in patients with poor composite outcome, suggesting that there is potential clinical value in expanding research on calcification diagnostic metrics to include "mineral-entrapped" organic matrix.
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Affiliation(s)
| | - Daniel Sudilovsky
- Department of Pathology and Laboratory Medicine, Cayuga Medical Center at Ithaca, Ithaca, NY 14850, USA
- Pathology Department, Kingman Regional Medical Center, Kingman, AZ 86409, USA
- Pathology Department, Western Arizona Medical Center, Bullhead City, AZ 86442, USA
- Pathology Department, Yuma Regional Medical Center, Yuma, AZ 85364, USA
| | - Lynn M. Johnson
- Cornell Statistical Consulting Unit, Cornell University, Ithaca, NY 14850, USA
| | - Hyun-Chae Loh
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Siyoung Choi
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - Patrick G. Morris
- Medical Oncology Service, Beaumont Hospital, Dublin, Ireland
- Breast Medicine Service, Department of Medicine, Memorial Sloan Kettering Cancer Center/Evelyn H. Lauder Breast and Imaging Center, New York, NY 10065, USA
- Department of Medicine, Weill Cornell Medical College, New York, NY 10021, USA
| | - Maxine S. Jochelson
- Department of Radiology, Memorial Sloan Kettering Cancer Center/Evelyn H. Lauder Breast and Imaging Center, New York, NY 10065, USA
| | - Neil M. Iyengar
- Department of Medicine, Weill Cornell Medical College, New York, NY 10021, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Monica Morrow
- Breast Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Admir Masic
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Corresponding author. (L.A.E.); (C.F.); (A.M.)
| | - Claudia Fischbach
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
- Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY 14850, USA
- Corresponding author. (L.A.E.); (C.F.); (A.M.)
| | - Lara A. Estroff
- Department of Materials Science and Engineering, Cornell University, Ithaca, NY 14850, USA
- Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY 14850, USA
- Corresponding author. (L.A.E.); (C.F.); (A.M.)
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25
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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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Prada P, Brunel B, Moulin D, Rouillon L, Netter P, Loeuille D, Slimano F, Bouche O, Peyrin-Biroulet L, Jouzeau JY, Piot O. Identification of circulating biomarkers of Crohn's disease and spondyloarthritis using Fourier transform infrared spectroscopy. JOURNAL OF BIOPHOTONICS 2023; 16:e202200200. [PMID: 36112612 DOI: 10.1002/jbio.202200200] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
Crohn's disease (CD) and spondyloarthritis (SpA) are two inflammatory diseases sharing many common features (genetic polymorphism, armamentarium). Both diseases lack diagnostic markers of certainty. While the diagnosis of CD is made by a combination of clinical, and biological criteria, the diagnosis of SpA may take several years to be confirmed. Based on the hypothesis that CD and SpA alter the biochemical profile of plasma, the objective of this study was to evaluate the analytical capability of Fourier transform infrared spectroscopy (FTIR) in identifying spectral biomarkers. Plasma from 104 patients was analyzed. After data processing of the spectra by Extended Multiplicative Signal Correction and linear discriminant analysis, we demonstrated that it was possible to distinguish CD and SpA from controls with an accuracy of 97% and 85% respectively. Spectral differences were mainly associated with proteins and lipids. This study showed that FTIR analysis is efficient to identify plasma biosignatures specific to CD or SpA.
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Affiliation(s)
- Pierre Prada
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
| | - Benjamin Brunel
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
- FEMTO-ST Institute, CNRS UMR-6174, Université de Bourgogne Franche-Comté, Besançon, France
| | - David Moulin
- Ingénierie Moléculaire et Ingénierie Articulaire (IMoPA), UMR-7365 CNRS, Faculté de Médecine, Université de Lorraine et Hôpital Universitaire de Nancy, Nancy, France
| | - Lise Rouillon
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
| | - Patrick Netter
- Ingénierie Moléculaire et Ingénierie Articulaire (IMoPA), UMR-7365 CNRS, Faculté de Médecine, Université de Lorraine et Hôpital Universitaire de Nancy, Nancy, France
| | - Damien Loeuille
- Ingénierie Moléculaire et Ingénierie Articulaire (IMoPA), UMR-7365 CNRS, Faculté de Médecine, Université de Lorraine et Hôpital Universitaire de Nancy, Nancy, France
| | - Florian Slimano
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
| | - Olivier Bouche
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
| | - Laurent Peyrin-Biroulet
- Département de Gastroentérologie, Hôpital Universitaire de Nancy-Brabois, Vandœuvre-lès-Nancy, France
| | - Jean-Yves Jouzeau
- Ingénierie Moléculaire et Ingénierie Articulaire (IMoPA), UMR-7365 CNRS, Faculté de Médecine, Université de Lorraine et Hôpital Universitaire de Nancy, Nancy, France
| | - Olivier Piot
- EA7506-BioSpectroscopie Translationnelle (BioSpecT), Université de Reims Champagne-Ardenne, Reims, France
- Plateforme d'Imagerie Cellulaire ou Tissulaire (PICT), Université de Reims Champagne-Ardenne, Reims, France
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27
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Sheehy G, Picot F, Dallaire F, Ember K, Nguyen T, Petrecca K, Trudel D, Leblond F. Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:025002. [PMID: 36825245 PMCID: PMC9941747 DOI: 10.1117/1.jbo.28.2.025002] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 01/30/2023] [Indexed: 05/25/2023]
Abstract
SIGNIFICANCE Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing. AIM An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise. RESULTS Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility. CONCLUSIONS A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.
