1
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Chautard R, Caulet M, Bouché O, Borg C, Manfredi S, Capitain O, Spano JP, Raoul W, Guéguinou M, Herault O, Ferru A, Pobel C, Sire O, Lecomte T. Evaluation of serum mid-infrared spectroscopy as new prognostic marker for first-line bevacizumab-based chemotherapy in metastatic colorectal cancer. Dig Liver Dis 2024:S1590-8658(24)00886-7. [PMID: 39164167 DOI: 10.1016/j.dld.2024.07.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 07/05/2024] [Accepted: 07/20/2024] [Indexed: 08/22/2024]
Abstract
BACKGROUND AND AIMS Bevacizumab-based chemotherapy is a recommended first-line treatment for metastatic colorectal cancer (mCRC). Robust biomarkers with clinical practice applicability have not been identified for patients with this treatment. We aimed to evaluate the prognostic yield of serum mid-infrared spectroscopy (MIRS) on patients receiving first-line bevacizumab-based chemotherapy for mCRC. METHODS We conducted an ancillary analysis from a multicentre prospective study (NCT00489697). All baseline serums were screened by attenuated total reflection method. Principal component analysis and unsupervised k-mean partitioning methods were performed blinded to all patients' data. Endpoints were progression-free survival (PFS) and overall survival (OS). RESULTS From the 108 included patients, MIRS discriminated two prognostic groups. First group patients had significantly lower body mass index (p = 0.026) and albumin levels (p < 0.001), and higher levels of angiogenic markers, lactate dehydrogenase and carcinoembryonic antigen (p < 0.001). In univariate analysis, their OS and PFS were shorter with respective medians: 17.6 vs 27.9 months (p = 0.02) and 8.7 vs 11.3 months (p = 0.03). In multivariate analysis, PFS was significantly shorter (HR = 1.74, p = 0.025) with a similar trend for OS (HR = 1.69, p = 0.061). CONCLUSION By metabolomic fingerprinting, MIRS proves to be a promising prognostic tool for patients receiving first-line bevacizumab-based chemotherapy for mCRC.
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Affiliation(s)
- Romain Chautard
- Department of Hepato-Gastroenterology and Digestive Oncology, Centre Hospitalier Régional Universitaire de Tours, Université François Rabelais, Tours, France; Université de Tours, Inserm, UMR 1069, Nutrition Croissance et Cancer (N2C), Faculté de Médecine, Tours, France.
| | - Morgane Caulet
- Department of Hepato-Gastroenterology and Digestive Oncology, Centre Hospitalier Régional Universitaire de Tours, Université François Rabelais, Tours, France
| | - Olivier Bouché
- Department of Digestive Oncology, Hôpital Robert Debré, CHU de Reims, Avenue Général Koenig, 51092, Reims, France
| | - Christophe Borg
- Department of Medical Oncology, Hôpital Jean Minjoz, CHRU de Besançon, 3 Boulevard Alexandre Fleming, 25000, Besançon, France
| | - Sylvain Manfredi
- Department of Gastroenterology, CHU Dijon, University of Bourgogne-Franche Comté, INSERM U1231, Dijon, France
| | - Olivier Capitain
- Department of Medical Oncology, Institut de Cancérologie de l'Ouest Paul Papin, Angers, France
| | - Jean-Philippe Spano
- Oncology Department, Sorbonne University, Pitié-Salpêtrière Hospital, Paris, France
| | - William Raoul
- Université de Tours, Inserm, UMR 1069, Nutrition Croissance et Cancer (N2C), Faculté de Médecine, Tours, France
| | - Maxime Guéguinou
- Université de Tours, Inserm, UMR 1069, Nutrition Croissance et Cancer (N2C), Faculté de Médecine, Tours, France
| | - Olivier Herault
- CNRS ERL7001 LNOX, EA7501, Tours University, 37000 Tours, France
| | - Aurélie Ferru
- Medical Oncology Department, Poitiers University Hospital, Poitiers, France
| | - Cédric Pobel
- INSERM U981, Gustave Roussy Institute, Villejuif, France
| | | | - Thierry Lecomte
- Department of Hepato-Gastroenterology and Digestive Oncology, Centre Hospitalier Régional Universitaire de Tours, Université François Rabelais, Tours, France; Université de Tours, Inserm, UMR 1069, Nutrition Croissance et Cancer (N2C), Faculté de Médecine, Tours, France
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2
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Roman M, Wrobel TP, Panek A, Kwiatek WM. High-definition FT-IR reveals a synergistic effect on lipid accumulation in prostate cancer cells induced by a combination of X-rays and radiosensitizing drugs. Biochim Biophys Acta Mol Cell Biol Lipids 2024; 1869:159468. [PMID: 38408538 DOI: 10.1016/j.bbalip.2024.159468] [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: 12/26/2023] [Revised: 02/02/2024] [Accepted: 02/22/2024] [Indexed: 02/28/2024]
Abstract
Radiotherapy is one of the most commonly used cancer therapies with many benefits including low toxicity to healthy tissues. However, a major problem in radiotherapy is cancer radioresistance. To enhance the effect of this kind of therapy several approaches have been proposed such as the use of radiosensitizers. A combined treatment of radiotherapy and radiosensitizing drugs leads to a greater effect on cancer cells than anticipated from the addition of both responses (synergism). In this study, high-definition FT-IR imaging was applied to follow lipid accumulation in prostate cancer cells as a response to X-ray irradiation, radiosensitizing drugs, and a combined treatment of X-rays and the drugs. Lipid accumulation induced in the cells by an increasing X-ray dose and the presence of the drugs was analyzed using Principal Component Analysis and lipid staining. Finally, the synergistic effect of the combined therapy (X-rays and radiosensitizers) was confirmed by calculations of the integral intensity of the 2850 cm-1 band.
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Affiliation(s)
- Maciej Roman
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland; SOLARIS National Synchrotron Radiation Centre, Jagiellonian University, Czerwone Maki 98, 30-392 Krakow, Poland.
| | - Tomasz P Wrobel
- SOLARIS National Synchrotron Radiation Centre, Jagiellonian University, Czerwone Maki 98, 30-392 Krakow, Poland
| | - Agnieszka Panek
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
| | - Wojciech M Kwiatek
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
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Reihanisaransari R, Gajjela CC, Wu X, Ishrak R, Corvigno S, Zhong Y, Liui J, Sood AK, Mayerich D, Berisha S, Reddy R. Rapid hyperspectral photothermal mid-infrared spectroscopic imaging from sparse data for gynecologic cancer tissue subtyping. ARXIV 2024:arXiv:2402.17960v1. [PMID: 38463509 PMCID: PMC10925386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Ovarian cancer detection has traditionally relied on a multi-step process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. Our method significantly accelerates data collection by capturing a combination of highresolution and interleaved, lower-resolution infrared band images and applying computational techniques for data interpolation. We effectively minimize data collection requirements by leveraging sparse data acquisition and employing curvelet-based reconstruction algorithms. This approach enhances imaging speed without compromising image quality and ensures robust tissue segmentation. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled datasets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology. It represents a significant leap forward from traditional histopathological methods, offering profound implications for cancer diagnostics and treatment decision-making.
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Affiliation(s)
- Reza Reihanisaransari
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX
| | | | - Xinyu Wu
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX
| | - Ragib Ishrak
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX
| | - Sara Corvigno
- The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yanping Zhong
- The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jinsong Liui
- The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Anil K. Sood
- The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - David Mayerich
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX
| | | | - Rohith Reddy
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX
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4
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Alix JJP, Plesia M, Shaw PJ, Mead RJ, Day JCC. Combining electromyography and Raman spectroscopy: optical EMG. Muscle Nerve 2023; 68:464-470. [PMID: 37477391 PMCID: PMC10952815 DOI: 10.1002/mus.27937] [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: 12/22/2022] [Revised: 06/21/2023] [Accepted: 06/25/2023] [Indexed: 07/22/2023]
Abstract
INTRODUCTION/AIMS Electromyography (EMG) remains a key component of the diagnostic work-up for suspected neuromuscular disease, but it does not provide insight into the molecular composition of muscle which can provide diagnostic information. Raman spectroscopy is an emerging neuromuscular biomarker capable of generating highly specific, molecular fingerprints of tissue. Here, we present "optical EMG," a combination of EMG and Raman spectroscopy, achieved using a single needle. METHODS An optical EMG needle was created to collect electrophysiological and Raman spectroscopic data during a single insertion. We tested functionality with in vivo recordings in the SOD1G93A mouse model of amyotrophic lateral sclerosis (ALS), using both transgenic (n = 10) and non-transgenic (NTg, n = 7) mice. Under anesthesia, compound muscle action potentials (CMAPs), spontaneous EMG activity and Raman spectra were recorded from both gastrocnemius muscles with the optical EMG needle. Standard concentric EMG needle recordings were also undertaken. Electrophysiological data were analyzed with standard univariate statistics, Raman data with both univariate and multivariate analyses. RESULTS A significant difference in CMAP amplitude was observed between SOD1G93A and NTg mice with optical EMG and standard concentric needles (p = .015 and p = .011, respectively). Spontaneous EMG activity (positive sharp waves) was detected in transgenic SOD1G93A mice only. Raman spectra demonstrated peaks associated with key muscle components. Significant differences in molecular composition between SOD1G93A and NTg muscle were identified through the Raman spectra. DISCUSSION Optical EMG can provide standard electrophysiological data and molecular Raman data during a single needle insertion and represents a potential biomarker for neuromuscular disease.
