1
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Wu D, Fedorov Kukk A, Panzer R, Emmert S, Roth B. In vivo Raman spectroscopic and fluorescence study of suspected melanocytic lesions and surrounding healthy skin. JOURNAL OF BIOPHOTONICS 2024; 17:e202400050. [PMID: 38932707 DOI: 10.1002/jbio.202400050] [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] [Received: 02/15/2024] [Revised: 04/25/2024] [Accepted: 05/03/2024] [Indexed: 06/28/2024]
Abstract
Cutaneous melanoma is the most lethal skin cancer and noninvasively distinguishing it from benign tumor is a major challenge. Raman spectroscopic measurements were conducted on 65 suspected melanocytic lesions and surrounding healthy skin from 47 patients. Compared to the spectra of healthy skin, spectra of melanocytic lesions exhibited lower intensities in carotenoid bands and higher intensities in lipid and melanin bands, suggesting similar variations in the content of these components. Distinct variations were observed among the autofluorescence intensities of healthy skin, benign nevi and malignant melanoma. By incorporating autofluorescence information, the classification accuracy of the support vector machine for spectra of healthy skin, nevi, and melanoma reached 90.2%, surpassing the 87.9% accuracy achieved without autofluorescence, with this difference being statistically significant. These findings indicate the diagnostic value of autofluorescence intensity, which reflect differences in fluorophore content, chemical composition, and structure among healthy skin, nevi, and melanoma.
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Affiliation(s)
- Di Wu
- Hannover Centre for Optical Technologies, Leibniz University Hannover, Hanover, Germany
| | - Anatoly Fedorov Kukk
- Hannover Centre for Optical Technologies, Leibniz University Hannover, Hanover, Germany
| | | | | | - Bernhard Roth
- Hannover Centre for Optical Technologies, Leibniz University Hannover, Hanover, Germany
- Cluster of Excellence PhoenixD, Leibniz University Hannover, Hannover, Germany
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2
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Liu D, Hennelly BM. Wavenumber Calibration Protocol for Raman Spectrometers Using Physical Modelling and a Fast Search Algorithm. APPLIED SPECTROSCOPY 2024; 78:790-805. [PMID: 38825581 DOI: 10.1177/00037028241254847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
A wavenumber calibration protocol is proposed that replaces polynomial fitting to relate the detector axis and the wavenumber shift. The physical model of the Raman spectrometer is used to derive a mathematical expression relating the detector plane to the wavenumber shift, in terms of the system parameters including the spectrograph focal length, the grating angle, and the laser wavelength; the model is general to both reflection and transmission gratings. A fast search algorithm detects the set of parameters that best explains the position of spectral lines recorded on the detector for a known reference standard. Using three different reference standards, four different systems, and hundreds of spectra recorded with a rotating grating, we demonstrate the superior accuracy of the technique, especially in bands outside of the outermost reference peaks when compared with polynomial fitting. We also provide a thorough review of wavenumber calibration for Raman spectroscopy and we introduce several new evaluation metrics to this field borrowed from chemometrics, including leave-one-out and leave-half-out cross-validation.
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Affiliation(s)
- Dongyue Liu
- Department of Electronic Engineering, Maynooth University, Kildare, Ireland
| | - Bryan M Hennelly
- Department of Electronic Engineering, Maynooth University, Kildare, Ireland
- Department of Computer Science, Maynooth University, Kildare, Ireland
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3
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Lin J, Li Y, Lin X, Che C. Decision-level data fusion based on laser-induced breakdown and Raman spectroscopy: A study of bimodal spectroscopy for diagnosis of lung cancer at different stages. Talanta 2024; 275:126194. [PMID: 38703481 DOI: 10.1016/j.talanta.2024.126194] [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: 03/06/2024] [Revised: 04/22/2024] [Accepted: 04/30/2024] [Indexed: 05/06/2024]
Abstract
Lung cancer staging is crucial for personalized treatment and improved prognosis. We propose a novel bimodal diagnostic approach that integrates LIBS and Raman technologies into a single platform, enabling comprehensive tissue elemental and molecular analysis. This strategy identifies critical staging elements and molecular marker signatures of lung tumors. LIBS detects concentration patterns of elemental lines including Mg (I), Mg (II), Ca (I), Ca (II), Fe (I), and Cu (II). Concurrently, Raman spectroscopy identifies changes in molecular content, such as phenylalanine (1033 cm-1), tyrosine (1174 cm-1), tryptophan (1207 cm-1), amide III (1267 cm-1), and proteins (1126 cm-1 and 1447 cm-1), among others. The bimodal information is fused using a decision-level Bayesian fusion model, significantly enhancing the performance of the convolutional neural network architecture in classification algorithms, with an accuracy of 99.17 %, sensitivity of 99.17 %, and specificity of 99.88 %. This study provides a powerful new tool for the accurate staging and diagnosis of lung tumors.
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Affiliation(s)
- Jingjun Lin
- Changchun University of Technology, Changchun, Jilin, 130012, China
| | - Yao Li
- Changchun University of Technology, Changchun, Jilin, 130012, China
| | - Xiaomei Lin
- Changchun University of Technology, Changchun, Jilin, 130012, China.
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4
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Boudries R, Williams H, Paquereau-Gaboreau S, Bashir S, Hojjat Jodaylami M, Chisanga M, Trudeau LÉ, Masson JF. Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience. ACS NANO 2024. [PMID: 39088751 DOI: 10.1021/acsnano.4c05200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/03/2024]
Abstract
Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.
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Affiliation(s)
- Ryma Boudries
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
| | - Hannah Williams
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
| | - Soraya Paquereau-Gaboreau
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
- Department of Pharmacology and Physiology, Department of Neurosciences, Faculty of Medicine, Université de Montréal, C.P. 6128 Succ. Centre-ville, Montréal, Quebec H3C 3J7, Canada
- Neural Signalling and Circuitry Research Group (SNC), Center for Interdisciplinary Research on the Brain and Learning (CIRCA), Université de Montréal, C.P. 6128 Succ. Centre-ville, Montréal, Quebec H3C 3J7, Canada
| | - Saba Bashir
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
| | - Maryam Hojjat Jodaylami
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
| | - Malama Chisanga
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
| | - Louis-Éric Trudeau
- Department of Pharmacology and Physiology, Department of Neurosciences, Faculty of Medicine, Université de Montréal, C.P. 6128 Succ. Centre-ville, Montréal, Quebec H3C 3J7, Canada
- Neural Signalling and Circuitry Research Group (SNC), Center for Interdisciplinary Research on the Brain and Learning (CIRCA), Université de Montréal, C.P. 6128 Succ. Centre-ville, Montréal, Quebec H3C 3J7, Canada
| | - Jean-Francois Masson
- Department of Chemistry, Institut Courtois, Quebec Center for Advanced Materials (QCAM), and Regroupement Québécois sur les Matériaux de Pointe (RQMP), Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, Quebec H3C 3J7, Canada
- Neural Signalling and Circuitry Research Group (SNC), Center for Interdisciplinary Research on the Brain and Learning (CIRCA), Université de Montréal, C.P. 6128 Succ. Centre-ville, Montréal, Quebec H3C 3J7, Canada
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5
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Wei L, Kushwaha R, Sadhukhan T, Wu H, Dao A, Zhang Z, Zhu H, Gong Q, Ru J, Liang C, Zhang P, Banerjee S, Huang H. Dinuclear Tridentate Ru(II) Complex with Strong Near-Infrared Light-Triggered Anticancer Activity. J Med Chem 2024; 67:11125-11137. [PMID: 38905437 DOI: 10.1021/acs.jmedchem.4c00624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
The design of the dinuclear Ru(II) complex (Ru2) with strong near-infrared (NIR) absorption properties has been reported for efficient anticancer phototherapy. Under 700 nm LED light excitation, Ru2 exhibited remarkable synergistic type I/II photosensitization ability and photocatalytic activity toward intracellular biomolecules. Ru2 showed impressive 700 nm light-triggered anticancer activity under normoxia and hypoxia compared with the clinically used photosensitizer Chlorin e6. The mechanistic studies showed that Ru2 induced intracellular redox imbalance and perturbed the energy metabolism and biosynthesis in A549 cancer cells. Overall, this work provides a new strategy for developing efficient metal-based complexes for anticancer phototherapy under NIR light.