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Affiliation(s)
- Guillaume Sheehy
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Fabien Picot
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Frédérick Dallaire
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Katherine Ember
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Tien Nguyen
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Division of Neuropathology, Department of Pathology, Montreal, Quebec, Canada
| | - Dominique Trudel
- Institut du cancer de Montréal, Montreal, Quebec, Canada
- Université de Montréal, Department of Pathology and Cellular Biology, Montreal, Quebec, Canada
- Center Hospitalier de l’Université de Montréal, Department of Pathology, Montreal, Quebec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
- Institut du cancer de Montréal, Montreal, Quebec, Canada
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28
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Zhao B, Zhai H, Shao H, Bi K, Zhu L. Potential of vibrational spectroscopy coupled with machine learning as a non-invasive diagnostic method for COVID-19. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 229:107295. [PMID: 36706562 PMCID: PMC9711896 DOI: 10.1016/j.cmpb.2022.107295] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/10/2022] [Accepted: 11/29/2022] [Indexed: 06/18/2023]
Abstract
BACKGROUND AND OBJECTIVE Efforts to alleviate the ongoing coronavirus disease 2019 (COVID-19) crisis showed that rapid, sensitive, and large-scale screening is critical for controlling the current infection and that of ongoing pandemics. METHODS Here, we explored the potential of vibrational spectroscopy coupled with machine learning to screen COVID-19 patients in its initial stage. Herein presented is a hybrid classification model called grey wolf optimized support vector machine (GWO-SVM). The proposed model was tested and comprehensively compared with other machine learning models via vibrational spectroscopic fingerprinting including saliva FTIR spectra dataset and serum Raman scattering spectra dataset. RESULTS For the unknown vibrational spectra, the presented GWO-SVM model provided an accuracy, specificity and F1_score value of 0.9825, 0.9714 and 0.9778 for saliva FTIR spectra dataset, respectively, while an overall accuracy, specificity and F1_score value of 0.9085, 0.9552 and 0.9036 for serum Raman scattering spectra dataset, respectively, which showed superiority than those of state-of-the-art models, thereby suggesting the suitability of the GWO-SVM model to be adopted in a clinical setting for initial screening of COVID-19 patients. CONCLUSIONS Prospectively, the presented vibrational spectroscopy based GWO-SVM model can facilitate in screening of COVID-19 patients and alleviate the medical service burden. Therefore, herein proof-of-concept results showed the chance of vibrational spectroscopy coupled with GWO-SVM model to help COVID-19 diagnosis and have the potential be further used for early screening of other infectious diseases.
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Affiliation(s)
- Bingqiang Zhao
- College of Chemistry & Chemical Engineering, Lanzhou University; South Tianshui Road 222, Lanzhou, Gansu 730000, PR China
| | - Honglin Zhai
- College of Chemistry & Chemical Engineering, Lanzhou University; South Tianshui Road 222, Lanzhou, Gansu 730000, PR China.
| | - Haiping Shao
- College of Chemistry & Chemical Engineering, Lanzhou University; South Tianshui Road 222, Lanzhou, Gansu 730000, PR China
| | - Kexin Bi
- College of Chemistry & Chemical Engineering, Lanzhou University; South Tianshui Road 222, Lanzhou, Gansu 730000, PR China
| | - Ling Zhu
- College of Chemistry & Chemical Engineering, Lanzhou University; South Tianshui Road 222, Lanzhou, Gansu 730000, PR China
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29
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Aitekenov S, Sultangaziyev A, Boranova A, Dyussupova A, Ilyas A, Gaipov A, Bukasov R. SERS for Detection of Proteinuria: A Comparison of Gold, Silver, Al Tape, and Silicon Substrates for Identification of Elevated Protein Concentration in Urine. SENSORS (BASEL, SWITZERLAND) 2023; 23:1605. [PMID: 36772644 PMCID: PMC9921516 DOI: 10.3390/s23031605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
Excessive protein excretion in human urine is an early and sensitive marker of diabetic nephropathy and primary and secondary renal disease. Kidney problems, particularly chronic kidney disease, remain among the few growing causes of mortality in the world. Therefore, it is important to develop an efficient, expressive, and low-cost method for protein determination. Surface enhanced Raman spectroscopy (SERS) methods are potential candidates to achieve these criteria. In this paper, a SERS method was developed to distinguish patients with proteinuria from the healthy group. Commercial gold nanoparticles (AuNPs) with diameters of 60 nm and 100 nm, and silver nanoparticles (AgNPs) with a diameter of 100 nm were tested on the surface of four different substrates including silver and gold films, silicon, and aluminum tape. SERS spectra were acquired from 111 unique human urine samples prepared and measured for each of the seven different nanoparticle plus substrate combinations. Data analysis by the PCA-LDA algorithm and the ROC curves gave results for the diagnostic figures of merits. The best sensitivity, specificity, accuracy, and AUC were 0.91, 0.84, 0.88, and 0.94 for the set with 100 nm Au NPs on the silver substrate, respectively. Among the three metal substrates, the substrate with AuNPs and Al tape performed slightly worse than the other three substrates, and 100 nm gold nanoparticles on average produced better results than 60 nm gold nanoparticles. The 60 nm diameter AuNPs and silicon, which is about one order of magnitude more cost-effective than AuNPs and gold film, showed a relative performance close to the performance of 60 nm AuNPs and Au film (average AUC 0.88 (Si) vs. 0.89 (Au)). This is likely the first reported application of unmodified silicon in SERS substrates applied for direct detection of proteins in any biofluid, particularly in urine. These results position silicon and AuNPs@Si in particular as a perspective SERS substrate for direct urine analysis, including clinical diagnostics of proteinuria.