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Affiliation(s)
- James J. P. Alix
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Cross‐Faculty Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Maria Plesia
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
| | - Pamela J. Shaw
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Cross‐Faculty Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Richard J. Mead
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Cross‐Faculty Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - John C. C. Day
- Interface Analysis Centre, School of PhysicsUniversity of BristolBristolUK
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Maitra I, Morais CLM, Lima KMG, Ashton KM, Bury D, Date RS, Martin FL. Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma. J Pers Med 2023; 13:1277. [PMID: 37623527 PMCID: PMC10455976 DOI: 10.3390/jpm13081277] [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: 05/30/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023] Open
Abstract
This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Camilo L. M. Morais
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
- Center for Education, Science and Technology of the Inhamuns Region, State University of Ceará, Tauá 63660-000, Brazil
| | - Kássio M. G. Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
| | - Katherine M. Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Danielle Bury
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
| | - Ravindra S. Date
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Francis L. Martin
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
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6
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Brunel B, Prada P, Slimano F, Boulagnon-Rombi C, Bouché O, Piot O. Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology. Analyst 2023; 148:3909-3917. [PMID: 37466305 DOI: 10.1039/d3an00627a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Colorectal cancer is a global public health problem with one of the highest death rates. It is the second most deadly type of cancer and the third most frequently diagnosed in the world. The present study focused on metastatic colorectal cancer (mCRC) patients who had been treated with chemotherapy-based regimen for which it remains uncertainty about the efficacy for all eligible patients. This is a major problem, as it is not yet possible to test different therapies in view of the consequences on the health of the patients and the risk of progression. Here, we propose a method to predict the efficacy of an anticancer treatment in an individualized way, using a deep learning model constructed on the retrospective analysis of the primary tumor of several patients. Histological sections from tumors were imaged by standard hematoxylin and eosin (HE) staining and infrared spectroscopy (IR). Images obtained were then processed by a convolutional neural network (CNN) to extract features and correlate them with the subsequent progression-free survival (PFS) of each patient. Separately, HE and IR imaging resulted in a PFS prediction with an error of 6.6 and 6.3 months respectively (28% and 26% of the average PFS). Combining both modalities allowed to decrease the error to 5.0 months (21%). The inflammatory state of the stroma seemed to be one of the main features detected by the CNN. Our pilot study suggests that multimodal imaging analyzed with deep learning methods allow to give an indication of the effectiveness of a treatment when choosing.
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Affiliation(s)
- Benjamin Brunel
- Université de Reims Champagne-Ardenne, EA7506-BioSpectroscopie Translationnelle (BioSpecT), Reims, France
- Université de Franche-Comté, CNRS, institut FEMTO-ST, F-25000 Besançon, France
| | - Pierre Prada
- Université de Reims Champagne-Ardenne, EA7506-BioSpectroscopie Translationnelle (BioSpecT), Reims, France
| | - Florian Slimano
- Université de Reims Champagne-Ardenne, EA7506-BioSpectroscopie Translationnelle (BioSpecT), Reims, France
| | | | - Olivier Bouché
- Université de Reims Champagne-Ardenne, EA7506-BioSpectroscopie Translationnelle (BioSpecT), Reims, France
- Service d'Oncologie Digestive, CHU Reims, 51100 Reims, France
| | - Olivier Piot
- Université de Reims Champagne-Ardenne, EA7506-BioSpectroscopie Translationnelle (BioSpecT), Reims, France
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Bhargava R. Digital Histopathology by Infrared Spectroscopic Imaging. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2023; 16:205-230. [PMID: 37068745 PMCID: PMC10408309 DOI: 10.1146/annurev-anchem-101422-090956] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. First, this review summarizes IR imaging instrumentation especially suited to histopathology, analyses of its performance, and major trends. Second, an overview of data processing methods and application of machine learning is given, with an emphasis on the emerging use of deep learning. Third, a discussion on workflows in pathology is provided, with four categories proposed based on the complexity of methods and the analytical performance needed. Last, a set of guidelines, termed experimental and analytical specifications for spectroscopic imaging in histopathology, are proposed to help standardize the diversity of approaches in this emerging area.
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Affiliation(s)
- Rohit Bhargava
- Department of Bioengineering; Department of Electrical and Computer Engineering; Department of Mechanical Science and Engineering; Department of Chemical and Biomolecular Engineering; Department of Chemistry; Cancer Center at Illinois; and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA;
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8
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Caldrer S, Deotto N, Pertile G, Bellisola G, Guidi MC. Infrared analysis in the aqueous humor of patients with uveitis: Preliminary results. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2023; 243:112715. [PMID: 37126864 DOI: 10.1016/j.jphotobiol.2023.112715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 03/23/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
Inflammatory processes affecting the uvea result in a temporary o permanent blurred vision and represent an important cause of visual impairment worldwide. It is often hard to make a precise diagnosis which is dependent on the clinical expertise, diagnostic tests, laboratory investigations in blood and sometimes in the aqueous humor (AH). With the aim of obtaining proof of principle Fourier Transformed Infrared (FT-IR) absorbance spectroscopy was applied to study the molecular composition of 72 AH samples collected in 26 patients with uveitis and in 44 controls. The unsupervised exploration of the internal structure of the dataset by principal component analysis reduced hundreds IR variables to those most representative allowing to obtain the predictive model that distinguished the AH spectra of patients with uveitis from controls. The same result was obtained by unsupervised agglomerative cluster analysis. After labeling the spectra with some clinical information it was observed that most severe uveitis with active processes were grouped separately from chronic and relapsing uveitis and controls. The consistence of prediction models is discussed in the light of supporting etiological diagnosis by machine learning processes. In conclusion, proof of principle has been obtained that the IR spectral pattern of AH may reflect particular uveal diseases.
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Affiliation(s)
- Sara Caldrer
- Department of Infectious - Tropical Diseases and Microbiology, IRCCS Sacro Cuore - Don Calabria Hospital, Via Don A. Sempreboni, 5, Negrar di Valpolicella (Verona) 37024, Italy.
| | - Niccolò Deotto
- Department of Ophthalmology, IRCCS Sacro Cuore Don Calabria Hospital, Via Don A. Sempreboni, 5, Negrar di Valpolicella (Verona) 37024, Italy.
| | - Grazia Pertile
- Department of Ophthalmology, IRCCS Sacro Cuore Don Calabria Hospital, Via Don A. Sempreboni, 5, Negrar di Valpolicella (Verona) 37024, Italy.
| | - Giuseppe Bellisola
- INFN - Laboratori Nazionali di Frascati, Via E. Fermi, 54, Frascati (Rome) 00044, Italy.
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Caixeta DC, Carneiro MG, Rodrigues R, Alves DCT, Goulart LR, Cunha TM, Espindola FS, Vitorino R, Sabino-Silva R. Salivary ATR-FTIR Spectroscopy Coupled with Support Vector Machine Classification for Screening of Type 2 Diabetes Mellitus. Diagnostics (Basel) 2023; 13:diagnostics13081396. [PMID: 37189497 DOI: 10.3390/diagnostics13081396] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 02/04/2023] [Accepted: 02/08/2023] [Indexed: 05/17/2023] Open
Abstract
The blood diagnosis of diabetes mellitus (DM) is highly accurate; however, it is an invasive, high-cost, and painful procedure. In this context, the combination of ATR-FTIR spectroscopy and machine learning techniques in other biological samples has been used as an alternative tool to develop a non-invasive, fast, inexpensive, and label-free diagnostic or screening platform for several diseases, including DM. In this study, we used the ATR-FTIR tool associated with linear discriminant analysis (LDA) and a support vector machine (SVM) classifier in order to identify changes in salivary components to be used as alternative biomarkers for the diagnosis of type 2 DM. The band area values of 2962 cm-1, 1641 cm-1, and 1073 cm-1 were higher in type 2 diabetic patients than in non-diabetic subjects. The best classification of salivary infrared spectra was by SVM, showing a sensitivity of 93.3% (42/45), specificity of 74% (17/23), and accuracy of 87% between non-diabetic subjects and uncontrolled type 2 DM patients. The SHAP features of infrared spectra indicate the main salivary vibrational modes of lipids and proteins that are responsible for discriminating DM patients. In summary, these data highlight the potential of ATR-FTIR platforms coupled with machine learning as a reagent-free, non-invasive, and highly sensitive tool for screening and monitoring diabetic patients.