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Affiliation(s)
- Li Wei
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, P.R. China
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, P.R. China
| | - Rajesh Kushwaha
- Department of Chemistry, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Tumpa Sadhukhan
- Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu 603203, India
| | - Haorui Wu
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, P.R. China
| | - Anyi Dao
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, P.R. China
| | - Zhishang Zhang
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, P.R. China
| | - Haotu Zhu
- Department of Oncology, Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong 518107, P.R. China
| | - Qiufang Gong
- Institute for Advanced Research, Cixi Biomedical Research Institute, Wenzhou Medical University, Wenzhou, Zhejinag 325035, P.R. China
| | - Jiaxi Ru
- Institute for Advanced Research, Cixi Biomedical Research Institute, Wenzhou Medical University, Wenzhou, Zhejinag 325035, P.R. China
| | - Chao Liang
- Institute for Advanced Research, Cixi Biomedical Research Institute, Wenzhou Medical University, Wenzhou, Zhejinag 325035, P.R. China
| | - Pingyu Zhang
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, P.R. China
| | - Samya Banerjee
- Department of Chemistry, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India
| | - Huaiyi Huang
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong 518107, P.R. China
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6
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Koch T, Ackermann R, Stoecker A, Meyer-Zedler T, Gabler T, Lippoldt T, Missbach-Guentner J, Russmann C, Popp J, Nolte S. Ultrabroadband two-beam coherent anti-Stokes Raman scattering and spontaneous Raman spectroscopy of organic fluids: A comparative study. JOURNAL OF BIOPHOTONICS 2024:e202300505. [PMID: 38982549 DOI: 10.1002/jbio.202300505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 04/14/2024] [Accepted: 06/17/2024] [Indexed: 07/11/2024]
Abstract
Spontaneous Raman spectroscopy is a well-established diagnostic tool, allowing for the identification of all Raman active species with a single measurement. Yet, it may suffer from low-signal intensity and fluorescent background. In contrast, coherent anti-Stokes Raman scattering (CARS) offers laser-like signals, but the traditional approach lacks the multiplex capability of spontaneous Raman spectroscopy. We present an ultrabroadband CARS setup which aims at exciting the full spectrum (300-3700 cm-1) of biological molecules. A dual-output optical parametric amplifier provides a ~7 fs pump/Stokes and a ~700 fs probe pulse. CARS spectra of DMSO, ethanol, and methanol show great agreement with spontaneous Raman spectroscopy and superiority in fluorescent environments. The spectral resolution proves sufficient to differentiate between the complex spectra of L-proline and hydroxyproline. Moreover, decay constants in the sub picosecond range are determined for individual Raman transitions, providing an additional approach for sample characterization.
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Affiliation(s)
- Timea Koch
- Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Roland Ackermann
- Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Axel Stoecker
- Faculty of Engineering and Health, University of Applied Science and Arts, Goettingen, Germany
| | - Tobias Meyer-Zedler
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
- Leibniz Institute of Photonic Technology, Jena, Germany
| | - Thomas Gabler
- Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Tom Lippoldt
- Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
| | | | - Christoph Russmann
- Faculty of Engineering and Health, University of Applied Science and Arts, Goettingen, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center, Goettingen, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Jena, Germany
| | - Stefan Nolte
- Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Germany
- Fraunhofer Institute for Applied Optics and Precision Engineering IOF, Jena, Germany
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7
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Khadem H, Mangini M, Farazpour S, De Luca AC. Correlative Raman Imaging: Development and Cancer Applications. BIOSENSORS 2024; 14:324. [PMID: 39056600 PMCID: PMC11274409 DOI: 10.3390/bios14070324] [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] [Received: 05/24/2024] [Revised: 06/26/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
Despite extensive research efforts, cancer continues to stand as one of the leading causes of death on a global scale. To gain profound insights into the intricate mechanisms underlying cancer onset and progression, it is imperative to possess methodologies that allow the study of cancer cells at the single-cell level, focusing on critical parameters such as cell morphology, metabolism, and molecular characteristics. These insights are essential for effectively discerning between healthy and cancerous cells and comprehending tumoral progression. Recent advancements in microscopy techniques have significantly advanced the study of cancer cells, with Raman microspectroscopy (RM) emerging as a particularly powerful tool. Indeed, RM can provide both biochemical and spatial details at the single-cell level without the need for labels or causing disruptions to cell integrity. Moreover, RM can be correlated with other microscopy techniques, creating a synergy that offers a spectrum of complementary insights into cancer cell morphology and biology. This review aims to explore the correlation between RM and other microscopy techniques such as confocal fluoresce microscopy (CFM), atomic force microscopy (AFM), digital holography microscopy (DHM), and mass spectrometry imaging (MSI). Each of these techniques has their own strengths, providing different perspectives and parameters about cancer cell features. The correlation between information from these various analysis methods is a valuable tool for physicians and researchers, aiding in the comprehension of cancer cell morphology and biology, unraveling mechanisms underlying cancer progression, and facilitating the development of early diagnosis and/or monitoring cancer progression.
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Affiliation(s)
- Hossein Khadem
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Maria Mangini
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Somayeh Farazpour
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
| | - Anna Chiara De Luca
- Institute for Experimental Endocrinology and Oncology 'G. Salvatore', IEOS-Second Unit, National Research Council, 80131 Naples, Italy
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Ranasinghe JC, Wang Z, Huang S. Unveiling brain disorders using liquid biopsy and Raman spectroscopy. NANOSCALE 2024; 16:11879-11913. [PMID: 38845582 PMCID: PMC11290551 DOI: 10.1039/d4nr01413h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.
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Affiliation(s)
- Jeewan C Ranasinghe
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Ziyang Wang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Shengxi Huang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
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Zhao J, Lui H, Kalia S, Lee TK, Zeng H. Improving skin cancer detection by Raman spectroscopy using convolutional neural networks and data augmentation. Front Oncol 2024; 14:1320220. [PMID: 38962264 PMCID: PMC11219827 DOI: 10.3389/fonc.2024.1320220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 05/23/2024] [Indexed: 07/05/2024] Open
Abstract
Background Our previous studies have demonstrated that Raman spectroscopy could be used for skin cancer detection with good sensitivity and specificity. The objective of this study is to determine if skin cancer detection can be further improved by combining deep neural networks and Raman spectroscopy. Patients and methods Raman spectra of 731 skin lesions were included in this study, containing 340 cancerous and precancerous lesions (melanoma, basal cell carcinoma, squamous cell carcinoma and actinic keratosis) and 391 benign lesions (melanocytic nevus and seborrheic keratosis). One-dimensional convolutional neural networks (1D-CNN) were developed for Raman spectral classification. The stratified samples were divided randomly into training (70%), validation (10%) and test set (20%), and were repeated 56 times using parallel computing. Different data augmentation strategies were implemented for the training dataset, including added random noise, spectral shift, spectral combination and artificially synthesized Raman spectra using one-dimensional generative adversarial networks (1D-GAN). The area under the receiver operating characteristic curve (ROC AUC) was used as a measure of the diagnostic performance. Conventional machine learning approaches, including partial least squares for discriminant analysis (PLS-DA), principal component and linear discriminant analysis (PC-LDA), support vector machine (SVM), and logistic regression (LR) were evaluated for comparison with the same data splitting scheme as the 1D-CNN. Results The ROC AUC of the test dataset based on the original training spectra were 0.886±0.022 (1D-CNN), 0.870±0.028 (PLS-DA), 0.875±0.033 (PC-LDA), 0.864±0.027 (SVM), and 0.525±0.045 (LR), which were improved to 0.909±0.021 (1D-CNN), 0.899±0.022 (PLS-DA), 0.895±0.022 (PC-LDA), 0.901±0.020 (SVM), and 0.897±0.021 (LR) respectively after augmentation of the training dataset (p<0.0001, Wilcoxon test). Paired analyses of 1D-CNN with conventional machine learning approaches showed that 1D-CNN had a 1-3% improvement (p<0.001, Wilcoxon test). Conclusions Data augmentation not only improved the performance of both deep neural networks and conventional machine learning techniques by 2-4%, but also improved the performance of the models on spectra with higher noise or spectral shifting. Convolutional neural networks slightly outperformed conventional machine learning approaches for skin cancer detection by Raman spectroscopy.
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Affiliation(s)
- Jianhua Zhao
- Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
- BC Cancer Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Harvey Lui
- Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
- BC Cancer Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Sunil Kalia
- Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
| | - Tim K. Lee
- Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
- BC Cancer Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Haishan Zeng
- Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
- BC Cancer Research Institute, University of British Columbia, Vancouver, BC, Canada
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10
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Georgiev D, Pedersen SV, Xie R, Fernández-Galiana Á, Stevens MM, Barahona M. RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis. Anal Chem 2024; 96:8492-8500. [PMID: 38747470 PMCID: PMC11140669 DOI: 10.1021/acs.analchem.4c00383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.
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Affiliation(s)
- Dimitar Georgiev
- Department
of Computing & UKRI Centre
for Doctoral Training in AI for Healthcare, Imperial College London, London SW7 2AZ, United
Kingdom
- Department
of Materials, Department of Bioengineering & Institute of Biomedical
Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Simon Vilms Pedersen
- Department
of Materials, Department of Bioengineering & Institute of Biomedical
Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Ruoxiao Xie
- Department
of Materials, Department of Bioengineering & Institute of Biomedical
Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Álvaro Fernández-Galiana
- Department
of Materials, Department of Bioengineering & Institute of Biomedical
Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Molly M. Stevens
- Department
of Materials, Department of Bioengineering & Institute of Biomedical
Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Mauricio Barahona
- Department
of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
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11
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Vališ J, Fousková M, Janstová D, Habartová L, Petrtýl J, Petruželka L, Synytsya A, Setnička V. Automated classification pipeline for real-time in vivo examination of colorectal tissue using Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 313:124152. [PMID: 38503254 DOI: 10.1016/j.saa.2024.124152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/07/2024] [Accepted: 03/11/2024] [Indexed: 03/21/2024]
Abstract
Colorectal cancer is the third most common malignancy worldwide and one of the leading causes of death in oncological patients with its diagnosis typically involving confirmation by tissue biopsy. In vivo Raman spectroscopy, an experimental diagnostic method less invasive than a biopsy, has shown great potential to discriminate between normal and cancerous tissue. However, the complex and often manual processing of Raman spectra along with the absence of a suitable instant classifier are the main obstacles to its adoption in clinical practice. This study aims to address these issues by developing a real-time automated classification pipeline coupled with a user-friendly application tailored for non-spectroscopists. First, in addition to routine colonoscopy, 377 subjects underwent in vivo acquisitions of Raman spectra of healthy tissue, adenomatous polyps, or cancerous tissue, which were conducted using a custom-made microprobe. The spectra were then loaded into the pipeline and pre-processed in several steps, including standard normal variate transformation and finite impulse response filtration. The quality of the pre-processed spectral data was checked based on their signal-to-noise ratio before the suitable spectra were decomposed and classified using a combination of principal component analysis and a support vector machine, respectively. After five-fold cross-validation, the developed classifier exhibited 100% sensitivity toward adenocarcinoma and adenomatous polyps. The overall accuracy was 96.9% and 79.2% for adenocarcinoma and adenomatous polyps respectively. In addition, an application with a graphical user interface was developed to facilitate the use of our data pipeline by medical professionals in a clinical environment. Overall, the combination of supervised and unsupervised machine learning with algorithmic pre-processing of in vivo Raman spectra appears to be a viable way of reducing the relatively large number of biopsies currently needed to definitively diagnose colorectal cancer.