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Affiliation(s)
- Sultan Aitekenov
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Alisher Sultangaziyev
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Aigerim Boranova
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Aigerim Dyussupova
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Aisha Ilyas
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Abduzhappar Gaipov
- Department of Medicine, School of Medicine, Nazarbayev University, Nur-Sultan 010000, Kazakhstan
| | - Rostislav Bukasov
- Department of Chemistry, School of Sciences and Humanities (SSH) Nazarbayev University, Nur-Sultan 010000, Kazakhstan
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30
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Khan RS, Malik H. Diagnostic Biomarkers for Gestational Diabetes Mellitus Using Spectroscopy Techniques: A Systematic Review. Diseases 2023; 11:diseases11010016. [PMID: 36810530 PMCID: PMC9944100 DOI: 10.3390/diseases11010016] [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: 11/22/2022] [Revised: 12/28/2022] [Accepted: 01/20/2023] [Indexed: 01/27/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is associated with adverse maternal and foetal consequences, along with the subsequent risk of type 2 diabetes mellitus (T2DM) and several other diseases. Due to early risk stratification in the prevention of progression of GDM, improvements in biomarker determination for GDM diagnosis will enhance the optimization of both maternal and foetal health. Spectroscopy techniques are being used in an increasing number of applications in medicine for investigating biochemical pathways and the identification of key biomarkers associated with the pathogenesis of GDM. The significance of spectroscopy promises the molecular information without the need for special stains and dyes; therefore, it speeds up and simplifies the necessary ex vivo and in vivo analysis for interventions in healthcare. All the selected studies showed that spectroscopy techniques were effective in the identification of biomarkers through specific biofluids. Existing GDM prediction and diagnosis through spectroscopy techniques presented invariable findings. Further studies are required in larger, ethnically diverse populations. This systematic review provides the up-to-date state of research on biomarkers in GDM, which were identified via various spectroscopy techniques, and a discussion of the clinical significance of these biomarkers in the prediction, diagnosis, and management of GDM.
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Affiliation(s)
- Rabia Sannam Khan
- Department of Bioengineering, Lancaster University, Lancaster LA1 4YW, UK
- Correspondence:
| | - Haroon Malik
- Queens Medical Centre, Jumeirah, Dubai P.O. Box 2652, United Arab Emirates
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31
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Rutherford SH, Baker MJ, Hunt NT. 2D-IR spectroscopy of proteins in H 2O-A Perspective. J Chem Phys 2023; 158:030901. [PMID: 36681646 DOI: 10.1063/5.0129480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H2O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H2O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H2O and show how this development has the potential to impact areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardization of 2D-IR data collection, and signal quantification. Ultimately, we visualize a direction of travel toward the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis.
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Affiliation(s)
- Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, United Kingdom
| | - Matthew J Baker
- School of Medicine, Faculty of Clinical Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, United Kingdom
| | - Neil T Hunt
- Department of Chemistry and York Biomedical Research Institute, University of York, York YO10 5DD, United Kingdom
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32
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Howard NS, Archer AJ, Sibley DN, Southee DJ, Wijayantha KGU. Surfactant Control of Coffee Ring Formation in Carbon Nanotube Suspensions. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2023; 39:929-941. [PMID: 36607610 PMCID: PMC9878724 DOI: 10.1021/acs.langmuir.2c01691] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/06/2022] [Indexed: 06/17/2023]
Abstract
The coffee ring effect regularly occurs during the evaporation of colloidal droplets and is often undesirable. Here we show that adding a specific concentration of a surfactant can mitigate this effect. We have conducted experiments on aqueous suspensions of carbon nanotubes that were prepared with cationic surfactant dodecyltrimethylammonium bromide added at 0.2, 0.5, 1, 2, 5, and 10 times the critical micelle concentration. Colloidal droplets were deposited on candidate substrates for printed electronics with varying wetting characteristics: glass, polyethylene terephthalate, fluoroethylene propylene copolymer, and polydimethylsiloxane. Following drying, four pattern types were observed in the final deposits: dot-like, uniform, coffee ring deposits, and combined patterns (coffee ring with a dot-like central deposit). Evaporation occurred predominantly in constant contact radius mode for most pattern types, except for some cases that led to uniform deposits in which early stage receding of the contact line occurred. Image analysis and profilometry yielded deposit thicknesses, allowing us to identify a coffee ring subfeature in all uniform deposits and to infer the percentage coverage in all cases. Importantly, a critical surfactant concentration was identified for the generation of highly uniform deposits across all substrates. This concentration resulted in visually uniform deposits consisting of a coffee ring subfeature with a densely packed center, generated from two distinct evaporative phases.
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Affiliation(s)
- N. S. Howard
- Department
of Chemistry, Loughborough University, Loughborough LE11 3TU, U.K.
| | - A. J. Archer
- Department
of Mathematical Sciences, Loughborough University, Loughborough LE11 3TU, U.K.