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Affiliation(s)
- Douglas Carvalho Caixeta
- Innovation Center in Salivary Diagnostic and Nanotheranostics, Department of Physiology, Institute of Biomedical Sciences, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
| | | | - Ricardo Rodrigues
- Innovation Center in Salivary Diagnostic and Nanotheranostics, Department of Physiology, Institute of Biomedical Sciences, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
| | - Deborah Cristina Teixeira Alves
- Innovation Center in Salivary Diagnostic and Nanotheranostics, Department of Physiology, Institute of Biomedical Sciences, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
| | - Luís Ricardo Goulart
- Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
| | - Thúlio Marquez Cunha
- School of Medicine, Federal University of Uberlandia (UFU), Uberlandia 38408-100, Minas Gerais, Brazil
| | - Foued Salmen Espindola
- Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
| | - Rui Vitorino
- Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Robinson Sabino-Silva
- Innovation Center in Salivary Diagnostic and Nanotheranostics, Department of Physiology, Institute of Biomedical Sciences, Federal University of Uberlandia, Uberlandia 38408-100, Minas Gerais, Brazil
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de Almeida MP, Rodrigues C, Novais Â, Grosso F, Leopold N, Peixe L, Franco R, Pereira E. Silver Nanostar-Based SERS for the Discrimination of Clinically Relevant Acinetobacter baumannii and Klebsiella pneumoniae Species and Clones. BIOSENSORS 2023; 13:149. [PMID: 36831915 PMCID: PMC9953856 DOI: 10.3390/bios13020149] [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: 12/20/2022] [Revised: 01/12/2023] [Accepted: 01/14/2023] [Indexed: 06/18/2023]
Abstract
The development of rapid, reliable, and low-cost methods that enable discrimination among clinically relevant bacteria is crucial, with emphasis on those listed as WHO Global Priority 1 Critical Pathogens, such as carbapenem-resistant Acinetobacter baumannii and carbapenem-resistant or ESBL-producing Klebsiella pneumoniae. To address this problem, we developed and validated a protocol of surface-enhanced Raman spectroscopy (SERS) with silver nanostars for the discrimination of A. baumannii and K. pneumoniae species, and their globally disseminated and clinically relevant antibiotic resistant clones. Isolates were characterized by mixing bacterial colonies with silver nanostars, followed by deposition on filter paper for SERS spectrum acquisition. Spectral data were processed with unsupervised and supervised multivariate data analysis methods, including principal component analysis (PCA) and partial least-squares discriminant analysis (PLSDA), respectively. Our proposed SERS procedure using silver nanostars adsorbed to the bacteria, followed by multivariate data analysis, enabled differentiation between and within species. This pilot study demonstrates the potential of SERS for the rapid discrimination of clinically relevant A. baumannii and K. pneumoniae species and clones, displaying several advantages such as the ease of silver nanostars synthesis and the possible use of a handheld spectrometer, which makes this approach ideal for point-of-care applications.
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Affiliation(s)
- Miguel Peixoto de Almeida
- LAQV/REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal
| | - Carla Rodrigues
- UCIBIO—Applied Molecular Biosciences Unit, Department of Biological Sciences, Laboratory of Microbiology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Associate Laboratory, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Ângela Novais
- UCIBIO—Applied Molecular Biosciences Unit, Department of Biological Sciences, Laboratory of Microbiology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Associate Laboratory, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- 4TOXRUN, Toxicology Research Unit, University Institute of Health Sciences, CESPU (IUCS-CESPU), 4585-116 Gandra, Portugal
| | - Filipa Grosso
- UCIBIO—Applied Molecular Biosciences Unit, Department of Biological Sciences, Laboratory of Microbiology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Associate Laboratory, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Nicolae Leopold
- Faculty of Physics, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Luísa Peixe
- UCIBIO—Applied Molecular Biosciences Unit, Department of Biological Sciences, Laboratory of Microbiology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Associate Laboratory, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Ricardo Franco
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, School of Science and Technology, Universidade NOVA de Lisboa, 2819-516 Caparica, Portugal
- UCIBIO—Applied Molecular Biosciences Unit, Departamento de Química, School of Science and Technology, Universidade NOVA de Lisboa, 2819-516 Caparica, Portugal
| | - Eulália Pereira
- LAQV/REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal
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11
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Urinalysis of individuals with renal hyperfiltration using ATR-FTIR spectroscopy. Sci Rep 2022; 12:20887. [PMID: 36463336 PMCID: PMC9719484 DOI: 10.1038/s41598-022-25535-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022] Open
Abstract
Abnormal increased glomerular filtration rate (GFR), otherwise known as renal hyperfiltration (RHf), is associated with an increased risk of chronic kidney disease and cardiovascular mortality. Although it is not considered as a disease alone in medicine today, early detection of RHf is essential to reducing risk in a timely manner. However, detecting RHf is a challenge since it does not have a practical biochemical marker that can be followed or quantified. In this study, we tested the ability of ATR-FTIR spectroscopy to distinguish 17 individuals with RHf (hyperfiltraters; RHf (+)), from 20 who have normal GFR (normofiltraters; RHf(-)), using urine samples. Spectra collected from hyperfiltraters were significantly different from the control group at positions 1621, 1390, 1346, 933 and 783/cm. Intensity changes at these positions could be followed directly from the absorbance spectra without the need for pre-processing. They were tentatively attributed to urea, citrate, creatinine, phosphate groups, and uric acid, respectively. Using principal component analysis (PCA), major peaks of the second derivative forms for the classification of two groups were determined. Peaks at 1540, 1492, 1390, 1200, 1000 and 840/cm were significantly different between the two groups. Statistical analysis showed that the spectra of normofiltraters are similar; however, those of hyperfiltraters show diversity at multiple positions that can be observed both from the absorbance spectra and the second derivative profiles. This observation implies that RHf can simultaneously affect the excretion of many substances, and that a spectroscopic analysis of urine can be used as a rapid and non-invasive pre-screening tool.
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12
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Azam KSF, Ryabchykov O, Bocklitz T. A Review on Data Fusion of Multidimensional Medical and Biomedical Data. Molecules 2022; 27:7448. [PMID: 36364272 PMCID: PMC9655963 DOI: 10.3390/molecules27217448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/19/2022] [Accepted: 10/21/2022] [Indexed: 08/05/2024] Open
Abstract
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
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Affiliation(s)
- Kazi Sultana Farhana Azam
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
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13
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Vibrational spectroscopy for decoding cancer microbiota interactions: Current evidence and future perspective. Semin Cancer Biol 2022; 86:743-752. [PMID: 34273519 DOI: 10.1016/j.semcancer.2021.07.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/08/2021] [Accepted: 07/09/2021] [Indexed: 01/27/2023]
Abstract
The role of human microbiota in cancer initiation and progression is recognized in recent years. In order to investigate the interactions between cancer cells and microbes, a systematic analysis using various emerging techniques is required. Owing to the label-free, non-invasive and molecular fingerprinting characteristics, vibrational spectroscopy is uniquely suited to decode and understand the relationship and interactions between cancer and the microbiota at the molecular level. In this review, we first provide a quick overview of the fundamentals of vibrational spectroscopic techniques, namely Raman and infrared spectroscopy. Next, we discuss the emerging evidence underscoring utilities of these spectroscopic techniques to study cancer or microbes separately, and share our perspective on how vibrational spectroscopy can be employed at the intersection of the two fields. Finally, we envision the potential opportunities in exploiting vibrational spectroscopy not only in basic cancer-microbiome research but also in its clinical translation, and discuss the challenges in the bench to bedside translation.
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14
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Vernuccio F, Bresci A, Talone B, de la Cadena A, Ceconello C, Mantero S, Sobacchi C, Vanna R, Cerullo G, Polli D. Fingerprint multiplex CARS at high speed based on supercontinuum generation in bulk media and deep learning spectral denoising. OPTICS EXPRESS 2022; 30:30135-30148. [PMID: 36242123 DOI: 10.1364/oe.463032] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/14/2022] [Indexed: 06/16/2023]
Abstract
We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400-1800 cm-1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (<1 ms/pixel) and unprecedented sensitivity of ≈14.1 mmol/L when detecting dimethyl sulfoxide in water. To further improve the performance of the system and to enhance the signal-to-noise ratio of the CARS spectra, we designed a convolutional neural network for spectral denoising, coupled with a post-processing pipeline to distinguish different chemical species of biological tissues.
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15
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Veettil TCP, Wood BR. A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22124528. [PMID: 35746311 PMCID: PMC9228712 DOI: 10.3390/s22124528] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/03/2022] [Accepted: 06/10/2022] [Indexed: 05/16/2023]
Abstract
Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25-2.5 μm) and near-infrared (2500-800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R2 value of 0.999 over a concentration range of 0-50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix.
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Affiliation(s)
- Thulya Chakkumpulakkal Puthan Veettil
- Centre for Biospectroscopy, Monash University, Clayton, VIC 3800, Australia;
- Centre for Sustainable and Circular Technologies (CSCT), University of Bath, Bath BA2 7AY, UK
| | - Bayden R. Wood
- Centre for Biospectroscopy, Monash University, Clayton, VIC 3800, Australia;
- Correspondence:
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16
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Combining multilayered wrinkled polymer SERS substrates and spectral data processing for low concentration analyte detection. Anal Bioanal Chem 2022; 414:5719-5732. [PMID: 35648171 DOI: 10.1007/s00216-022-04151-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/09/2022] [Accepted: 05/25/2022] [Indexed: 11/01/2022]
Abstract
A series of thermally shrinkable polymer surface-enhanced Raman scattering (SERS) substrates were prepared with bimetallic Au and Ag (oxidized or not) films and with Au nanoparticles (AuNPs) located at different places in the layered structure to evaluate the synergistic effect of different known SERS amplification methods to enhance the Raman signal for low concentration dopamine detection. A bimetallic Au and Ag layered structure improved the Raman signal by 5 and 2 times compared to the single-layered Au and Ag films. Oxidizing the Ag layer prior to deposition of Au further improved the signal by a factor of 2, while adding AuNP on wrinkled films increased another 10 times the intensity of the Raman signal. It was found that the enhancement was another 10 times stronger when using AuNPs in combination with other means of enhancement such as with a silver underlayer or surface wrinkling. Wrinkling alone only gave a few-fold increase compared to a flat film, but the combination of wrinkling with AuNPs and a silver underlayer improved the SERS intensity by more than 3 orders of magnitude, showing the synergistic effect of these enhancement methods. The optimized sensors were then tested in dynamic SERS with low concentration dopamine solutions, where the signal showed characteristics of a digital SERS response. Raman spectra preprocessing and sorting software was developed to triage the SERS-active spectra from the null spectra, to count the detection events such as the ones observed in single molecule experiments.