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Affiliation(s)
- Jan Vališ
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Markéta Fousková
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Daniela Janstová
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Lucie Habartová
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Jaromír Petrtýl
- 4(th) Department of Internal Medicine, General University Hospital in Prague and 1(St) Faculty of Medicine, Charles University in Prague, U Nemocnice 2, 128 08 Prague 2, Czech Republic
| | - Luboš Petruželka
- Department of Oncology, General University Hospital in Prague and 1(St) Faculty of Medicine, Charles University in Prague, U Nemocnice 2, 128 08 Prague 2, Czech Republic
| | - Alla Synytsya
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Vladimír Setnička
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic.
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12
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Burström G, Amini M, El-Hajj VG, Arfan A, Gharios M, Buwaider A, Losch MS, Manni F, Edström E, Elmi-Terander A. Optical Methods for Brain Tumor Detection: A Systematic Review. J Clin Med 2024; 13:2676. [PMID: 38731204 PMCID: PMC11084501 DOI: 10.3390/jcm13092676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 04/28/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.
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Affiliation(s)
- Gustav Burström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Misha Amini
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Victor Gabriel El-Hajj
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Arooj Arfan
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Maria Gharios
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Ali Buwaider
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Merle S. Losch
- Department of Biomechanical Engineering, Faculty of Mechanical Engineering, Delft University of Technology, 2627 Delft, The Netherlands
| | - Francesca Manni
- Department of Electrical Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands;
| | - Erik Edström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
| | - Adrian Elmi-Terander
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
- Department of Surgical Sciences, Uppsala University, 751 35 Uppsala, Sweden
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13
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Monteagudo Honrubia M, Caposciutti G, Herraiz-Martínez FJ, Matanza Domingo J, Tellini B, Giannetti R. Measuring Sedimentation Profiles for Nanoparticle Characterization through a Square Spiral Resonator Sensor. SENSORS (BASEL, SWITZERLAND) 2024; 24:2735. [PMID: 38732845 PMCID: PMC11086076 DOI: 10.3390/s24092735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/15/2024] [Accepted: 04/22/2024] [Indexed: 05/13/2024]
Abstract
Metallic nanoscale particles attract a growing interest in several fields, thanks to their unique bonding characteristics; applications are appearing in the literature in the fields of, for example, sensor coatings and biochemical compound detection. However, the controlled fabrication of such nanopowders is often cumbersome, especially because their characterization is normally slow, involving procedures such as electron microscopy. On the other hand, microwave sensors based on near-field effects on materials are being developed with high sensitivity and show promising characteristics. In this paper, the authors show how a microwave sensor based on a Square Spiral Resonator can be used to characterize paraffin dispersions of nanoparticles conveniently and cost-effectively.
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Affiliation(s)
- Miguel Monteagudo Honrubia
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (M.M.H.); (F.J.H.-M.); (J.M.D.)
| | - Gianluca Caposciutti
- Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy; (G.C.); (B.T.)
| | - Francisco Javier Herraiz-Martínez
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (M.M.H.); (F.J.H.-M.); (J.M.D.)
| | - Javier Matanza Domingo
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (M.M.H.); (F.J.H.-M.); (J.M.D.)
| | - Bernardo Tellini
- Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy; (G.C.); (B.T.)
| | - Romano Giannetti
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (M.M.H.); (F.J.H.-M.); (J.M.D.)
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14
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Ilchenko O, Pilhun Y, Kutsyk A, Slobodianiuk D, Goksel Y, Dumont E, Vaut L, Mazzoni C, Morelli L, Boisen S, Stergiou K, Aulin Y, Rindzevicius T, Andersen TE, Lassen M, Mundhada H, Jendresen CB, Philipsen PA, Hædersdal M, Boisen A. Optics miniaturization strategy for demanding Raman spectroscopy applications. Nat Commun 2024; 15:3049. [PMID: 38589380 PMCID: PMC11001912 DOI: 10.1038/s41467-024-47044-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 03/12/2024] [Indexed: 04/10/2024] Open
Abstract
Raman spectroscopy provides non-destructive, label-free quantitative studies of chemical compositions at the microscale as used on NASA's Perseverance rover on Mars. Such capabilities come at the cost of high requirements for instrumentation. Here we present a centimeter-scale miniaturization of a Raman spectrometer using cheap non-stabilized laser diodes, densely packed optics, and non-cooled small sensors. The performance is comparable with expensive bulky research-grade Raman systems. It has excellent sensitivity, low power consumption, perfect wavenumber, intensity calibration, and 7 cm-1 resolution within the 400-4000 cm-1 range using a built-in reference. High performance and versatility are demonstrated in use cases including quantification of methanol in beverages, in-vivo Raman measurements of human skin, fermentation monitoring, chemical Raman mapping at sub-micrometer resolution, quantitative SERS mapping of the anti-cancer drug methotrexate and in-vitro bacteria identification. We foresee that the miniaturization will allow realization of super-compact Raman spectrometers for integration in smartphones and medical devices, democratizing Raman technology.
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Affiliation(s)
- Oleksii Ilchenko
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark.
- Lightnovo ApS, Birkerød, Denmark.
| | - Yurii Pilhun
- Lightnovo ApS, Birkerød, Denmark
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Andrii Kutsyk
- Lightnovo ApS, Birkerød, Denmark
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
- Technical University of Denmark, Department of Energy Conversion and Storage, Kgs. Lyngby, Denmark
| | - Denys Slobodianiuk
- Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
- Institute of Magnetism, Kyiv, Ukraine
| | - Yaman Goksel
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Elodie Dumont
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Lukas Vaut
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Chiara Mazzoni
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Lidia Morelli
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | | | | | | | - Tomas Rindzevicius
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
| | - Thomas Emil Andersen
- Department of Clinical Microbiology, Odense University Hospital and Research Unit of Clinical Microbiology, University of Southern Denmark, Odense, Denmark
| | | | | | | | | | - Merete Hædersdal
- Department of Dermatology, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Copenhagen University, Copenhagen, Denmark
| | - Anja Boisen
- Technical University of Denmark, Department of Health Technology, Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Kgs. Lyngby, Denmark
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15
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Medrano-Lopez JA, Villalpando I, Salazar MI, Torres-Torres C. Hierarchical Nanobiosensors at the End of the SARS-CoV-2 Pandemic. BIOSENSORS 2024; 14:108. [PMID: 38392027 PMCID: PMC10887370 DOI: 10.3390/bios14020108] [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] [Received: 12/24/2023] [Revised: 02/09/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
Nanostructures have played a key role in the development of different techniques to attack severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Some applications include masks, vaccines, and biosensors. The latter are of great interest for detecting diseases since some of their features allowed us to find specific markers in secretion samples such as saliva, blood, and even tears. Herein, we highlight how hierarchical nanoparticles integrated into two or more low-dimensional materials present outstanding advantages that are attractive for photonic biosensing using their nanoscale functions. The potential of nanohybrids with their superlative mechanical characteristics together with their optical and optoelectronic properties is discussed. The progress in the scientific research focused on using nanoparticles for biosensing a variety of viruses has become a medical milestone in recent years, and has laid the groundwork for future disease treatments. This perspective analyzes the crucial information about the use of hierarchical nanostructures in biosensing for the prevention, treatment, and mitigation of SARS-CoV-2 effects.