- Interdisciplinary
Centre for Mathematical Modelling, Loughborough
University, Loughborough LE11 3TU, U.K.
| | - D. N. Sibley
- Department
of Mathematical Sciences, Loughborough University, Loughborough LE11 3TU, U.K.
- Interdisciplinary
Centre for Mathematical Modelling, Loughborough
University, Loughborough LE11 3TU, U.K.
| | - D. J. Southee
- School
of Design and Creative Arts, Loughborough
University, Loughborough LE11 3TU, U.K.
| | - K. G. U. Wijayantha
- Department
of Chemistry, Loughborough University, Loughborough LE11 3TU, U.K.
- Centre
for Renewable and Low Carbon Energy, Cranfield
University, Cranfield, Bedfordshire MK43 0AL, U.K.
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33
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Zhang K, Liu R, Tuo Y, Ma K, Zhang D, Wang Z, Huang P. Distinguishing Asphyxia from Sudden Cardiac Death as the Cause of Death from the Lung Tissues of Rats and Humans Using Fourier Transform Infrared Spectroscopy. ACS OMEGA 2022; 7:46859-46869. [PMID: 36570197 PMCID: PMC9773813 DOI: 10.1021/acsomega.2c05968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
The ability to determine asphyxia as a cause of death is important in forensic practice and helps us to judge whether a case is criminal. However, in some cases where the deceased has underlying heart disease, death by asphyxia cannot be determined by traditional autopsy and morphological observation under a microscope because there are no specific morphological features for either asphyxia or sudden cardiac death (SCD). Here, Fourier transform infrared (FTIR) spectroscopy was employed to distinguish asphyxia from SCD. A total of 40 lung tissues (collected at 0 h and 24 h postmortem) from 20 rats (10 died from asphyxia and 10 died from SCD) and 16 human lung tissues from 16 real cases were used for spectral data acquisition. After data preprocessing, 2675 spectra from rat lung tissues and 1526 spectra from human lung tissues were obtained for subsequent analysis. First, we found that there were biochemical differences in the rat lung tissues between the two causes of death by principal component analysis and partial least-squares discriminant analysis (PLS-DA), which were related to alterations in lipids, proteins, and nucleic acids. In addition, a PLS-DA classification model can be built to distinguish asphyxia from SCD. Second, based on the spectral data obtained from lung tissues allowed to decompose for 24 h, we could still distinguish asphyxia from SCD even when decomposition occurred in animal models. Nine important spectral features that contributed to the discrimination in the animal experiment were selected and further analyzed. Third, 7 of the 9 differential spectral features were also found to be significantly different in human lung tissues from 16 real cases. A support vector machine model was finally built by using the seven variables to distinguish asphyxia from SCD in the human samples. Compared with the linear PLS-DA model, its accuracy was significantly improved to 0.798, and the correct rate of determining the cause of death was 100%. This study shows the application potential of FTIR spectroscopy for exploring the subtle biochemical differences resulting from different death processes and determining the cause of death even after decomposition.
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Affiliation(s)
- Kai Zhang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ruina Liu
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ya Tuo
- Department
of Biochemistry and Physiology, Shanghai
University of Medicine and Health Sciences, Shanghai 201318, People’s Republic of China
| | - Kaijun Ma
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Dongchuan Zhang
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Zhenyuan Wang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ping Huang
- Shanghai
Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, People’s Republic of China
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34
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Callery EL, Morais CLM, Nugent L, Rowbottom AW. Classification of Systemic Lupus Erythematosus Using Raman Spectroscopy of Blood and Automated Computational Detection Methods: A Novel Tool for Future Diagnostic Testing. Diagnostics (Basel) 2022; 12:diagnostics12123158. [PMID: 36553165 PMCID: PMC9777204 DOI: 10.3390/diagnostics12123158] [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: 10/24/2022] [Revised: 12/08/2022] [Accepted: 12/11/2022] [Indexed: 12/16/2022] Open
Abstract
The aim of this study was to explore the proof of concept for using Raman spectroscopy as a diagnostic platform in the setting of systemic lupus erythematosus (SLE). We sought to identify unique Raman signatures in serum blood samples to successfully segregate SLE patients from healthy controls (HC). In addition, a retrospective audit was undertaken to assess the clinical utility of current testing platforms used to detect anti-double stranded DNA (dsDNA) antibodies (n = 600). We examined 234 Raman spectra to investigate key variances between SLE patients (n = 8) and HC (n = 4). Multi-variant analysis and classification model construction was achieved using principal component analysis (PCA), PCA-linear discriminant analysis and partial least squares-discriminant analysis (PLS-DA). We achieved the successful segregation of Raman spectra from SLE patients and healthy controls (p-value < 0.0001). Classification models built using PLS-DA demonstrated outstanding performance characteristics with 99% accuracy, 100% sensitivity and 99% specificity. Twelve statistically significant (p-value < 0.001) wavenumbers were identified as potential diagnostic spectral markers. Molecular assignments related to proteins and DNA demonstrated significant Raman intensity changes between SLE and HC groups. These wavenumbers may serve as future biomarkers and offer further insight into the pathogenesis of SLE. Our audit confirmed previously reported inconsistencies between two key methodologies used to detect anti-dsDNA, highlighting the need for improved laboratory testing for SLE. Raman spectroscopy has demonstrated powerful performance characteristics in this proof-of-concept study, setting the foundations for future translation into the clinical setting.