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17
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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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18
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Wieduwilt F, Grünewald J, Ctistis G, Lenth C, Perl T, Wackerbarth H. Exploration of an Alarm Sensor to Detect Infusion Failure Administered by Syringe Pumps. Diagnostics (Basel) 2022; 12:diagnostics12040936. [PMID: 35453984 PMCID: PMC9032832 DOI: 10.3390/diagnostics12040936] [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: 03/09/2022] [Revised: 04/05/2022] [Accepted: 04/06/2022] [Indexed: 02/05/2023] Open
Abstract
Incorrect medication administration causes millions of undesirable complications worldwide every year. The problem is severe and there are many control systems in the market, yet the exact molecular composition of the solution is not monitored. Here, we propose an alarm sensor based on UV-Vis spectroscopy and refractometry. Both methods are non-invasive and non-destructive as they utilize visible light for the analysis. Moreover, they can be used for on-site or point-of-care diagnosis. UV-Vis-spectrometer detect the absorption of light caused by an electronic transition in an atom or molecule. In contrast a refractometer measures the extent of light refraction as part of a refractive index of transparent substances. Both methods can be used for quantification of dissolved analytes in transparent substances. We show that a sensor combining both methods is capable to discern most standard medications that are used in intensive care medicine. Furthermore, an integration of the alarm sensor in already existing monitoring systems is possible.
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Affiliation(s)
- Florian Wieduwilt
- Institut für Nanophotonik Göttingen e.V., Hans-Adolf-Krebs-Weg 1, 37077 Göttingen, Germany; (J.G.); (C.L.); (H.W.)
- Physical Chemistry of Nanomaterials, Institute of Chemistry and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Straße 40, 34132 Kassel, Germany
- Correspondence: (F.W.); (G.C.)
| | - Jasmin Grünewald
- Institut für Nanophotonik Göttingen e.V., Hans-Adolf-Krebs-Weg 1, 37077 Göttingen, Germany; (J.G.); (C.L.); (H.W.)
| | - Georgios Ctistis
- Institut für Nanophotonik Göttingen e.V., Hans-Adolf-Krebs-Weg 1, 37077 Göttingen, Germany; (J.G.); (C.L.); (H.W.)
- Correspondence: (F.W.); (G.C.)
| | - Christoph Lenth
- Institut für Nanophotonik Göttingen e.V., Hans-Adolf-Krebs-Weg 1, 37077 Göttingen, Germany; (J.G.); (C.L.); (H.W.)
| | - Thorsten Perl
- Department of General, Visceral and Pediatric Surgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany;
| | - Hainer Wackerbarth
- Institut für Nanophotonik Göttingen e.V., Hans-Adolf-Krebs-Weg 1, 37077 Göttingen, Germany; (J.G.); (C.L.); (H.W.)
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19
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Mittal S, Kim J, Bhargava R. Statistical Considerations and Tools to Improve Histopathologic Protocols with Spectroscopic Imaging. APPLIED SPECTROSCOPY 2022; 76:428-438. [PMID: 35296146 PMCID: PMC9202564 DOI: 10.1177/00037028211066327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Advances in infrared (IR) spectroscopic imaging instrumentation and data science now present unique opportunities for large validation studies of the concept of histopathology using spectral data. In this study, we examine the discrimination potential of IR metrics for different histologic classes to estimate the sample size needed for designing validation studies to achieve a given statistical power and statistical significance. Next, we present an automated annotation transfer tool that can allow large-scale training/validation, overcoming the limitations of sparse ground truth data with current manual approaches by providing a tool to transfer pathologist annotations from stained images to IR images across diagnostic categories. Finally, the results of a combination of supervised and unsupervised analysis provide a scheme to identify diagnostic groups/patterns and isolating pure chemical pixels for each class to better train complex histopathological models. Together, these methods provide essential tools to take advantage of the emerging capabilities to record and utilize large spectroscopic imaging datasets.
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Affiliation(s)
- Shachi Mittal
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA
- Department of Chemical Engineering, University of Washington, Seattle, WA, USA
| | - Jonathan Kim
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Rohit Bhargava
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA
- Departments of Mechanical Science and Engineering, Electrical and Computer Engineering, Chemical and Biomolecular Engineering, and Chemistry, University of Illinois at Urbana–Champaign, Urbana, IL, USA
- Cancer Center at Illinois, University of Illinois at Urbana–Champaign, Urbana, IL, USA
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20
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Mankar R, Gajjela CC, Bueso-Ramos CE, Yin CC, Mayerich D, Reddy RK. Polarization Sensitive Photothermal Mid-Infrared Spectroscopic Imaging of Human Bone Marrow Tissue. APPLIED SPECTROSCOPY 2022; 76:508-518. [PMID: 35236126 PMCID: PMC10074826 DOI: 10.1177/00037028211063513] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Collagen quantity and integrity play an important role in understanding diseases such as myelofibrosis (MF). Label-free mid-infrared spectroscopic imaging (MIRSI) has the potential to quantify collagen while minimizing the subjective variance observed with conventional histopathology. Infrared (IR) spectroscopy with polarization sensitivity provides chemical information while also estimating tissue dichroism. This can potentially aid MF grading by revealing the structure and orientation of collagen fibers. Simultaneous measurement of collagen structure and biochemical properties can translate clinically into improved diagnosis and enhance our understanding of disease progression. In this paper, we present the first report of polarization-dependent spectroscopic variations in collagen from human bone marrow samples. We build on prior work with animal models and extend it to human clinical biopsies with a practical method for high-resolution chemical and structural imaging of bone marrow on clinical glass slides. This is done using a new polarization-sensitive photothermal mid-infrared spectroscopic imaging scheme that enables sample and source independent polarization control. This technology provides 0.5 µm spatial resolution, enabling the identification of thin (≈1 µm) collagen fibers that were not separable using Fourier Transform Infrared (FT-IR) imaging in the fingerprint region at diffraction-limited resolution ( ≈ 5 µm). Finally, we propose quantitative metrics to identify fiber orientation from discrete band images (amide I and amide II) measured under three polarizations. Previous studies have used a pair of orthogonal polarization measurements, which is insufficient for clinical samples since human bone biopsies contain collagen fibers with multiple orientations. Here, we address this challenge and demonstrate that three polarization measurements are necessary to resolve orientation ambiguity in clinical bone marrow samples. This is also the first study to demonstrate the ability to spectroscopically identify thin collagen fibers (≈1 µm diameter) and their orientations, which is critical for accurate grading of human bone marrow fibrosis.
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Affiliation(s)
- Rupali Mankar
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
| | - Chalapathi C. Gajjela
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
| | - Carlos E. Bueso-Ramos
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - C. Cameron Yin
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - David Mayerich
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
| | - Rohith K. Reddy
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
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21
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Joshi N, Shukla S, Narayan RJ. Novel photonic methods for diagnosis of SARS-CoV-2 infection. TRANSLATIONAL BIOPHOTONICS 2022; 4:e202200001. [PMID: 35602265 PMCID: PMC9111306 DOI: 10.1002/tbio.202200001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/27/2022] [Accepted: 03/02/2022] [Indexed: 11/08/2022] Open
Abstract
The COVID-19 pandemic that began in March 2020 continues in many countries. The ongoing pandemic makes early diagnosis a crucial part of efforts to prevent the spread of SARS-CoV-2 infections. As such, the development of a rapid, reliable, and low-cost technique with increased sensitivity for detection of SARS-CoV-2 is an important priority of the scientific community. At present, nucleic acid-based techniques are primarily used as the reference approach for the detection of SARS-CoV-2 infection. However, in several cases, false positive results have been observed with these techniques. Due to the drawbacks associated with existing techniques, the development of new techniques for the diagnosis of COVID-19 is an important research activity. We provide an overview of novel diagnostic methods for SARS-CoV-2 diagnosis that integrate photonic technology with artificial intelligence. Recent developments in emerging diagnostic techniques based on the principles of advanced molecular spectroscopy and microscopy are considered.
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Affiliation(s)
- Naveen Joshi
- Department of Materials Science and EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Shubhangi Shukla
- Joint Department of Biomedical EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Roger J. Narayan
- Joint Department of Biomedical EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
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22
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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: 7] [Impact Index Per Article: 3.5] [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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23
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Iakab SA, Baquer G, Lafuente M, Pina MP, Ramírez JL, Ràfols P, Correig-Blanchar X, García-Altares M. SALDI-MS and SERS Multimodal Imaging: One Nanostructured Substrate to Rule Them Both. Anal Chem 2022; 94:2785-2793. [PMID: 35102738 PMCID: PMC8851428 DOI: 10.1021/acs.analchem.1c04118] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
Imaging techniques
based on mass spectrometry or spectroscopy methods
inform in situ about the chemical composition of
biological tissues or organisms, but they are sometimes limited by
their specificity, sensitivity, or spatial resolution. Multimodal
imaging addresses these limitations by combining several imaging modalities;
however, measuring the same sample with the same preparation using
multiple imaging techniques is still uncommon due to the incompatibility
between substrates, sample preparation protocols, and data formats.
We present a multimodal imaging approach that employs a gold-coated
nanostructured silicon substrate to couple surface-assisted laser
desorption/ionization mass spectrometry (SALDI-MS) and surface-enhanced
Raman spectroscopy (SERS). Our approach integrates both imaging modalities
by using the same substrate, sample preparation, and data analysis
software on the same sample, allowing the coregistration of both images.
We transferred molecules from clean fingertips and fingertips covered
with plasticine modeling clay onto our nanostructure and analyzed
their chemical composition and distribution by SALDI-MS and SERS.
Multimodal analysis located the traces of plasticine on fingermarks
and provided chemical information on the composition of the clay.
Our multimodal approach effectively combines the advantages of mass
spectrometry and vibrational spectroscopy with the signal enhancing
abilities of our nanostructured substrate.