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Affiliation(s)
- Jael Abigail Medrano-Lopez
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Ingeniería y Eléctrica, Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Isaela Villalpando
- Centro de Investigación para los Recursos Naturales, Salaices 33941, Mexico
| | - Ma Isabel Salazar
- Departamento de Microbiología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City 11340, Mexico
| | - Carlos Torres-Torres
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Ingeniería y Eléctrica, Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City 07738, Mexico
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16
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Espinosa-Garavito AC, Quiroz EN, Galán-Freyle NJ, Aroca-Martinez G, Hernández-Rivera SP, Villa-Medina J, Méndez-López M, Gomez-Escorcia L, Acosta-Hoyos A, Pacheco-Lugo L, Espitia-Almeida F, Pacheco-Londoño LC. Surface-enhanced Raman Spectroscopy in urinalysis of hypertension patients with kidney disease. Sci Rep 2024; 14:3035. [PMID: 38321263 PMCID: PMC10847430 DOI: 10.1038/s41598-024-53679-9] [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: 08/28/2023] [Accepted: 02/03/2024] [Indexed: 02/08/2024] Open
Abstract
Arterial hypertension (AH) is a multifactorial and asymptomatic disease that affects vital organs such as the kidneys and heart. Considering its prevalence and the associated severe health repercussions, hypertension has become a disease of great relevance for public health across the globe. Conventionally, the classification of an individual as hypertensive or non-hypertensive is conducted through ambulatory blood pressure monitoring over a 24-h period. Although this method provides a reliable diagnosis, it has notable limitations, such as additional costs, intolerance experienced by some patients, and interferences derived from physical activities. Moreover, some patients with significant renal impairment may not present proteinuria. Accordingly, alternative methodologies are applied for the classification of individuals as hypertensive or non-hypertensive, such as the detection of metabolites in urine samples through liquid chromatography or mass spectrometry. However, the high cost of these techniques limits their applicability for clinical use. Consequently, an alternative methodology was developed for the detection of molecular patterns in urine collected from hypertension patients. This study generated a direct discrimination model for hypertensive and non-hypertensive individuals through the amplification of Raman signals in urine samples based on gold nanoparticles and supported by chemometric techniques such as partial least squares-discriminant analysis (PLS-DA). Specifically, 162 patient urine samples were used to create a PLS-DA model. These samples included 87 urine samples from patients diagnosed with hypertension and 75 samples from non-hypertensive volunteers. In the AH group, 35 patients were diagnosed with kidney damage and were further classified into a subgroup termed (RAH). The PLS-DA model with 4 latent variables (LV) was used to classify the hypertensive patients with external validation prediction (P) sensitivity of 86.4%, P specificity of 77.8%, and P accuracy of 82.5%. This study demonstrates the ability of surface-enhanced Raman spectroscopy to differentiate between hypertensive and non-hypertensive patients through urine samples, representing a significant advance in the detection and management of AH. Additionally, the same model was then used to discriminate only patients diagnosed with renal damage and controls with a P sensitivity of 100%, P specificity of 77.8%, and P accuracy of 82.5%.
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Affiliation(s)
- Alberto C Espinosa-Garavito
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | - Elkin Navarro Quiroz
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | - Nataly J Galán-Freyle
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | | | - Samuel P Hernández-Rivera
- Center for Chemical Sensors, DHS SENTRY COE, University of Puerto Rico-Mayaguez, Mayaguez, PR, 00681, USA
| | - Joe Villa-Medina
- Center of Pharmaceutical Research, Procaps Laboratories, 080002, Barranquilla, Colombia
| | - Maximiliano Méndez-López
- Grupo de Química y Biología, Departamento de Química y Biología, Universidad del Norte, Km 5 Vía Puerto Colombia, 080001, Barranquilla, Colombia
| | | | - Antonio Acosta-Hoyos
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | - Lisandro Pacheco-Lugo
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | - Fabián Espitia-Almeida
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia
| | - Leonardo C Pacheco-Londoño
- Centro de Investigaciones en Ciencias de la Vida, Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, 080002, Barranquilla, Atlántico, Colombia.
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17
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Zhang S, Wu SQY, Hum M, Perumal J, Tan EY, Lee ASG, Teng J, Dinish US, Olivo M. Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis. RSC Adv 2024; 14:3599-3610. [PMID: 38264270 PMCID: PMC10804230 DOI: 10.1039/d3ra05723b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/17/2023] [Indexed: 01/25/2024] Open
Abstract
Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.
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Affiliation(s)
- Shuyan Zhang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Steve Qing Yang Wu
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Melissa Hum
- Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore (NCCS) 30 Hospital Boulevard Singapore 168583 Republic of Singapore
| | - Jayakumar Perumal
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Ern Yu Tan
- Breast & Endocrine Surgery, Tan Tock Seng Hospital (TTSH) 11 Jln Tan Tock Seng Singapore 308433 Republic of Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Republic of Singapore
| | - Ann Siew Gek Lee
- Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore (NCCS) 30 Hospital Boulevard Singapore 168583 Republic of Singapore
- SingHealth Duke-NUS Oncology Academic Clinical Programme (ONCO ACP), Duke-NUS Medical School Singapore 169857 Republic of Singapore
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore Singapore 117593 Republic of Singapore
| | - Jinghua Teng
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - U S Dinish
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Malini Olivo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
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18
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Huang Q, Gong H, Wang G, Hu W, Wang W, Pan S, Xu J, Liu G, Tian Z. Positively Charged Silver and Gold Nanoparticles with Controllable Size Distribution for SERS Detection of Negatively Charged Molecules. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:1305-1315. [PMID: 38164750 DOI: 10.1021/acs.langmuir.3c02846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has been demonstrated as an ultrasensitive tool for various molecules. However, for the negatively charged molecules, the widely used SERS substrate [negatively charged Ag and Au nanoparticles (Ag or Au NPs (-)] showed either low sensitivity or poor stability. The best solution is to synthesize positively charged silver or gold nanoparticles [Ag or Au NPs (+)] with high stability and excellent SERS performance, which are currently unavailable. To this end, we revitalized the strategy of "charge reversal and seed growth". By selection of ascorbic acid as the reductant and surfactant, the surface charge of Ag or Au NP (-) seeds is adjusted to a balanced state, where the surface charge is negative enough to satisfy the stabilization of the NPs (-) but does not hinder the subsequent charge reversal. By optimization of the chain length and electric charge of polyamine molecules, the highly stable and size-controllable uniform Ag NPs (+) and Au NPs (+) were seed-growth synthesized with high reproducibility. More importantly, the SERS performance of both Ag NPs (+) and Au NPs (+) achieved the trace detection of negatively charged molecules at the level of 1 μg/L, demonstrating an improved SERS sensitivity of up to 3 orders of magnitude compared to the previously reported sensitivity. Promisingly, the introduction of polyamine-capped Ag NPs (+) and Au NPs (+) as SERS substrates with high stability (1 year shelf life) will significantly broaden the application of SERS.
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Affiliation(s)
- Qiuting Huang
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Hongbo Gong
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Guoqiang Wang
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Weiye Hu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Weili Wang
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Siqi Pan
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Jing Xu
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Guokun Liu
- State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
| | - Zhongqun Tian
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
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Acri G, Testagrossa B, Lucanto MC, Cristadoro S, Pellegrino S, Ruello E, Costa S. Raman Spectroscopy and Cystic Fibrosis Disease: An Alternative Potential Tool for Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Modulator Response Differentiation-A Pilot Study Based on Serum Samples. Molecules 2024; 29:433. [PMID: 38257346 PMCID: PMC10818724 DOI: 10.3390/molecules29020433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/06/2024] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Cystic fibrosis (CF) is a genetic disorder that alters chloride transport in mucous membranes. Recent studies have demonstrated that treatment with modulators of the chloride channel reduces inflammatory markers, restoring, among others, the imbalance of lipids. In this study, we analyzed the serum samples of treated and non-treated patients with modulators with Raman spectroscopy. Nineteen (eight treated an eleven non-treated) patients were considered. The main difference between the two groups appeared in the 3020-2800 cm-1 range. A Voigt deconvolution fit was performed, and nine sub-bands were identified. To distinguish between treated and non-treated patients, the area ratio between the CH3 and CH2 vibration modes was calculated for each patient. The results were validated using statistical analyses. In particular, receiver operating characteristic (ROC) curves and Youden index (Y) were calculated (Area Under Curve (AUC): 0.977; Y: 3.30). An ROC curve represents the performance of the classification, illustrating the diagnostic ability of Raman spectroscopy. It was demonstrated that Raman spectroscopy is able to highlight peculiar differences between elexacaftor/tezacaftor/ivacaftor (ETI)-treated and non-treated patients, in relation with lipids biomarkers.
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Affiliation(s)
- Giuseppe Acri
- Dipartimento di Scienze Biomediche, Odontoiatriche, e delle Immagini Morfologiche e Funzionali, Università degli Studi di Messina, 98125 Messina, Italy; (G.A.); (E.R.)
| | - Barbara Testagrossa
- Dipartimento di Scienze Biomediche, Odontoiatriche, e delle Immagini Morfologiche e Funzionali, Università degli Studi di Messina, 98125 Messina, Italy; (G.A.); (E.R.)
| | - Maria Cristina Lucanto
- Unità Operativa Semplice Dipartimentale Gastroenterologia Pediatrica e Fibrosi Cistica, Azienda, Ospedaliera Universitaria Policlinico G. Martino, Via Consolare Valeria, 98125 Messina, Italy; (M.C.L.); (S.C.); (S.P.); (S.C.)
| | - Simona Cristadoro
- Unità Operativa Semplice Dipartimentale Gastroenterologia Pediatrica e Fibrosi Cistica, Azienda, Ospedaliera Universitaria Policlinico G. Martino, Via Consolare Valeria, 98125 Messina, Italy; (M.C.L.); (S.C.); (S.P.); (S.C.)
| | - Salvatore Pellegrino
- Unità Operativa Semplice Dipartimentale Gastroenterologia Pediatrica e Fibrosi Cistica, Azienda, Ospedaliera Universitaria Policlinico G. Martino, Via Consolare Valeria, 98125 Messina, Italy; (M.C.L.); (S.C.); (S.P.); (S.C.)
| | - Elisa Ruello
- Dipartimento di Scienze Biomediche, Odontoiatriche, e delle Immagini Morfologiche e Funzionali, Università degli Studi di Messina, 98125 Messina, Italy; (G.A.); (E.R.)
| | - Stefano Costa
- Unità Operativa Semplice Dipartimentale Gastroenterologia Pediatrica e Fibrosi Cistica, Azienda, Ospedaliera Universitaria Policlinico G. Martino, Via Consolare Valeria, 98125 Messina, Italy; (M.C.L.); (S.C.); (S.P.); (S.C.)