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Affiliation(s)
- Emma L. Callery
- Department of Immunology, Royal Preston Hospital, Preston PR2 9HT, UK
- Correspondence: (E.L.C.); (A.W.R.)
| | - Camilo L. M. Morais
- Institute of Chemistry, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil
| | - Lucy Nugent
- Department of Immunology, Whiston Hospital, Prescot L35 5DR, UK
| | - Anthony W. Rowbottom
- Department of Immunology, Royal Preston Hospital, Preston PR2 9HT, UK
- School of Medicine, University of Central Lancashire, Preston PR1 2HE, UK
- Correspondence: (E.L.C.); (A.W.R.)
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35
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Surface-enhanced Raman spectroscopy (SERS) for protein determination in human urine. SENSING AND BIO-SENSING RESEARCH 2022. [DOI: 10.1016/j.sbsr.2022.100535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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36
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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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37
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Lin H, Wang Z, Luo Y, Lin Z, Hong G, Deng K, Huang P, Shen Y. Weighted spectrochemical correlation network analysis-guided GA-PLSR: a potential spectral “fluid biopsy” approach for quantitative assessment of cardiac metabolites in diabetic cardiomyopathy. Microchem J 2022. [DOI: 10.1016/j.microc.2022.108249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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38
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Duckworth E, Hole A, Deshmukh A, Chaturvedi P, Chilakapati MK, Mora B, Roy D. Improving Vibrational Spectroscopy Prospects in Frontline Clinical Diagnosis: Fourier Transform Infrared on Buccal Mucosa Cancer. Anal Chem 2022; 94:13642-13646. [PMID: 36161799 PMCID: PMC9558084 DOI: 10.1021/acs.analchem.2c02496] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
We report a novel
method with higher than 90% accuracy
in diagnosing
buccal mucosa cancer. We use Fourier transform infrared spectroscopic
analysis of human serum by suppressing confounding high molecular
weight signals, thus relatively enhancing the biomarkers’ signals.
A narrower range molecular weight window of the serum was also investigated
that yielded even higher accuracy on diagnosis. The most accurate
results were produced in the serum’s 10–30 kDa molecular
weight region to distinguish between the two hardest to discern classes,
i.e., premalignant and cancer patients. This work promises an avenue
for earlier diagnosis with high accuracy as well as greater insight
into the molecular origins of these signals by identifying a key molecular
weight region to focus on.
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Affiliation(s)
- Edward Duckworth
- Swansea University, Singleton Park, Swansea, SA28PP Wales, United Kingdom
| | - Arti Hole
- Advanced Centre for Treatment, Research and Education in Cancer, Kharghar, Navi Mumbai 410210, India
| | - Atul Deshmukh
- Center for Interdisciplinary Research, D. Y. Patil Dental College, Nerul, Navi Mumbai 400706, India
| | - Pankaj Chaturvedi
- Department of Life Sciences, Homi Bhaba National Institute, Mumbai 400094, India
| | - Murali Krishna Chilakapati
- Advanced Centre for Treatment, Research and Education in Cancer, Kharghar, Navi Mumbai 410210, India.,Tata Memorial Center, Head and Neck Surgical Oncology, Dr. E Borges Road, Parel, Mumbai 400012, India.,Department of Life Sciences, Homi Bhaba National Institute, Mumbai 400094, India
| | - Benjamin Mora
- Swansea University, Singleton Park, Swansea, SA28PP Wales, United Kingdom
| | - Debdulal Roy
- Swansea University, Singleton Park, Swansea, SA28PP Wales, United Kingdom
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39
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Rumaling MI, Chee FP, Bade A, Hasbi NH, Daim S, Juhim F, Duinong M, Rasmidi R. Methods of optical spectroscopy in detection of virus in infected samples: A review. Heliyon 2022; 8:e10472. [PMID: 36060463 PMCID: PMC9422564 DOI: 10.1016/j.heliyon.2022.e10472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/05/2022] [Accepted: 08/23/2022] [Indexed: 01/08/2023] Open
Affiliation(s)
- Muhammad Izzuddin Rumaling
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Fuei Pien Chee
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
- Corresponding author.