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Affiliation(s)
- Stefania-Alexandra Iakab
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Gerard Baquer
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Marta Lafuente
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain
| | - Maria Pilar Pina
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN, Madrid 28029, Spain
| | - José Luis Ramírez
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Xavier Correig-Blanchar
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus 43204, Spain
| | - María García-Altares
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
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24
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Nakar A, Pistiki A, Ryabchykov O, Bocklitz T, Rösch P, Popp J. Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy. Anal Bioanal Chem 2022; 414:1481-1492. [PMID: 34982178 PMCID: PMC8761712 DOI: 10.1007/s00216-021-03800-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/05/2021] [Accepted: 11/22/2021] [Indexed: 01/08/2023]
Abstract
In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli. Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health.
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Affiliation(s)
- Amir Nakar
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Aikaterini Pistiki
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany.
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany.
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
- Jena Biophotonics and Imaging Laboratory, Albert-Einstein-Straße 9, 07745, Jena, Germany
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25
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From lab to field: Surface-enhanced Raman scattering-based sensing strategies for on-site analysis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2021.116488] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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26
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Vibrational Imaging Techniques for the Characterization of Hard Dental Tissues: From Bench-Top to Chair-Side. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app112411953] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Currently, various analytical techniques, including scanning electron microscopy, X-Ray diffraction, microcomputed tomography, and energy dispersive X-ray spectroscopy, are available to study the structural or elemental features of hard dental tissues. In contrast to these approaches, Raman Microspectroscopy (RMS) has the great advantage of simultaneously providing, at the same time and on the same sample, a morpho-chemical correlation between the microscopic information from the visual analysis of the sample and its chemical and macromolecular composition. Hence, RMS represents an innovative and non-invasive technique to study both inorganic and organic teeth components in vitro. The aim of this narrative review is to shed new light on the applicative potential of Raman Microspectroscopy in the dental field. Specific Raman markers representative of sound and pathological hard dental tissues will be discussed, and the future diagnostic application of this technique will be outlined. The objective and detailed information provided by this technique in terms of the structure and chemical/macromolecular components of sound and pathological hard dental tissues could be useful for improving knowledge of several dental pathologies. Scientific articles regarding RMS studies of human hard dental tissues were retrieved from the principal databases by following specific inclusion and exclusion criteria.
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27
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Giamougiannis P, Silva RVO, Freitas DLD, Lima KMG, Anagnostopoulos A, Angelopoulos G, Naik R, Wood NJ, Martin-Hirsch PL, Martin FL. Raman spectroscopy of blood and urine liquid biopsies for ovarian cancer diagnosis: identification of chemotherapy effects. JOURNAL OF BIOPHOTONICS 2021; 14:e202100195. [PMID: 34296515 DOI: 10.1002/jbio.202100195] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
Blood plasma and serum Raman spectroscopy for ovarian cancer diagnosis has been applied in pilot studies, with promising results. Herein, a comparative analysis of these biofluids, with a novel assessment of urine, was conducted by Raman spectroscopy application in a large patient cohort. Spectra were obtained through samples measurements from 116 ovarian cancer patients and 307 controls. Principal component analysis identified significant spectral differences between cancers without previous treatment (n = 71) and following neo-adjuvant chemotherapy (NACT), (n = 45). Application of five classification algorithms achieved up to 73% sensitivity for plasma, high specificities and accuracies for both blood biofluids, and lower performance for urine. A drop in sensitivities for the NACT group in plasma and serum, with an opposite trend in urine, suggest that Raman spectroscopy could identify chemotherapy-related changes. This study confirms that biofluids' Raman spectroscopy can contribute in ovarian cancer's diagnostic work-up and demonstrates its potential in monitoring treatment response.
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Affiliation(s)
- Panagiotis Giamougiannis
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Raissa V O Silva
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Daniel L D Freitas
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Kássio M G Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Antonios Anagnostopoulos
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Georgios Angelopoulos
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Raj Naik
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Nicholas J Wood
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Pierre L Martin-Hirsch
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
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28
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Phal Y, Yeh K, Bhargava R. Design Considerations for Discrete Frequency Infrared Microscopy Systems. APPLIED SPECTROSCOPY 2021; 75:1067-1092. [PMID: 33876990 PMCID: PMC9993325 DOI: 10.1177/00037028211013372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Discrete frequency infrared chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument's performance mathematically. Finally, we provide a validation approach by enumerating performance metrics that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.
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Affiliation(s)
- Yamuna Phal
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Kevin Yeh
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Rohit Bhargava
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
- Departments of Bioengineering, Mechanical Science and Engineering, Chemical and Biomolecular Engineering, and Chemistry, University of Illinois at Urbana-Champaign, Urbana, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, USA
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29
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Tang JW, Liu QH, Yin XC, Pan YC, Wen PB, Liu X, Kang XX, Gu B, Zhu ZB, Wang L. Comparative Analysis of Machine Learning Algorithms on Surface Enhanced Raman Spectra of Clinical Staphylococcus Species. Front Microbiol 2021; 12:696921. [PMID: 34531835 PMCID: PMC8439569 DOI: 10.3389/fmicb.2021.696921] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 07/30/2021] [Indexed: 12/13/2022] Open
Abstract
Raman spectroscopy (RS) is a widely used analytical technique based on the detection of molecular vibrations in a defined system, which generates Raman spectra that contain unique and highly resolved fingerprints of the system. However, the low intensity of normal Raman scattering effect greatly hinders its application. Recently, the newly emerged surface enhanced Raman spectroscopy (SERS) technique overcomes the problem by mixing metal nanoparticles such as gold and silver with samples, which greatly enhances signal intensity of Raman effects by orders of magnitudes when compared with regular RS. In clinical and research laboratories, SERS provides a great potential for fast, sensitive, label-free, and non-destructive microbial detection and identification with the assistance of appropriate machine learning (ML) algorithms. However, choosing an appropriate algorithm for a specific group of bacterial species remains challenging, because with the large volumes of data generated during SERS analysis not all algorithms could achieve a relatively high accuracy. In this study, we compared three unsupervised machine learning methods and 10 supervised machine learning methods, respectively, on 2,752 SERS spectra from 117 Staphylococcus strains belonging to nine clinically important Staphylococcus species in order to test the capacity of different machine learning methods for bacterial rapid differentiation and accurate prediction. According to the results, density-based spatial clustering of applications with noise (DBSCAN) showed the best clustering capacity (Rand index 0.9733) while convolutional neural network (CNN) topped all other supervised machine learning methods as the best model for predicting Staphylococcus species via SERS spectra (ACC 98.21%, AUC 99.93%). Taken together, this study shows that machine learning methods are capable of distinguishing closely related Staphylococcus species and therefore have great application potentials for bacterial pathogen diagnosis in clinical settings.
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Affiliation(s)
- Jia-Wei Tang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Qing-Hua Liu
- State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, China
| | - Xiao-Cong Yin
- Department of Laboratory Medicine, School of Medical Technology, Xuzhou Medical University, Xuzhou, China
| | - Ya-Cheng Pan
- School of Life Science, Xuzhou Medical University, Xuzhou, China
| | - Peng-Bo Wen
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Xin Liu
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Xing-Xing Kang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Bing Gu
- Department of Laboratory Medicine, School of Medical Technology, Xuzhou Medical University, Xuzhou, China
- Department of Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zuo-Bin Zhu
- School of Life Science, Xuzhou Medical University, Xuzhou, China
| | - Liang Wang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, China
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30
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GARİP USTAOĞLU Ş, KAYGUSUZ H, BİLGİN MD, SEVERCAN F. Novel approaches for COVID-19 diagnosis and treatment: a nonsystematic review. Turk J Biol 2021; 45:358-371. [PMID: 34803440 PMCID: PMC8573842 DOI: 10.3906/biy-2105-45] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/19/2021] [Indexed: 12/13/2022] Open
Abstract
Since COVID-19 pandemic has been continuously rising and spreading, several original contributions and review articles on COVID-19 started to appear in the literature. The review articles are mainly focus on the current status of the pandemic along with current status of the corona diagnosis and treatment process. Due to some disadvantages of the currently used methods, the improvement on the novel promising diagnosis and treatment methods of corona virus is very important issue. In this review, after briefly discussing the status of current diagnosis and treatment methods, we present to the scientific community, novel promising methods in the diagnosis and treatment of COVID-19. As with other novel approaches, first, the diagnosis potential of mass spectroscopy and optical spectroscopic methods such as UV/visible, infrared, and Raman spectroscopy coupled with chemometrics will be discussed for the corona virus infected samples based on the relevant literature. In vibrational spectroscopy studies, due to complexity of the data, multivariate analysis methods are also applied to data. The application of multivariate analysis tools that can be used to extract useful information from the data for diagnostic and characterisation purposes is also included in this review. The reviewed methods include hierarchical cluster analysis, principal component analysis, linear and quadratic discriminant analysis, support vector machine algorithm, and one form of neural networks namely deep learning method. Second, novel treatment methods such as photodynamic therapy and the use of nanoparticles in the in-corona virus therapy will be discussed. Finally, the advantages of novel promising diagnosis and treatment methods in COVID-19, over standard methods will be discussed. One of the main aims of this paper is to encourage the scientific community to explore the potential of this novel tools for their use in corona virus characterization, diagnosis, and treatment.