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20
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Budiman A, Wardhana YW, Ainurofiq A, Nugraha YP, Qaivani R, Hakim SNAL, Aulifa DL. Drug-Coformer Loaded-Mesoporous Silica Nanoparticles: A Review of the Preparation, Characterization, and Mechanism of Drug Release. Int J Nanomedicine 2024; 19:281-305. [PMID: 38229702 PMCID: PMC10790662 DOI: 10.2147/ijn.s449159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/19/2023] [Indexed: 01/18/2024] Open
Abstract
Drug-coformer systems, such as coamorphous and cocrystal, are gaining recognition as highly effective strategies for enhancing the stability, solubility, and dissolution of drugs. These systems depend on the interactions between drug and coformer to prevent the conversion of amorphous drugs into the crystalline form and improve the solubility. Furthermore, mesoporous silica (MPS) is also a promising carrier commonly used for stabilization, leading to solubility improvement of poorly water-soluble drugs. The surface interaction of drug-MPS and the nanoconfinement effect prevent amorphous drugs from crystallizing. A novel method has been developed recently, which entails the loading of drug-coformer into MPS to improve the solubility, dissolution, and physical stability of the amorphous drug. This method uses the synergistic effects of drug-coformer interactions and the nanoconfinement effect within MPS. Several studies have reported successful incorporation of drug-coformer into MPS, indicating the potential for significant improvement in dissolution characteristics and physical stability of the drug. Therefore, this study aimed to discuss the preparation and characterization of drug-coformer within MPS, particularly the interaction in the nanoconfinement, as well as the impact on drug release and physical stability.
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Affiliation(s)
- Arif Budiman
- Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, West Java45363, Indonesia
| | - Yoga Windhu Wardhana
- Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, West Java45363, Indonesia
| | - Ahmad Ainurofiq
- Pharmaceutical Technology and Drug Delivery, Department of Pharmacy, Universitas Sebelas Maret, Surakarta, Central Java, 57126, Indonesia
| | - Yuda Prasetya Nugraha
- School of Pharmacy, Bandung Institute of Technology, Bandung, West Java, 40132, Indonesia
| | - Ridhatul Qaivani
- Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, West Java, 45363, Indonesia
| | - Siti Nazila Awaliyyah Lukmanul Hakim
- Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, West Java, 45363, Indonesia
| | - Diah Lia Aulifa
- Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, West Java, 45363, Indonesia
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21
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Tipatet K, Du Boulay I, Muir H, Davison-Gates L, Ellederová Z, Downes A. Raman spectroscopy of brain and skin tissue in a minipig model of Huntington's disease. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:253-261. [PMID: 38108410 DOI: 10.1039/d3ay00970j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
We applied Raman spectroscopy to brain and skin tissues from a minipig model of Huntington's disease. Differences were observed between measured spectra of tissues with and without Huntington's disease, for both brain tissue and skin tissue. There are linked to changes in the chemical composition between tissue types. Using machine learning we correctly classified 96% of test spectra as diseased or wild type, indicating that the test would have a similar accuracy when used as a diagnostic tool for the disease. This suggests the technique has great potential in the rapid and accurate diagnosis of Huntington's and other neurodegenerative diseases in a clinical setting.
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Affiliation(s)
- Kevin Tipatet
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Isla Du Boulay
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Hamish Muir
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Liam Davison-Gates
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Zdenka Ellederová
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
- Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Rumburská 89, 277 21 Liběchov, UK
| | - Andrew Downes
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
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22
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Abidi SMS, Sharma C, Randhawa S, Shukla AK, Acharya A. A review on nanotechnological perspective of "the amyloid cascade hypothesis" for neurodegenerative diseases. Int J Biol Macromol 2023; 253:126821. [PMID: 37690655 DOI: 10.1016/j.ijbiomac.2023.126821] [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: 08/02/2023] [Revised: 09/03/2023] [Accepted: 09/07/2023] [Indexed: 09/12/2023]
Abstract
Neurodegenerative diseases (NDs) are characterized by progressive degeneration of neurons which deteriorates the brain functions. An early detection of the onset of NDs is utmost important, as it will provide the fast treatment strategies to prevent further progression of the disease. Conventionally, accurate diagnosis of the brain related disorders is difficult in their early phase. To solve this problem, nanotechnology based neurofunctional imaging and biomarker detection techniques have been developed which allows high specificity and sensitivity towards screening and diagnosis of NDs. Another challenge to treat the brain related disorders is to overcome the complex integrity of blood-brain-barrier (BBB) for the delivery of theranostic agents. Fortunately, utilization of nanomaterials has been pursued as promising strategy to address this challenge. Herein, we critically highlighted the recent improvements in the field of neurodiagnostic and therapeutic approaches involving innovative strategies for diagnosis, and inhibition of protein aggregates. We have provided particular emphasis on the use of nanotechnology which can push forward the blooming research growth in this field to win the battle against devastating NDs.
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Affiliation(s)
- Syed M S Abidi
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. 176061, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Chandni Sharma
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. 176061, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Shiwani Randhawa
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. 176061, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Ashish K Shukla
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. 176061, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Amitabha Acharya
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. 176061, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India.
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23
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Bassler MC, Knoblich M, Gerhard-Hartmann E, Mukherjee A, Youssef A, Hagen R, Haug L, Goncalves M, Scherzad A, Stöth M, Ostertag E, Steinke M, Brecht M, Hackenberg S, Meyer TJ. Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis. Diagnostics (Basel) 2023; 14:92. [PMID: 38201401 PMCID: PMC10795677 DOI: 10.3390/diagnostics14010092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/10/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
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Affiliation(s)
- Miriam C. Bassler
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Mona Knoblich
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Elena Gerhard-Hartmann
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Ashutosh Mukherjee
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Almoatazbellah Youssef
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Rudolf Hagen
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Lukas Haug
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Miguel Goncalves
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Agmal Scherzad
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Manuel Stöth
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Edwin Ostertag
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
| | - Maria Steinke
- Chair of Tissue Engineering and Regenerative Medicine, University Hospital Würzburg, Röntgenring 11, 97070 Würzburg, Germany;
- Fraunhofer Institute for Silicate Research ISC, Röntgenring 11, 97070 Würzburg, Germany
| | - Marc Brecht
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Stephan Hackenberg
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Till Jasper Meyer
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
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24
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Chiang CC, Huang SJ, Immanuel PN, Lan JH, Lo FY, Young KC. Using a 3D Silicon Micro-Channel Device and Raman Spectroscopy for the Analysis of Whole Blood and Abnormal Blood. MICROMACHINES 2023; 15:21. [PMID: 38258140 PMCID: PMC10819504 DOI: 10.3390/mi15010021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 11/23/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024]
Abstract
Blood testing is a crucial application in the field of clinical studies for disease diagnosis and screening, biomarker discovery, organ function assessment, and the personalization of medication. Therefore, it is of the utmost importance to collect precise data in a short time. In this study, we utilized Raman spectroscopy to analyze blood samples for the extraction of comprehensive biological information, including the primary components and compositions present in the blood. Short-wavelength (532 nm green light) Raman scattering spectroscopy was applied for the analysis of the blood samples, plasma, and serum for detection of the biological characteristics in each sample type. Our results indicated that the whole blood had a high hemoglobin content, which suggests that hemoglobin is a major component of blood. The characteristic Raman peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562-1649 cm-1. Analysis of the plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm-1. This novel 3D silicon micro-channel device technology holds immense potential in the field of medical blood testing. It can serve as the basis for the detection of various diseases and biomarkers, providing real-time data to help medical professionals and patients better understand their health conditions. Changes in biological data collected in this manner could potentially be used for clinical diagnosis.