| | - Abdullah Bade
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Nur Hasshima Hasbi
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Sylvia Daim
- Faculty of Medicine and Health Science, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Floressy Juhim
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Mivolil Duinong
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
| | - Rosfayanti Rasmidi
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
- Faculty of Applied Sciences, Universiti Teknologi MARA Sabah Branch, Kota Kinabalu Campus, 88997 Kota Kinabalu, Sabah, Malaysia
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40
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Wang G, Cai W, Wu H, Yang C, Yu K, Liu R, Wei X, Lin H, Sun Q, Wang Z. Identification of human and non-human bloodstains on rough carriers based on ATR-FTIR and chemometrics. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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41
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Koehler A, Scroferneker ML, Pereira BAS, Mateus Pereira de Souza N, de Souza Cavalcante R, Mendes RP, Corbellini VA. Using infrared spectroscopy of serum and chemometrics for diagnosis of paracoccidioidomycosis. J Pharm Biomed Anal 2022; 221:115021. [DOI: 10.1016/j.jpba.2022.115021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/25/2022] [Accepted: 08/26/2022] [Indexed: 10/31/2022]
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42
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Helburn R, Nolan K. Characterizing biological macromolecules with attenuated total reflectance-Fourier transform infrared spectroscopy provides hands-on spectroscopy experiences for undergraduates. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2022; 50:381-392. [PMID: 35616089 DOI: 10.1002/bmb.21619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 07/17/2021] [Accepted: 03/16/2022] [Indexed: 06/15/2023]
Abstract
Infrared (IR) spectra of biologically derived materials display distinct absorption bands correlating to individual macromolecules: protein, polysaccharide, lipid, and nucleic acids. A series of experiments aimed at teaching qualitative bioorganic spectroscopy using attenuated total reflectance (ATR) Fourier transform infrared (IR) with biological polymers as samples is proposed. Labs targeting 1st and 4th year undergraduate students at St. Francis College are being developed. During 2014 ➔ 2017, an integrated biology/chemistry exercise featuring elementary spectroscopy as an addition to an existing lab on light microscopy was administered to three sections of a 1st year general biology course. Students were taught the concept of a spectral fingerprint and to identify carbohydrate and protein based materials by looking for key vibrational bands. The success of that effort as determined by the results of an assessment quiz became the motivation for developing an advanced 4th year exercise involving four macromolecules. In a trial lab (Spring 2019) students gathered reference spectra from materials homogeneous in a single biopolymer followed by spectra of whole tissues which they were expected to fully characterize. Assessment data suggest that 1st year students benefited most from the experience. A detailed discussion of reference and sample spectra (as obtained by students) and relevant bond vibrations along with suggestions for instructors are presented.
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Affiliation(s)
- Robin Helburn
- Department of Chemistry and Physics, St. Francis College, New York, New York, USA
| | - Kathleen Nolan
- Department of Biology, St. Francis College, New York, New York, USA
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43
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Ghimire H, Viennois E, Hu X, Qin G, Merlin D, Perera AGU. Infrared spectrometric biomarkers for ulcerative colitis screening using human serum samples. JOURNAL OF BIOPHOTONICS 2022; 15:e202100307. [PMID: 35133076 DOI: 10.1002/jbio.202100307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 12/29/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
This study uses infrared spectrometry coupled with data analysis techniques to understand colitis-induced alterations in the molecular components of serum samples. Using samples from 18 ulcerative colitis patients and 28 healthy volunteers, we assessed features such as absorbance values at wavenumbers of 1033 and 1076 cm-1 , and the ratios at 1121 versus 1020 cm-1 and 1629 versus 1737 cm-1 . Through the deconvolution of the amide I band, protein secondary structure analysis was performed. Colitis-induced alterations are reflected as fluctuations in the vibrational modes, and are used to identify associated spectral signatures. The results of the study show statistically significant differences in five identifying spectral signatures. Among them, the sensitivity and specificity of the spectral signature, I1121 /I1020 , were 100% and 86%, respectively. These findings resemble our earlier proof-of-concept investigations in mouse models and provide preliminary evidence that this could be a reliable diagnostic test for human patients.
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Affiliation(s)
- Hemendra Ghimire
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
| | - Emilie Viennois
- Institute for Biomedical Sciences, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA
| | - Xinjie Hu
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA
| | - Gengsheng Qin
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA
| | - Didier Merlin
- Institute for Biomedical Sciences, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Decatur, GA, USA
| | - A G Unil Perera
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
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Comparative Study of Sample Carriers for the Identification of Volatile Compounds in Biological Fluids Using Raman Spectroscopy. Molecules 2022; 27:molecules27103279. [PMID: 35630756 PMCID: PMC9144713 DOI: 10.3390/molecules27103279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/02/2022] [Accepted: 05/18/2022] [Indexed: 11/17/2022] Open
Abstract
Vibrational spectroscopic techniques and especially Raman spectroscopy are gaining ground in substituting the officially established chromatographic methods in the identification of ethanol and other volatile substances in body fluids, such as blood, urine, saliva, semen, and vaginal fluids. Although a couple of different carriers and substrates have been employed for the biochemical analysis of these samples, most of them are suffering from important weaknesses as far as the analysis of volatile compounds is concerned. For this reason, in this study three carriers are proposed, and the respective sample preparation methods are described for the determination of ethanol in human urine samples. More specifically, a droplet of the sample on a highly reflective carrier of gold layer, a commercially available cuvette with a mirror to enhance backscattered radiation sealed with a lid, and a home designed microscope slide with a cavity coated with gold layer and covered with transparent cling film have been evaluated. Among the three proposed carriers, the last one achieved a quick, simple, and inexpensive identification of ethanol, which was used as a case study for the volatile compound, in the biological samples. The limit of detection (LoD) was found to be 1.00 μL/mL, while at the same time evaporation of ethanol was prevented.