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Affiliation(s)
- Şebnem GARİP USTAOĞLU
- Department of Medical Biochemistry, Faculty of Medicine, Altınbaş University, İstanbulTurkey
| | - Hakan KAYGUSUZ
- Department of Basic Sciences, Faculty of Engineering and Natural Sciences, Altınbaş University, İstanbulTurkey
- Sabanci University SUNUM Nanotechnology Research Center, İstanbulTurkey
| | - Mehmet Dinçer BİLGİN
- Department of Biophysics, Faculty of Medicine, Aydın Adnan Menderes University, AydınTurkey
| | - Feride SEVERCAN
- Department of Biophysics, Faculty of Medicine, Altınbaş University, İstanbulTurkey
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31
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Mankar R, Gajjela CC, Shahraki FF, Prasad S, Mayerich D, Reddy R. Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy. Analyst 2021; 146:4822-4834. [PMID: 34198314 DOI: 10.1039/d1an00103e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Mid-infrared Spectroscopic Imaging (MIRSI) provides spatially-resolved molecular specificity by measuring wavelength-dependent mid-infrared absorbance. Infrared microscopes use large numerical aperture objectives to obtain high-resolution images of heterogeneous samples. However, the optical resolution is fundamentally diffraction-limited, and therefore wavelength-dependent. This significantly limits resolution in infrared microscopy, which relies on long wavelengths (2.5 μm to 12.5 μm) for molecular specificity. The resolution is particularly restrictive in biomedical and materials applications, where molecular information is encoded in the fingerprint region (6 μm to 12 μm), limiting the maximum resolving power to between 3 μm and 6 μm. We present an unsupervised curvelet-based image fusion method that overcomes limitations in spatial resolution by augmenting infrared images with label-free visible microscopy. We demonstrate the effectiveness of this approach by fusing images of breast and ovarian tumor biopsies acquired using both infrared and dark-field microscopy. The proposed fusion algorithm generates a hyperspectral dataset that has both high spatial resolution and good molecular contrast. We validate this technique using multiple standard approaches and through comparisons to super-resolved experimentally measured photothermal spectroscopic images. We also propose a novel comparison method based on tissue classification accuracy.
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32
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Lovergne L, Ghosh D, Schuck R, Polyzos AA, Chen AD, Martin MC, Barnard ES, Brown JB, McMurray CT. An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms. Sci Rep 2021; 11:15598. [PMID: 34341363 PMCID: PMC8329289 DOI: 10.1038/s41598-021-93686-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/24/2021] [Indexed: 12/29/2022] Open
Abstract
Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.
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Affiliation(s)
- Lila Lovergne
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dhruba Ghosh
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
| | - Renaud Schuck
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Aris A Polyzos
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Andrew D Chen
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
| | - Michael C Martin
- Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Edward S Barnard
- Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - James B Brown
- Department of Statistics, University of California, Berkeley, CA, 94720, USA
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Cynthia T McMurray
- Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
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33
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Sarigul N, Kurultak İ, Uslu Gökceoğlu A, Korkmaz F. Urine analysis using FTIR spectroscopy: A study on healthy adults and children. JOURNAL OF BIOPHOTONICS 2021; 14:e202100009. [PMID: 33768707 DOI: 10.1002/jbio.202100009] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 03/23/2021] [Accepted: 03/23/2021] [Indexed: 06/12/2023]
Abstract
Urine spectra from 108 healthy volunteers are studied by attenuated total refraction-Fourier transform infrared (ATR-FTIR) spectroscopy. The spectral features are correlated with observable urine components. The variation of spectra within a healthy population is quantified and a library of reference spectra is constructed. Using the band assignments, these spectra are compared with both age-wise and gender-wise. Children show the least intensity variations compared to both adult groups. Young adults show the highest variation, particularly in the 1650 to 1400 cm-1 and 1200 to 900 cm-1 regions. These results indicate the importance of the size of the control group in comparative studies utilizing FTIR. Age-wise comparisons reveal that phosphate and sulfate excretion decreases with age, and that the variance of phosphate among individuals is higher with adults. As for gender-wise comparisons, females show a slightly higher citrate content at 1390 cm-1 regardless of the age and they show a higher variance in the 1200 to 1000 cm-1 region when compared to men.
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Affiliation(s)
- Neslihan Sarigul
- Institute of Nuclear Science, Hacettepe University, Ankara, Turkey
| | - İlhan Kurultak
- Department of Nephrology, Faculty of Medicine, Trakya University, Edirne, Turkey
| | - Arife Uslu Gökceoğlu
- Ankara Training and Research Hospital, University of Health Sciences, Ankara, Turkey
| | - Filiz Korkmaz
- Biophysics Laboratory, Faculty of Engineering, Atilim University, Ankara, Turkey
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34
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Gualerzi A, Picciolini S, Carlomagno C, Rodà F, Bedoni M. Biophotonics for diagnostic detection of extracellular vesicles. Adv Drug Deliv Rev 2021; 174:229-249. [PMID: 33887403 DOI: 10.1016/j.addr.2021.04.014] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/26/2021] [Accepted: 04/15/2021] [Indexed: 02/06/2023]
Abstract
Extracellular Vesicles (EVs) are versatile carriers for biomarkers involved in the pathogenesis of multiple human disorders. Despite the increasing scientific and commercial interest in EV application in diagnostics, traditional biomolecular techniques usually require consistent sample amount, rely on operator-dependent and time- consuming procedures and cannot cope with the nano-size range of EVs, limiting both sensitivity and reproducibility of results. The application of biophotonics, i.e. light-based methods, for the diagnostic detection of EVs has brought to the development of innovative platforms with excellent sensitivity. In this review, we propose an overview of the most promising and emerging technologies used in the field of EV-related biomarker discovery. When tested on clinical samples, the reported biophotonic approaches in most cases have managed to discriminate between nanovesicles and contaminants, achieved much higher resolution compared to traditional procedures, and reached moderate to excellent diagnostic accuracy, thus demonstrating great potentialities for their clinical translation.
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35
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Kuhar N, Nazeer SS, Kumar RV, Mukherjee G, Umapathy S. Infrared Microspectroscopy With Multivariate Analysis to Differentiate Oral Hyperplasia From Squamous Cell Carcinoma: A Proof of Concept for Early Diagnosis. Lasers Surg Med 2021; 53:1435-1445. [PMID: 34058028 DOI: 10.1002/lsm.23427] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 04/21/2021] [Accepted: 05/17/2021] [Indexed: 01/31/2023]
Abstract
BACKGROUND AND OBJECTIVES Despite having numerous advances in therapeutics, mortality and morbidity due to oral cancer incidence are still very high. Early detection can improve the chances of survival in most patients. However, diagnosis at early stages can be challenging as premalignant conditions are usually asymptomatic. Currently, histological assessment remains the gold standard for diagnosis. Early diagnosis poses challenges to pathologists due to less severe morphological changes associated with early stages. Therefore, a fast and robust method of detection based on molecular changes is needed for early diagnosis. © 2021 Wiley Periodicals LLC. STUDY DESIGN/MATERIAL AND METHODS In the present study, Fourier transform infrared (FTIR) spectroscopic imaging has been used to differentiate early-stage oral hyperplasia from adjacent normal (AN) and oral squamous cell carcinoma (OSCC). Hyperplasia is often considered as an initial event in the pathogenesis of oral cancer and OSCC is the most common advanced stage of malignancy. Differentiating normal versus hyperplasia and hyperplasia versus OSCC can remain quite challenging on occasion using conventional staining as the histological assessment is based on morphological changes. RESULTS Unsupervised hierarchical cluster analysis (UHCA) has been performed on FTIR images of multiple tissues together that provided some degree of classification among tissue groups. The AN epithelium clustered distinctively using UHCA from both hyperplasia and grades 1 and 2 of OSCC. An increase in the content of DNA, denaturation of protein, and altered lipid structures were more clearly elucidated with spectral analysis. CONCLUSION This study demonstrates a simple strategy to differentiate early-stage oral hyperplasia from AN and OSCC using UHCA. This study also proposes a future alternative method where FTIR imaging can be used as a diagnostic tool for cancer at early stages.
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Affiliation(s)
- Nikki Kuhar
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bengaluru, Karnataka, 560 012, India
| | - Shaiju S Nazeer
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bengaluru, Karnataka, 560 012, India.,Department of Chemistry, Indian Institute of Space Sciences and Technology, Thiruvananthapuram, Kerala, 695 547, India
| | - Rekha V Kumar
- Department of Pathology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, 560 029, India
| | - Geetashree Mukherjee
- Department of Pathology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, 560 029, India
| | - Siva Umapathy
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bengaluru, Karnataka, 560 012, India.,Department of Instrumentation & Applied Physics, Indian Institute of Science, Bangalore, Karnataka, 560012, India
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36
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Iakab S, Ràfols P, Correig-Blanchar X, García-Altares M. Perspective on Multimodal Imaging Techniques Coupling Mass Spectrometry and Vibrational Spectroscopy: Picturing the Best of Both Worlds. Anal Chem 2021; 93:6301-6310. [PMID: 33856207 PMCID: PMC8491157 DOI: 10.1021/acs.analchem.0c04986] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 04/07/2021] [Indexed: 01/19/2023]
Abstract
Studies on complex biological phenomena often combine two or more imaging techniques to collect high-quality comprehensive data directly in situ, preserving the biological context. Mass spectrometry imaging (MSI) and vibrational spectroscopy imaging (VSI) complement each other in terms of spatial resolution and molecular information. In the past decade, several combinations of such multimodal strategies arose in research fields as diverse as microbiology, cancer, and forensics, overcoming many challenges toward the unification of these techniques. Here we focus on presenting the advantages and challenges of multimodal imaging from the point of view of studying biological samples as well as giving a perspective on the upcoming trends regarding this topic. The latest efforts in the field are discussed, highlighting the purpose of the technique for clinical applications.