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Affiliation(s)
- Chao-Ching Chiang
- Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan; (C.-C.C.); (P.N.I.); (J.-H.L.)
| | - Song-Jeng Huang
- Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan; (C.-C.C.); (P.N.I.); (J.-H.L.)
| | - Philip Nathaniel Immanuel
- Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan; (C.-C.C.); (P.N.I.); (J.-H.L.)
| | - Jun-Han Lan
- Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan; (C.-C.C.); (P.N.I.); (J.-H.L.)
| | - Fang-Yuh Lo
- Department of Physics, National Taiwan Normal University, Taipei 10611, Taiwan;
| | - Kung-Chia Young
- Department of Medical Laboratory Science and Biotechnology, National Cheng Kung University, Tainan 70101, Taiwan
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25
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Olbrich K, Setkowicz Z, Kawon K, Czyzycki M, Janik-Olchawa N, Carlomagno I, Aquilanti G, Chwiej J. Vibrational spectroscopy methods for investigation of the animal models of glioblastoma multiforme. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 303:123230. [PMID: 37586277 DOI: 10.1016/j.saa.2023.123230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 06/26/2023] [Accepted: 08/01/2023] [Indexed: 08/18/2023]
Abstract
Glioblastoma multiforme (GBM) is the most common and devastating primary brain tumor among adults. It is highly lethal disease, as only 25% of patients survive longer than 1 year and only 5% more than 5 years from the diagnosis. To search for the new, more effective methods of treatment, the understanding of mechanisms underlying the process of tumorigenesis is needed. The new light on this problem may be shed by the analysis of biochemical anomalies of tissues affected by tumor growth. Therefore, in the present work, we applied the Fourier transform infrared (FTIR) and Raman microspectroscopy to evaluate changes in the distribution and structure of biomolecules appearing in the rat brain as a result of glioblastoma development. In turn, synchrotron X-ray fluorescence microscopy was utilized to determine the elemental anomalies appearing in the nervous tissue. To achieve the assumed goals of the study animal models of GBM were used. The rats were subjected to the intracranial implantation of glioma cells with different degree of invasiveness. For spectroscopic investigation brain slices taken from the area of cancer cells administration were used. The obtained results revealed, among others, the decrease content of lipids and compounds containing carbonyl groups, compositional and structural changes of proteins as well as abnormalities in the distribution of low atomic number elements within the region of tumor.
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Affiliation(s)
- Karolina Olbrich
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Zuzanna Setkowicz
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | - Kamil Kawon
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Mateusz Czyzycki
- Institute for Photon Science and Synchrotron Radiation, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Natalia Janik-Olchawa
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | | | | | - Joanna Chwiej
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland.
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Mostafapour S, Dörfer T, Heinke R, Rösch P, Popp J, Bocklitz T. Investigating the effect of different pre-treatment methods on Raman spectra recorded with different excitation wavelengths. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 302:123100. [PMID: 37437460 DOI: 10.1016/j.saa.2023.123100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/23/2023] [Accepted: 06/30/2023] [Indexed: 07/14/2023]
Abstract
Raman reference libraries can be used for identification of components in unknown samples as Raman spectroscopy offers fingerprint information of the measured samples. Since Raman libraries often contain many different and/or highly similar spectra, it is important that the spectra are a reliable fingerprint for each compound. However, Raman spectra are highly sensitive to the experimental conditions, and the Raman spectra will change in different conditions even though the same sample is measured. Raman data pre-treatment minimizes the differences between Raman spectra arising from different experimental conditions. In this study, different combinations of pre-treatment methods are used to quantify the effect of each pre-treatment step in minimizing the differences between Raman spectra of the same sample in different experimental conditions, e.g., different excitation wavelengths. These different pre-treatment processes are evaluated for six solvents. The spectra differences between spectra recorded with three excitation wavelengths (532 nm, 633 nm, and 830 nm) are evaluated by angular difference index and the influence on a classification model is tested. The angular difference index of each spectrum after every data pre-treatment step shows a decreasing behavior. It could be demonstrated that wavenumber calibration has the largest effect on the differences between the Raman spectra. However, ω4 correction doesn't have a significate effect in this dataset. The classification results show that the prediction accuracy is improving by doing data pre-treatment. In the dataset obtained in 633 nm a lower amount of pre-treatment steps is needed but in the dataset 830 nm more pre-treatment steps are needed for a high accuracy. The result shows that the choice of an optimal pre-treatment method or combination of methods strongly influences the analysis results, but is far from straightforward, since it depends on the characteristics of the data set and the goal of data analysis.
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Affiliation(s)
- Sara Mostafapour
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert‑Einstein‑Straße 9, 07745 Jena, Germany; Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Dörfer
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany
| | - Ralf Heinke
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert‑Einstein‑Straße 9, 07745 Jena, Germany; Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert‑Einstein‑Straße 9, 07745 Jena, Germany; Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany; Institute of Computer Science, Faculty of Mathematics, Physics & Computer Science, University Bayreuth Universitätsstraße 30, 95447 Bayreuth.
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27
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Szymoński K, Skirlińska-Nosek K, Lipiec E, Sofińska K, Czaja M, Wilkosz N, Krupa M, Wanat F, Ulatowska-Białas M, Adamek D. Combined analytical approach empowers precise spectroscopic interpretation of subcellular components of pancreatic cancer cells. Anal Bioanal Chem 2023; 415:7281-7295. [PMID: 37906289 PMCID: PMC10684650 DOI: 10.1007/s00216-023-04997-w] [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: 09/04/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 11/02/2023]
Abstract
The lack of specific and sensitive early diagnostic options for pancreatic cancer (PC) results in patients being largely diagnosed with late-stage disease, thus inoperable and burdened with high mortality. Molecular spectroscopic methodologies, such as Raman or infrared spectroscopies, show promise in becoming a leader in screening for early-stage cancer diseases, including PC. However, should such technology be introduced, the identification of differentiating spectral features between various cancer types is required. This would not be possible without the precise extraction of spectra without the contamination by necrosis, inflammation, desmoplasia, or extracellular fluids such as mucous that surround tumor cells. Moreover, an efficient methodology for their interpretation has not been well defined. In this study, we compared different methods of spectral analysis to find the best for investigating the biomolecular composition of PC cells cytoplasm and nuclei separately. Sixteen PC tissue samples of main PC subtypes (ductal adenocarcinoma, intraductal papillary mucinous carcinoma, and ampulla of Vater carcinoma) were collected with Raman hyperspectral mapping, resulting in 191,355 Raman spectra and analyzed with comparative methodologies, specifically, hierarchical cluster analysis, non-negative matrix factorization, T-distributed stochastic neighbor embedding, principal components analysis (PCA), and convolutional neural networks (CNN). As a result, we propose an innovative approach to spectra classification by CNN, combined with PCA for molecular characterization. The CNN-based spectra classification achieved over 98% successful validation rate. Subsequent analyses of spectral features revealed differences among PC subtypes and between the cytoplasm and nuclei of their cells. Our study establishes an optimal methodology for cancer tissue spectral data classification and interpretation that allows precise and cognitive studies of cancer cells and their subcellular components, without mixing the results with cancer-surrounding tissue. As a proof of concept, we describe findings that add to the spectroscopic understanding of PC.
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Affiliation(s)
- Krzysztof Szymoński
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland.
- Department of Pathomorphology, University Hospital, Kraków, Poland.
| | - Katarzyna Skirlińska-Nosek
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Kraków, Poland
| | - Ewelina Lipiec
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
| | - Kamila Sofińska
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
| | - Michał Czaja
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Kraków, Poland
| | - Natalia Wilkosz
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- AGH University of Krakow, Faculty of Physics and Applied Computer Science, Kraków, Poland
| | - Matylda Krupa
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
| | - Filip Wanat
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
| | - Magdalena Ulatowska-Białas
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
- Department of Pathomorphology, University Hospital, Kraków, Poland
| | - Dariusz Adamek
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
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28
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Xing Y, Li J, Yang J, Li J, Pang W, Martin FL, Xu L. Application of spectrochemical analysis with chemometrics to profile biochemical alterations in nanoplastic-exposed HepG 2 cells. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 336:122309. [PMID: 37543068 DOI: 10.1016/j.envpol.2023.122309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 08/01/2023] [Accepted: 08/03/2023] [Indexed: 08/07/2023]
Abstract
Humans are routinely exposed to nanoplastics (NPs) in various ways, and this exposure presents a significant health risk. Nevertheless, there remain gaps in our knowledge, particularly in the mechanisms of toxicity of NPs with different surface charges at very low environmental concentrations. Herein, a spectrochemical approach was used to profile the cytotoxicity of NPs with different surface charges in HepG2 cells. It was found that all three NPs can cause some biomolecular alterations in cells, affecting cellular lipids, proteins, amino acids, and genetic material. Of these, PS and PS-COOH led to a non-linear dose-response, which may be related to a biphasic dose-response, whereas PS-NH2 led to a linear dose-response with a gradual increase in toxicity with increasing exposure concentration. In addition, the spectroscopic results showed that surface modifications led to cellular biochemical changes and caused adverse biological effects, with PS-NH2 exhibiting higher toxicity compared to PS or PS-COOH along with an inhibition of cell proliferation. Surprisingly PS-COOH, although considered the least toxic NP, appears to cause DNA damage. Overall, the toxic effects of different surface-modified NPs in cells were detected for the first time by applying spectrochemical techniques, and these findings provide important data towards understanding the emerging widespread environmental pollution of NPs and their effects on humans.
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Affiliation(s)
- Yu Xing
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Jing Li
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jingjing Yang
- Department of Biochemistry and Molecular Biology, School of Medicine & Holistic Integrative Medicine, Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Junyi Li
- National University of Singapore (Suzhou) Research Institute, Suzhou, 215128, China
| | - Weiyi Pang
- School of Public Health, Guilin Medical University, Guilin, 541199, China
| | - Francis L Martin
- Biocel Ltd, Hull, HU10 7TS, UK; Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Whinney Heys Road, Blackpool, FY3 8NR, UK
| | - Li Xu
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
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Khristoforova Y, Bratchenko L, Bratchenko I. Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review. Int J Mol Sci 2023; 24:15605. [PMID: 37958586 PMCID: PMC10647591 DOI: 10.3390/ijms242115605] [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: 10/04/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
Raman spectroscopy is a widely developing approach for noninvasive analysis that can provide information on chemical composition and molecular structure. High chemical specificity calls for developing different medical diagnostic applications based on Raman spectroscopy. This review focuses on the Raman-based techniques used in medical diagnostics and provides an overview of such techniques, possible areas of their application, and current limitations. We have reviewed recent studies proposing conventional Raman spectroscopy and surface-enhanced Raman spectroscopy for rapid measuring of specific biomarkers of such diseases as cardiovascular disease, cancer, neurogenerative disease, and coronavirus disease (COVID-19). As a result, we have discovered several most promising Raman-based applications to identify affected persons by detecting some significant spectral features. We have analyzed these approaches in terms of their potentially diagnostic power and highlighted the remaining challenges and limitations preventing their translation into clinical settings.