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Lin H, Wang Z, Luo Y, Lin Z, Hong G, Deng K, Huang P, Shen Y. Non/mini-invasive monitoring of diabetes-induced myocardial damage by Fourier transform infrared spectroscopy: Evidence from biofluids. Biochim Biophys Acta Mol Basis Dis 2022; 1868:166445. [PMID: 35577177 DOI: 10.1016/j.bbadis.2022.166445] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/04/2022] [Accepted: 05/09/2022] [Indexed: 11/26/2022]
Abstract
Early identification of diabetic cardiomyopathy (DCM) can help clinicians develop targeted treatment plans and forensic pathologists make accurate postmortem diagnoses. In the present study, diabetes-induced metabolic abnormalities in the myocardium and biofluids (plasma, urine, and saliva) of db/db mice of various ages (7, 12, and 21 weeks) were investigated by attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results indicated that the diabetic and control groups had significantly different changes in the function groups of lipids, phosphate macromolecules (mostly nucleic acids), protein compositions and conformations, and carbohydrates (primarily glucose) in the myocardium and biofluids. The prediction model for quantifying DCM severity was developed on db/db mice's myocardial spectra using a genetic algorithm (GA)-partial least squares (PLS) regression method. Following that, the linear correlations between the predicted values for DCM severity and spectra for db/db biofluids were evaluated using the GA-PLS regression algorithm. The results showed there were good linear correlations between the predicted values for DCM severity and spectra for plasma (R2 = 0.929), saliva (R2 = 0.967), urine (R2 = 0.954), and combination of plasma and saliva (R2 = 0.980). This study provides a novel perspective on detecting diabetes-related biofluid and cardiac metabolic abnormalities and demonstrates the potential of biofluid infrared spectro-diagnostic models for non/mini-invasive assessment of DCM.
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Affiliation(s)
- Hancheng Lin
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Zhimin Wang
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Yiwen Luo
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Institute of Forensic Science, Ministry of Justice, PRC, Shanghai 200063, China
| | - Zijie Lin
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Guanghui Hong
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Kaifei Deng
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Institute of Forensic Science, Ministry of Justice, PRC, Shanghai 200063, China
| | - Ping Huang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Institute of Forensic Science, Ministry of Justice, PRC, Shanghai 200063, China.
| | - Yiwen Shen
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China.
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Schiemer R, Furniss D, Phang S, Seddon AB, Atiomo W, Gajjar KB. Vibrational Biospectroscopy: An Alternative Approach to Endometrial Cancer Diagnosis and Screening. Int J Mol Sci 2022; 23:ijms23094859. [PMID: 35563249 PMCID: PMC9102412 DOI: 10.3390/ijms23094859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 01/27/2023] Open
Abstract
Endometrial cancer (EC) is the sixth most common cancer and the fourth leading cause of death among women worldwide. Early detection and treatment are associated with a favourable prognosis and reduction in mortality. Unlike other common cancers, however, screening strategies lack the required sensitivity, specificity and accuracy to be successfully implemented in clinical practice and current diagnostic approaches are invasive, costly and time consuming. Such limitations highlight the unmet need to develop diagnostic and screening alternatives for EC, which should be accurate, rapid, minimally invasive and cost-effective. Vibrational spectroscopic techniques, Mid-Infrared Absorption Spectroscopy and Raman, exploit the atomic vibrational absorption induced by interaction of light and a biological sample, to generate a unique spectral response: a “biochemical fingerprint”. These are non-destructive techniques and, combined with multivariate statistical analysis, have been shown over the last decade to provide discrimination between cancerous and healthy samples, demonstrating a promising role in both cancer screening and diagnosis. The aim of this review is to collate available evidence, in order to provide insight into the present status of the application of vibrational biospectroscopy in endometrial cancer diagnosis and screening, and to assess future prospects.
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Affiliation(s)
- Roberta Schiemer
- Division of Child Health, Obstetrics and Gynaecology, University of Nottingham, Nottingham NG5 1PB, UK;
- Correspondence:
| | - David Furniss
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - Sendy Phang
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - Angela B. Seddon
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - William Atiomo
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai P.O. Box 505055, United Arab Emirates;
| | - Ketankumar B. Gajjar
- Division of Child Health, Obstetrics and Gynaecology, University of Nottingham, Nottingham NG5 1PB, UK;
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Cameron JM, Rinaldi C, Rutherford SH, Sala A, G Theakstone A, Baker MJ. Clinical Spectroscopy: Lost in Translation? APPLIED SPECTROSCOPY 2022; 76:393-415. [PMID: 34041957 DOI: 10.1177/00037028211021846] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.
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Affiliation(s)
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Ashton G Theakstone
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
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Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera. Int J Mol Sci 2022; 23:ijms23052791. [PMID: 35269934 PMCID: PMC8911153 DOI: 10.3390/ijms23052791] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/24/2022] [Accepted: 03/01/2022] [Indexed: 12/13/2022] Open
Abstract
Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are both autoimmune inflammatory and demyelinating diseases of the central nervous system. NMOSD is a highly disabling disease and rapid introduction of the appropriate treatment at the acute phase is crucial to prevent sequelae. Specific criteria were established in 2015 and provide keys to distinguish NMOSD and MS. One of the most reliable criteria for NMOSD diagnosis is detection in patient’s serum of an antibody that attacks the water channel aquaporin-4 (AQP-4). Another target in NMOSD is myelin oligodendrocyte glycoprotein (MOG), delineating a new spectrum of diseases called MOG-associated diseases. Lastly, patients with NMOSD can be negative for both AQP-4 and MOG antibodies. At disease onset, NMOSD symptoms are very similar to MS symptoms from a clinical and radiological perspective. Thus, at first episode, given the urgency of starting the anti-inflammatory treatment, there is an unmet need to differentiate NMOSD subtypes from MS. Here, we used Fourier transform infrared spectroscopy in combination with a machine learning algorithm with the aim of distinguishing the infrared signatures of sera of a first episode of NMOSD from those of a first episode of relapsing-remitting MS, as well as from those of healthy subjects and patients with chronic inflammatory demyelinating polyneuropathy. Our results showed that NMOSD patients were distinguished from MS patients and healthy subjects with a sensitivity of 100% and a specificity of 100%. We also discuss the distinction between the different NMOSD serostatuses. The coupling of infrared spectroscopy of sera to machine learning is a promising cost-effective, rapid and reliable differential diagnosis tool capable of helping to gain valuable time in patients’ treatment.