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Affiliation(s)
- Stefania
Alexandra Iakab
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - Pere Ràfols
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - Xavier Correig-Blanchar
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
| | - María García-Altares
- Rovira
i Virgili University, Department of Electronic
Engineering, IISPV, 43007 Tarragona, Spain
- Spanish
Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM), 28029 Madrid, Spain
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37
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Infrared Spectral Microscopy: A Primer for the Interventional Radiologist. J Vasc Interv Radiol 2021; 32:878-881.e1. [PMID: 33771714 DOI: 10.1016/j.jvir.2021.03.524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/03/2021] [Accepted: 03/14/2021] [Indexed: 11/20/2022] Open
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Carlomagno C, Bertazioli D, Gualerzi A, Picciolini S, Banfi PI, Lax A, Messina E, Navarro J, Bianchi L, Caronni A, Marenco F, Monteleone S, Arienti C, Bedoni M. COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections. Sci Rep 2021; 11:4943. [PMID: 33654146 PMCID: PMC7925543 DOI: 10.1038/s41598-021-84565-3] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 02/15/2021] [Indexed: 12/20/2022] Open
Abstract
The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89-92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.
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Affiliation(s)
- C Carlomagno
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy.
| | - D Bertazioli
- Università di Milano-Bicocca, Viale Sarca 366, 20126, Milan, Italy
| | - A Gualerzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - S Picciolini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - P I Banfi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - A Lax
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - E Messina
- Università di Milano-Bicocca, Viale Sarca 366, 20126, Milan, Italy
| | - J Navarro
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - L Bianchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - A Caronni
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - F Marenco
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - S Monteleone
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - C Arienti
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy
| | - M Bedoni
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148, Milan, Italy.
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Derruau S, Gobinet C, Untereiner V, Sockalingum GD, Nassif A, Viguier M, Piot O, Lorimier S. New insights into hidradenitis suppurativa diagnosis via salivary infrared biosignatures: A pilot study. JOURNAL OF BIOPHOTONICS 2021; 14:e202000327. [PMID: 33231348 DOI: 10.1002/jbio.202000327] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/17/2020] [Accepted: 11/22/2020] [Indexed: 06/11/2023]
Abstract
Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease which can lead to a prolonged physical disability. HS diagnosis is exclusively clinical with the absence of biomarkers. Our study aims at assessing the HS-diagnostic potential of infrared spectroscopy from saliva, as a biofluid reflecting the body's pathophysiological state. Infrared spectra from 127 patients (57 HS and 70 non-HS) were processed by multivariate methods: principal component analysis coupled with Kruskal-Wallis or Mann-Whitney tests to identify discriminant spectral wavenumbers and linear discriminant analysis to evaluate the performances of HS-diagnostic approach. Infrared features, mainly in the 1300 cm-1 -1600 cm-1 region, were identified as discriminant for HS and prediction models revealed diagnostic performances of about 80%. Tobacco and obesity, two main HS risk factors, do not seem to alter the infrared diagnosis. This pilot study shows the potential of salivary "liquid biopsy" associated to vibrational spectroscopy to develop a personalized medical approach for HS patients' management.
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Affiliation(s)
- Stéphane Derruau
- Université de Reims Champagne-Ardenne, BioSpect EA 7506, UFR de Pharmacie, Reims, France
- Université de Reims Champagne-Ardenne, UFR Odontologie, Département de Biologie Orale, Reims, France
- Centre Hospitalier Universitaire de Reims, Pôle de Médecine Bucco-dentaire, Reims, France
| | - Cyril Gobinet
- Université de Reims Champagne-Ardenne, BioSpect EA 7506, UFR de Pharmacie, Reims, France
| | | | - Ganesh D Sockalingum
- Université de Reims Champagne-Ardenne, BioSpect EA 7506, UFR de Pharmacie, Reims, France
| | - Aude Nassif
- Service de Pathologie Infectieuse et Tropicale, Institut Pasteur, Centre Médical, Paris, France
| | - Manuelle Viguier
- Centre Hospitalier Universitaire de Reims, Service de Dermatologie -Vénéréologie, Reims, France
| | - Olivier Piot
- Université de Reims Champagne-Ardenne, BioSpect EA 7506, UFR de Pharmacie, Reims, France
- Université de Reims Champagne-Ardenne, PICT, Reims, France
| | - Sandrine Lorimier
- Université de Reims Champagne-Ardenne, UFR Odontologie, Département de Biologie Orale, Reims, France
- Centre Hospitalier Universitaire de Reims, Pôle de Médecine Bucco-dentaire, Reims, France
- Université de Reims Champagne-Ardenne, GRESPI EA-4694, UFR Sciences Exactes et Naturelles, Reims, France
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40
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Martinez L, He L. Detection of Mycotoxins in Food Using Surface-Enhanced Raman Spectroscopy: A Review. ACS APPLIED BIO MATERIALS 2021; 4:295-310. [PMID: 35014285 DOI: 10.1021/acsabm.0c01349] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Mycotoxins are toxic metabolites produced by fungi that contaminate many important crops worldwide. Humans are commonly exposed to mycotoxins through the consumption of contaminated food products. Mycotoxin contamination is unpredictable and unavoidable; it occurs at any point in the food production system under favorable conditions, and they cannot be destroyed by common heat treatments, because of their high thermal stability. Early and fast detection plays an essential role in this unique challenge to monitor the presence of these compounds in the food chain. Surface-enhanced Raman spectroscopy (SERS) is an advanced spectroscopic technique that integrates Raman spectroscopic molecular fingerprinting and enhanced sensitivity based on nanotechnology to meet the requirement of sensitivity and selectivity, but that can also be performed in a cost-effective and straightforward manner. This Review focuses on the SERS methodologies applied to date for qualitative and quantitative analysis of mycotoxins based on a variety of SERS substrates, as well as our perspectives on current limitations and future trends for applying this technique to mycotoxin analyses.
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Affiliation(s)
- Lourdes Martinez
- Department of Food Science, University of Massachusetts, Amherst, Massachusetts United States
| | - Lili He
- Department of Food Science, University of Massachusetts, Amherst, Massachusetts United States
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41
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Gardner B, Matousek P, Stone N. Self-absorption corrected non-invasive transmission Raman spectroscopy (of biological tissue). Analyst 2021; 146:1260-1267. [DOI: 10.1039/d0an01940b] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Higher contrast of subsurface Raman spectra is achievable with self-absorption corrected transmission Raman spectroscopy. (Desired signal in red, interfering matrix artefacts in blue.)
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Affiliation(s)
- Benjamin Gardner
- School of Physics and Astronomy
- University of Exeter
- Exeter
- UK
- Royal Devon and Exeter NHS Foundation Trust
| | - Pavel Matousek
- Central Laser Facility
- Research Complex at Harwell
- STFC Rutherford Appleton Laboratory
- Harwell Oxford
- UK
| | - Nicholas Stone
- School of Physics and Astronomy
- University of Exeter
- Exeter
- UK
- Royal Devon and Exeter NHS Foundation Trust
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42
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Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities. Molecules 2020; 25:molecules25235547. [PMID: 33256052 PMCID: PMC7731440 DOI: 10.3390/molecules25235547] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/20/2020] [Accepted: 11/22/2020] [Indexed: 01/18/2023] Open
Abstract
Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.
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43
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Hackshaw KV, Miller JS, Aykas DP, Rodriguez-Saona L. Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples. Molecules 2020; 25:E4725. [PMID: 33076318 PMCID: PMC7587585 DOI: 10.3390/molecules25204725] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 09/27/2020] [Accepted: 09/28/2020] [Indexed: 12/16/2022] Open
Abstract
Vibrational spectroscopy (mid-infrared (IR) and Raman) and its fingerprinting capabilities offer rapid, high-throughput, and non-destructive analysis of a wide range of sample types producing a characteristic chemical "fingerprint" with a unique signature profile. Nuclear magnetic resonance (NMR) spectroscopy and an array of mass spectrometry (MS) techniques provide selectivity and specificity for screening metabolites, but demand costly instrumentation, complex sample pretreatment, are labor-intensive, require well-trained technicians to operate the instrumentation, and are less amenable for implementation in clinics. The potential for vibration spectroscopy techniques to be brought to the bedside gives hope for huge cost savings and potential revolutionary advances in diagnostics in the clinic. We discuss the utilization of current vibrational spectroscopy methodologies on biologic samples as an avenue towards rapid cost saving diagnostics.
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Affiliation(s)
- Kevin V. Hackshaw
- Department of Internal Medicine, Division of Rheumatology, Dell Medical School, The University of Texas, 1601 Trinity St, Austin, TX 78712, USA
| | - Joseph S. Miller
- Department of Medicine, Ohio University Heritage College of Osteopathic Medicine, Dublin, OH 43016, USA;
| | - Didem P. Aykas
- Department of Food Science and Technology, Ohio State University, Columbus, OH 43210, USA; (D.P.A.); (L.R.-S.)
- Department of Food Engineering, Faculty of Engineering, Adnan Menderes University, Aydin 09100, Turkey
| | - Luis Rodriguez-Saona
- Department of Food Science and Technology, Ohio State University, Columbus, OH 43210, USA; (D.P.A.); (L.R.-S.)