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Affiliation(s)
| | | | - Ivan Bratchenko
- Department of Laser and Biotechnical Systems, Samara National Research University, 34 Moskovskoye Shosse, Samara 443086, Russia; (Y.K.)
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30
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Vazquez-Osorio N, Castro-Ramos J, Sánchez-Escobar JJ. Matching Pursuit for Denoising Raman Spectra, Based on Genetic Algorithm and Hermite Atoms. APPLIED SPECTROSCOPY 2023; 77:1009-1024. [PMID: 37448352 DOI: 10.1177/00037028231179744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/15/2023]
Abstract
Due to its various advantages, Raman spectroscopy has become a powerful tool in different fields of science and engineering; however, in specific applications, this technique's limiting factor is closely related to the inherent noise of the Raman spectra. To eliminate the noise of a Raman spectrum, preserving its position, intensity, and width characteristic, we propose using a genetic matching pursuit-Hermite atoms (GMP-HAs) algorithm in this work. This algorithm helps recover Raman spectra immersed in Gaussian noise with the least number of atoms. The noise-free Raman signal is reconstructed with the GMP-HAs algorithm, transforming the typical best-matching atom search into an optimization problem. Specifically, we maximize the fitness function, defined as the correlation between current residual and Hermite atoms, with the genetic algorithm MI-LXPM encoded in a real domain and avoiding local maxima, by adding a stopping criterion based on an exponential adjustment according to the algorithm's behavior in the presence of noise. Simulated and biological Raman spectra are used to evaluate the proposed algorithm and compare its performance with typically known methods for denoising, such as the Savitzky- Golay filter (SG) and basis pursuit denoising. Using the signal-to-noise ratio (S/N)metric resulted in a 0.31 dB advantage in the S/N product for the proposed algorithm with respect to SG. Additionally, it is shown that the algorithm uses only 25.3% of the number of atoms needed by the matching pursuit algorithm. The results indicate that the GMP-HAs algorithm has better denoising capabilities, and at the same time, the Raman spectra are decomposed with fewer atoms compared to known sparse algorithms.
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Affiliation(s)
- Noe Vazquez-Osorio
- Coordinación de Óptica, Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico
| | - J Castro-Ramos
- Coordinación de Óptica, Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico
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Guleken Z, Ceylan Z, Aday A, Bayrak AG, Hindilerden İY, Nalçacı M, Jakubczyk P, Jakubczyk D, Kula-Maximenko M, Depciuch J. Detection of primary myelofibrosis in blood serum via Raman spectroscopy assisted by machine learning approaches; correlation with clinical diagnosis. NANOMEDICINE : NANOTECHNOLOGY, BIOLOGY, AND MEDICINE 2023; 53:102706. [PMID: 37633405 DOI: 10.1016/j.nano.2023.102706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 08/19/2023] [Accepted: 08/19/2023] [Indexed: 08/28/2023]
Abstract
Primary myelofibrosis (PM) is one of the myeloproliferative neoplasm, where stem cell-derived clonal neoplasms was noticed. Diagnosis of this disease is based on: physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. However, the molecular marker of PM, which is a mutation in the JAK2V617F gene, was observed also in other myeloproliferative neoplasms such as polycythemia vera and essential thrombocythemia. Therefore, there is a need to find methods that provide a marker unique to PM and allow for higher accuracy of PM diagnosis and consequently the treatment of the disease. Continuing, in this study, we used Raman spectroscopy, Principal Components Analysis (PCA), and Partial Least Squares (PLS) analysis as helpful diagnostic tools for PM. Consequently, we used serum collected from PM patients, which were classified using clinical parameters of PM such as the dynamic international prognostic scoring system (DIPSS) for primary myelofibrosis plus score, the JAK2V617F mutation, spleen size, bone marrow reticulin fibrosis degree and use of hydroxyurea drug features. Raman spectra showed higher amounts of C-H, C-C and C-C/C-N and amide II and lower amounts of amide I and vibrations of CH3 groups in PM patients than in healthy ones. Furthermore, shifts of amides II and I vibrations in PM patients were noticed. Machine learning methods were used to analyze Raman regions: (i) 800 cm-1 and 1800 cm-1, (ii) 1600 cm-1-1700 cm-1, and (iii) 2700 cm-1-3000 cm-1 showed 100 % accuracy, sensitivity, and specificity. Differences in the spectral dynamic showed that differences in the amide II and amide I regions were the most significant in distinguishing between PM and healthy subjects. Importantly, until now, the efficacy of Raman spectroscopy has not been established in clinical diagnostics of PM disease using the correlation between Raman spectra and PM clinical prognostic scoring. Continuing, our results showed the correlation between Raman signals and bone marrow fibrosis, as well as JAKV617F. Consequently, the results revealed that Raman spectroscopy has a high potential for use in medical laboratory diagnostics to quantify multiple biomarkers simultaneously, especially in the selected Raman regions.
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Affiliation(s)
- Zozan Guleken
- Faculty of Medicine, Department of Physiology, Gaziantep Islam Science and Technology University, Gaziantep, Turkey; Faculty of Medicine, Rzeszów University, Rzeszów, Poland.
| | - Zeynep Ceylan
- Samsun University, Faculty of Engineering, Department of Industrial Engineering, Samsun, Turkey
| | - Aynur Aday
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - Ayşe Gül Bayrak
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - İpek Yönal Hindilerden
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | - Meliha Nalçacı
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | | | - Dorota Jakubczyk
- Faculty of Mathematics and Applied Physics, Rzeszow University of Technology, Powstancow Warszawy 12, PL-35959 Rzeszow, Poland
| | - Monika Kula-Maximenko
- Institute of Plant Physiology, Polish Academy of Sciences, Niezapominajek 21, 30-239 Kraków, Poland
| | - Joanna Depciuch
- Institute of Nuclear Physics, PAS, 31342 Krakow, Poland; Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093 Lublin, Poland.
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32
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Stanciu SG, König K, Song YM, Wolf L, Charitidis CA, Bianchini P, Goetz M. Toward next-generation endoscopes integrating biomimetic video systems, nonlinear optical microscopy, and deep learning. BIOPHYSICS REVIEWS 2023; 4:021307. [PMID: 38510341 PMCID: PMC10903409 DOI: 10.1063/5.0133027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 05/26/2023] [Indexed: 03/22/2024]
Abstract
According to the World Health Organization, the proportion of the world's population over 60 years will approximately double by 2050. This progressive increase in the elderly population will lead to a dramatic growth of age-related diseases, resulting in tremendous pressure on the sustainability of healthcare systems globally. In this context, finding more efficient ways to address cancers, a set of diseases whose incidence is correlated with age, is of utmost importance. Prevention of cancers to decrease morbidity relies on the identification of precursor lesions before the onset of the disease, or at least diagnosis at an early stage. In this article, after briefly discussing some of the most prominent endoscopic approaches for gastric cancer diagnostics, we review relevant progress in three emerging technologies that have significant potential to play pivotal roles in next-generation endoscopy systems: biomimetic vision (with special focus on compound eye cameras), non-linear optical microscopies, and Deep Learning. Such systems are urgently needed to enhance the three major steps required for the successful diagnostics of gastrointestinal cancers: detection, characterization, and confirmation of suspicious lesions. In the final part, we discuss challenges that lie en route to translating these technologies to next-generation endoscopes that could enhance gastrointestinal imaging, and depict a possible configuration of a system capable of (i) biomimetic endoscopic vision enabling easier detection of lesions, (ii) label-free in vivo tissue characterization, and (iii) intelligently automated gastrointestinal cancer diagnostic.
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Affiliation(s)
- Stefan G. Stanciu
- Center for Microscopy-Microanalysis and Information Processing, University Politehnica of Bucharest, Bucharest, Romania
| | | | | | - Lior Wolf
- School of Computer Science, Tel Aviv University, Tel-Aviv, Israel
| | - Costas A. Charitidis
- Research Lab of Advanced, Composite, Nano-Materials and Nanotechnology, School of Chemical Engineering, National Technical University of Athens, Athens, Greece
| | - Paolo Bianchini
- Nanoscopy and NIC@IIT, Italian Institute of Technology, Genoa, Italy
| | - Martin Goetz
- Medizinische Klinik IV-Gastroenterologie/Onkologie, Kliniken Böblingen, Klinikverbund Südwest, Böblingen, Germany
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33
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Zhang S, Qi Y, Tan SPH, Bi R, Olivo M. Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review. BIOSENSORS 2023; 13:bios13050557. [PMID: 37232918 DOI: 10.3390/bios13050557] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 05/27/2023]
Abstract
Molecular vibrations play a crucial role in physical chemistry and biochemistry, and Raman and infrared spectroscopy are the two most used techniques for vibrational spectroscopy. These techniques provide unique fingerprints of the molecules in a sample, which can be used to identify the chemical bonds, functional groups, and structures of the molecules. In this review article, recent research and development activities for molecular fingerprint detection using Raman and infrared spectroscopy are discussed, with a focus on identifying specific biomolecules and studying the chemical composition of biological samples for cancer diagnosis applications. The working principle and instrumentation of each technique are also discussed for a better understanding of the analytical versatility of vibrational spectroscopy. Raman spectroscopy is an invaluable tool for studying molecules and their interactions, and its use is likely to continue to grow in the future. Research has demonstrated that Raman spectroscopy is capable of accurately diagnosing various types of cancer, making it a valuable alternative to traditional diagnostic methods such as endoscopy. Infrared spectroscopy can provide complementary information to Raman spectroscopy and detect a wide range of biomolecules at low concentrations, even in complex biological samples. The article concludes with a comparison of the techniques and insights into future directions.