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Yang S, Zhang Q, Yang H, Shi H, Dong A, Wang L, Yu S. Progress in infrared spectroscopy as an efficient tool for predicting protein secondary structure. Int J Biol Macromol 2022; 206:175-187. [PMID: 35217087 DOI: 10.1016/j.ijbiomac.2022.02.104] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 02/14/2022] [Accepted: 02/17/2022] [Indexed: 12/21/2022]
Abstract
Infrared (IR) spectroscopy is a highly sensitive technique that provides complete information on chemical compositions. The IR spectra of proteins or peptides give rise to nine characteristic IR absorption bands. The amide I bands are the most prominent and sensitive vibrational bands and widely used to predict protein secondary structures. The interference of H2O absorbance is the greatest challenge for IR protein secondary structure prediction. Much effort has been made to reduce/eliminate the interference of H2O, simplify operation steps, and increase prediction accuracy. Progress in sampling and equipment has rendered the Fourier transform infrared (FTIR) technique suitable for determining the protein secondary structure in broader concentration ranges, greatly simplifying the operating steps. This review highlights the recent progress in sample preparation, data analysis, and equipment development of FTIR in A/T mode, with a focus on recent applications of FTIR spectroscopy in the prediction of protein secondary structure. This review also provides a brief introduction of the progress in ATR-FTIR for predicting protein secondary structure and discusses some combined IR methods, such as AFM-based IR spectroscopy, that are used to analyze protein structural dynamics and protein aggregation.
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Affiliation(s)
- Shouning Yang
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | | | - Huayan Yang
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Haimei Shi
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Aichun Dong
- Department of Chemistry and Biochemistry, University of Northern Colorado, Greeley, CO, USA.
| | - Li Wang
- Kweichow Moutai Group, Renhuai, Guizhou 564501, China.
| | - Shaoning Yu
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, China.
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Aitekenov S, Sultangaziyev A, Abdirova P, Yussupova L, Gaipov A, Utegulov Z, Bukasov R. Raman, Infrared and Brillouin Spectroscopies of Biofluids for Medical Diagnostics and for Detection of Biomarkers. Crit Rev Anal Chem 2022; 53:1561-1590. [PMID: 35157535 DOI: 10.1080/10408347.2022.2036941] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
This review surveys Infrared, Raman/SERS and Brillouin spectroscopies for medical diagnostics and detection of biomarkers in biofluids, that include urine, blood, saliva and other biofluids. These optical sensing techniques are non-contact, noninvasive and relatively rapid, accurate, label-free and affordable. However, those techniques still have to overcome some challenges to be widely adopted in routine clinical diagnostics. This review summarizes and provides insights on recent advancements in research within the field of vibrational spectroscopy for medical diagnostics and its use in detection of many health conditions such as kidney injury, cancers, cardiovascular and infectious diseases. The six comprehensive tables in the review and four tables in supplementary information summarize a few dozen experimental papers in terms of such analytical parameters as limit of detection, range, diagnostic sensitivity and specificity, and other figures of merits. Critical comparison between SERS and FTIR methods of analysis reveals that on average the reported sensitivity for biomarkers in biofluids for SERS vs FTIR is about 103 to 105 times higher, since LOD SERS are lower than LOD FTIR by about this factor. High sensitivity gives SERS an edge in detection of many biomarkers present in biofluids at low concentration (nM and sub nM), which can be particularly advantageous for example in early diagnostics of cancer or viral infections.HighlightsRaman, Infrared spectroscopies use low volume of biofluidic samples, little sample preparation, fast time of analysis and relatively inexpensive instrumentation.Applications of SERS may be a bit more complicated than applications of FTIR (e.g., limited shelf life for nanoparticles and substrates, etc.), but this can be generously compensated by much higher (by several order of magnitude) sensitivity in comparison to FTIR.High sensitivity makes SERS a noninvasive analytical method of choice for detection, quantification and diagnostics of many health conditions, metabolites, and drugs, particularly in diagnostics of cancer, including diagnostics of its early stages.FTIR, particularly ATR-FTIR can be a method of choice for efficient sensing of many biomarkers, present in urine, blood and other biofluids at sufficiently high concentrations (mM and even a few µM)Brillouin scattering spectroscopy detecting visco-elastic properties of probed liquid medium, may also find application in clinical analysis of some biofluids, such as cerebrospinal fluid and urine.
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Affiliation(s)
- Sultan Aitekenov
- Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Alisher Sultangaziyev
- Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Perizat Abdirova
- Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Lyailya Yussupova
- Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
| | | | - Zhandos Utegulov
- Department of Physics, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Rostislav Bukasov
- Department of Chemistry, School of Sciences and Humanities (SSH), Nazarbayev University, Nur-Sultan, Kazakhstan
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