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44
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Xu Z, Jiang Y, Ji J, Forsberg E, Li Y, He S. Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning. OPTICS EXPRESS 2020; 28:30686-30700. [PMID: 33115064 DOI: 10.1364/oe.406036] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A transmission hyperspectral microscopic imager (THMI) that utilizes machine learning algorithms for hyperspectral detection of microalgae is presented. The THMI system has excellent performance with spatial and spectral resolutions of 4 µm and 3 nm, respectively. We performed hyperspectral imaging (HSI) of three species of microalgae to verify their absorption characteristics. Transmission spectra were analyzed using principal component analysis (PCA) and peak ratio algorithms for dimensionality reduction and feature extraction, and a support vector machine (SVM) model was used for classification. The average accuracy, sensitivity and specificity to distinguish one species from the other two species were found to be 94.4%, 94.4% and 97.2%, respectively. A species identification experiment for a group of mixed microalgae in solution demonstrates the usability of the classification method. Using a random forest (RF) model, the growth stage in a phaeocystis growth cycle cultivated under laboratory conditions was predicted with an accuracy of 98.1%, indicating the feasibility to evaluate the growth state of microalgae through their transmission spectra. Experimental results show that the THMI system has the capability for classification, identification and growth stage estimation of microalgae, with strong potential for in-situ marine environmental monitoring and early warning detection applications.
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45
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Suryadevara V, Nazeer SS, Sreedhar H, Adelaja O, Kajdacsy-Balla A, Natarajan V, Walsh MJ. Infrared spectral microscopy as a tool to monitor lung fibrosis development in a model system. BIOMEDICAL OPTICS EXPRESS 2020; 11:3996-4007. [PMID: 33014581 PMCID: PMC7510888 DOI: 10.1364/boe.394730] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 06/11/2023]
Abstract
Tissue fibrosis is a progressive and destructive disease process that can occur in many different organs including the liver, kidney, skin, and lungs. Fibrosis is typically initiated by inflammation as a result of chronic insults such as infection, chemicals and autoimmune diseases. Current approaches to examine organ fibrosis are limited to radiological and histological analyses. Infrared spectroscopic imaging offers a potential alternative approach to gain insight into biochemical changes associated with fibrosis progression. In this study, we demonstrate that IR imaging of a mouse model of pulmonary fibrosis can identify biochemical changes observed with fibrosis progression and the beginning of resolution using K-means analysis, spectral ratios and multivariate data analysis. This study demonstrates that IR imaging may be a useful approach to understand the biochemical events associated with fibrosis initiation, progression and resolution for both the clinical setting and for assessing novel anti-fibrotic drugs in a model system.
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Affiliation(s)
- Vidyani Suryadevara
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Shaiju S. Nazeer
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Hari Sreedhar
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Oluwatobi Adelaja
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - André Kajdacsy-Balla
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Viswanathan Natarajan
- Department of Pharmacology, University of Illinois at Chicago, Chicago, IL 60612, USA
- Contributed equally as senior co-authors
| | - Michael J. Walsh
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
- Contributed equally as senior co-authors
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46
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Kratz C, Furchner A, Sun G, Rappich J, Hinrichs K. Sensing and structure analysis by in situIR spectroscopy: from mL flow cells to microfluidic applications. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2020; 32:393002. [PMID: 32235045 DOI: 10.1088/1361-648x/ab8523] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 03/31/2020] [Indexed: 06/11/2023]
Abstract
In situmid-infrared (MIR) spectroscopy in liquids is an emerging field for the analysis of functional surfaces and chemical reactions. Different basic geometries exist forin situMIR spectroscopy in milliliter (mL) and microfluidic flow cells, such as attenuated total reflection (ATR), simple reflection, transmission and fiber waveguides. After a general introduction of linear opticalin situMIR techniques, the methodology of ATR, ellipsometric and microfluidic applications in single-reflection geometries is presented. Selected examples focusing on thin layers relevant to optical, electronical, polymer, biomedical, sensing and silicon technology are discussed. The development of an optofluidic platform translates IR spectroscopy to the world of micro- and nanofluidics. With the implementation of SEIRA (surface enhanced infrared absorption) interfaces, the sensitivity of optofluidic analyses of biomolecules can be improved significantly. A large variety of enhancement surfaces ranging from tailored nanostructures to metal-island film substrates are promising for this purpose. Meanwhile, time-resolved studies, such as sub-monolayer formation of organic molecules in nL volumes, become available in microscopic or laser-based set-ups. With the adaption of modern brilliant IR sources, such as tunable and broadband IR lasers as well as frequency comb sources, possible applications of far-field IR spectroscopy inin situsensing with high lateral (sub-mm) and time (sub-s) resolution are considerably extended.
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Affiliation(s)
| | | | - Guoguang Sun
- ISAS-e.V., Schwarzschildstr. 8, 12489 Berlin, Germany
| | - Jörg Rappich
- Helmholtz-Zentrum Berlin für Materialien und Energie GmbH, Kekuléstr. 5, 12489 Berlin, Germany
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47
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Kochan K, Nethercott C, Taghavimoghaddam J, Richardson Z, Lai E, Crawford SA, Peleg AY, Wood BR, Heraud P. Rapid Approach for Detection of Antibiotic Resistance in Bacteria Using Vibrational Spectroscopy. Anal Chem 2020; 92:8235-8243. [PMID: 32407103 DOI: 10.1021/acs.analchem.0c00474] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Here, we applied vibrational spectroscopy to investigate the drug response following incubation of S. aureus with oxacillin. The main focus of this work was to identify the chemical changes caused by oxacillin over time and to determine the feasibility of the spectroscopic approach to detect antimicrobial resistance. The oxacillin-induced changes in the chemical composition of susceptible bacteria, preceding (and leading to) the inhibition of growth, included an increase in the relative content of nucleic acids, alteration in the α-helical/β-sheet protein ratio, structural changes in carbohydrates (observed via changes in the band at 1035 cm-1), and significant thickening of the cell wall. These observations enabled a dose-dependent discrimination between susceptible bacteria incubated with and without oxacillin after 120 min. In methicillin resistant strains, no spectral differences were observed between cells, regardless of drug exposure. These results pave the way for a new, rapid spectroscopic approach to detect drug resistance in pathogens, based on their early positive/negative drug response.
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Affiliation(s)
- Kamila Kochan
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Cara Nethercott
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | | | - Zack Richardson
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Elizabeth Lai
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Simon A Crawford
- The Ramaciotti Centre for Cryo Electron Microscopy, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Anton Y Peleg
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,Department of Infectious Diseases, The Alfred Hospital and Central Clinical School, Monash University, Melbourne 3004, Victoria, Australia
| | - Bayden R Wood
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Philip Heraud
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
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48
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Kraka E, Zou W, Tao Y. Decoding chemical information from vibrational spectroscopy data: Local vibrational mode theory. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2020. [DOI: 10.1002/wcms.1480] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Elfi Kraka
- Department of Chemistry Southern Methodist University Dallas Texas USA
| | - Wenli Zou
- Institute of Modern Physics Northwest University and Shaanxi Key Laboratory for Theoretical Physics Frontiers, Xi'an Shaanxi PR China
| | - Yunwen Tao
- Department of Chemistry Southern Methodist University Dallas Texas USA
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49
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Application of chemometric methods to the analysis of multimodal chemical images of biological tissues. Anal Bioanal Chem 2020; 412:5179-5190. [PMID: 32356097 DOI: 10.1007/s00216-020-02595-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 02/20/2020] [Accepted: 03/10/2020] [Indexed: 10/24/2022]
Abstract
Current histology techniques, such as tissue staining or histochemistry protocols, provide very limited chemical information about the tissues. Chemical imaging technologies such as infrared, Raman, and mass spectrometry imaging, are powerful analytical techniques with a huge potential in describing the chemical composition of sample surfaces. In this work, three images of the same tissue slice using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, infrared microspectroscopy, and an RGB picture from a conventional hematoxylin/eosin (H/E) staining are simultaneously analyzed. These fused images were analyzed by multivariate curve resolution-alternating least squares (MCR-ALS), which provided, for each component, its distribution within the tissue surface, its IR spectrum fingerprint, its characteristic mass values, and the contribution of the RGB channels of the H/E staining. Compared with the individual analysis of each of the images alone, the fusion of the three images showed the relationship between the different types of chemical/biological information and enabled a better interpretation of the tissue under study. In addition, the least-squares projection of the MCR-ALS resolved spectra of components at low spatial resolution onto the IR and RBG images at high spatial resolution, provided a better delimitation of the sample constituents on the image, giving a more precise description of their distribution on the investigated tissue. The application of this procedure can be of interest in different research areas in which a good description of the spatial distribution of the chemical constituents of the samples is needed, such as in biomedicine, food, or environmental research.
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50
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Hubbard TJE, Shore A, Stone N. Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens. Analyst 2020; 144:6479-6496. [PMID: 31616885 DOI: 10.1039/c9an01163c] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Raman spectroscopy, a form of vibrational spectroscopy, has the ability to provide sensitive and specific biochemical analysis of tissue. This review article provides an in-depth analysis of the suitability of different Raman spectroscopy techniques in providing intra-operative margin analysis in a range of solid tumour pathologies. Surgical excision remains the primary treatment of a number of solid organ cancers. Incomplete excision of a tumour and positive margins on histopathological analysis is associated with a worse prognosis, the need for adjuvant therapies with significant side effects and a resulting financial burden. The provision of intra-operative margin analysis of surgically excised tumour specimens would be beneficial for a number of pathologies, as there are no widely adopted and accurate methods of margin analysis, beyond histopathology. The limitations of Raman spectroscopic studies to date are discussed and future work necessary to enable translation to clinical use is identified. We conclude that, although there remain a number of challenges in translating current techniques into a clinically effective tool, studies so far demonstrate that Raman Spectroscopy has the attributes to successfully perform highly accurate intra-operative margin analysis in a clinically relevant environment.
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