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Affiliation(s)
- Shuyan Zhang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Yi Qi
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Sonia Peng Hwee Tan
- Department of Biomedical Engineering, National University of Singapore (NUS), 4 Engineering Drive 3 Block 4, #04-08, Singapore 117583, Singapore
| | - Renzhe Bi
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Malini Olivo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
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34
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Conti F, D'Acunto M, Caudai C, Colantonio S, Gaeta R, Moroni D, Pascali MA. Raman spectroscopy and topological machine learning for cancer grading. Sci Rep 2023; 13:7282. [PMID: 37142690 PMCID: PMC10160071 DOI: 10.1038/s41598-023-34457-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/30/2023] [Indexed: 05/06/2023] Open
Abstract
In the last decade, Raman Spectroscopy is establishing itself as a highly promising technique for the classification of tumour tissues as it allows to obtain the biochemical maps of the tissues under investigation, making it possible to observe changes among different tissues in terms of biochemical constituents (proteins, lipid structures, DNA, vitamins, and so on). In this paper, we aim to show that techniques emerging from the cross-fertilization of persistent homology and machine learning can support the classification of Raman spectra extracted from cancerous tissues for tumour grading. In more detail, topological features of Raman spectra and machine learning classifiers are trained in combination as an automatic classification pipeline in order to select the best-performing pair. The case study is the grading of chondrosarcoma in four classes: cross and leave-one-patient-out validations have been used to assess the classification accuracy of the method. The binary classification achieves a validation accuracy of 81% and a test accuracy of 90%. Moreover, the test dataset has been collected at a different time and with different equipment. Such results are achieved by a support vector classifier trained with the Betti Curve representation of the topological features extracted from the Raman spectra, and are excellent compared with the existing literature. The added value of such results is that the model for the prediction of the chondrosarcoma grading could easily be implemented in clinical practice, possibly integrated into the acquisition system.
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Affiliation(s)
- Francesco Conti
- Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi 1, Pisa, 56124, Italy.
- Department of Mathematics, University of Pisa, Largo B. Pontecorvo, 56126, Pisa, Italy.
| | - Mario D'Acunto
- Institute of Biophysics, National Research Council of Italy, Via G. Moruzzi 1, 56124, Pisa, Italy
| | - Claudia Caudai
- Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi 1, Pisa, 56124, Italy
| | - Sara Colantonio
- Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi 1, Pisa, 56124, Italy
| | - Raffaele Gaeta
- Division of Surgical Pathology, Department of Surgical, Medical, Molecular Pathology and Critical Area, University of Pisa, Via Paradisa 2, 56124, Pisa, Italy
| | - Davide Moroni
- Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi 1, Pisa, 56124, Italy
| | - Maria Antonietta Pascali
- Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi 1, Pisa, 56124, Italy
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35
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Liu Y, Wu Z, Armstrong DW, Wolosker H, Zheng Y. Detection and analysis of chiral molecules as disease biomarkers. Nat Rev Chem 2023; 7:355-373. [PMID: 37117811 PMCID: PMC10175202 DOI: 10.1038/s41570-023-00476-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2023] [Indexed: 04/30/2023]
Abstract
The chirality of small metabolic molecules is important in controlling physiological processes and indicating the health status of humans. Abnormal enantiomeric ratios of chiral molecules in biofluids and tissues occur in many diseases, including cancers and kidney and brain diseases. Thus, chiral small molecules are promising biomarkers for disease diagnosis, prognosis, adverse drug-effect monitoring, pharmacodynamic studies and personalized medicine. However, it remains difficult to achieve cost-effective and reliable analysis of small chiral molecules in clinical procedures, in part owing to their large variety and low concentration. In this Review, we describe current and emerging techniques that detect and quantify small-molecule enantiomers and their biological importance.
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Affiliation(s)
- Yaoran Liu
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Zilong Wu
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA.
- Texas Materials Institute, The University of Texas at Austin, Austin, TX, USA.
| | - Daniel W Armstrong
- Department of Chemistry & Biochemistry, University of Texas at Arlington, Arlington, TX, USA.
| | - Herman Wolosker
- Department of Biochemistry, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
| | - Yuebing Zheng
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA.
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA.
- Texas Materials Institute, The University of Texas at Austin, Austin, TX, USA.
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
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36
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van Breugel SJ, Low I, Christie ML, Pokorny MR, Nagarajan R, Holtkamp HU, Srinivasa K, Amirapu S, Nieuwoudt MK, Simpson MC, Zargar-Shoshtari K, Aguergaray C. Raman spectroscopy system for real-time diagnosis of clinically significant prostate cancer tissue. JOURNAL OF BIOPHOTONICS 2023; 16:e202200334. [PMID: 36715344 DOI: 10.1002/jbio.202200334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/24/2023] [Accepted: 01/25/2023] [Indexed: 05/17/2023]
Abstract
Prostate cancer (PCa) is a significant healthcare problem worldwide. Current diagnosis and treatment methods are limited by a lack of precise in vivo tissue analysis methods. Real-time cancer identification and grading could dramatically improve current protocols. Here, we report the testing of a thin optical probe using Raman spectroscopy (RS) and classification methods to detect and grade PCa accurately in real-time. We present the first clinical trial on fresh ex vivo biopsy cores from an 84 patient cohort. Findings from 2395 spectra measured on 599 biopsy cores show high accuracy for diagnosing and grading PCa. We can detect clinically significant PCa from benign and clinically insignificant PCa with 90% sensitivity and 80.2% specificity. We also demonstrate the ability to differentiate cancer grades with 90% sensitivity and specificity ≥82.8%. This work demonstrates the utility of RS for real-time PCa detection and grading during routine transrectal biopsy appointments.
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Affiliation(s)
- Suse J van Breugel
- The Photon Factory, University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, University of Auckland, Auckland, New Zealand
- The Dodd-Walls Centre for Photonic and Quantum Technologies, University of Otago, Dunedin, New Zealand
| | - Irene Low
- Counties Manukau District Healthboard, Auckland, New Zealand
| | - Mary L Christie
- Counties Manukau District Healthboard, Auckland, New Zealand
| | - Morgan R Pokorny
- Counties Manukau District Healthboard, Auckland, New Zealand
- Auckland District Healthboard, Auckland, New Zealand
| | - Ramya Nagarajan
- Counties Manukau District Healthboard, Auckland, New Zealand
- Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Hannah U Holtkamp
- The Photon Factory, University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, University of Auckland, Auckland, New Zealand
| | - Komal Srinivasa
- Auckland District Healthboard, Auckland, New Zealand
- Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Satya Amirapu
- Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Michel K Nieuwoudt
- The Photon Factory, University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, University of Auckland, Auckland, New Zealand
- The Dodd-Walls Centre for Photonic and Quantum Technologies, University of Otago, Dunedin, New Zealand
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, Victoria University of Wellington, Wellington, New Zealand
| | - M Cather Simpson
- The Photon Factory, University of Auckland, Auckland, New Zealand
- School of Chemical Sciences, University of Auckland, Auckland, New Zealand
- The Dodd-Walls Centre for Photonic and Quantum Technologies, University of Otago, Dunedin, New Zealand
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, Victoria University of Wellington, Wellington, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
| | - Kamran Zargar-Shoshtari
- Counties Manukau District Healthboard, Auckland, New Zealand
- Auckland District Healthboard, Auckland, New Zealand
- Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Claude Aguergaray
- The Photon Factory, University of Auckland, Auckland, New Zealand
- The Dodd-Walls Centre for Photonic and Quantum Technologies, University of Otago, Dunedin, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
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37
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Colniță A, Toma VA, Brezeștean IA, Tahir MA, Dina NE. A Review on Integrated ZnO-Based SERS Biosensors and Their Potential in Detecting Biomarkers of Neurodegenerative Diseases. BIOSENSORS 2023; 13:bios13050499. [PMID: 37232860 DOI: 10.3390/bios13050499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/15/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) applications in clinical diagnosis and spectral pathology are increasing due to the potential of the technique to bio-barcode incipient and differential diseases via real-time monitoring of biomarkers in fluids and in real-time via biomolecular fingerprinting. Additionally, the rapid advancements in micro/nanotechnology have a visible influence in all aspects of science and life. The miniaturization and enhanced properties of materials at the micro/nanoscale transcended the confines of the laboratory and are revolutionizing domains such as electronics, optics, medicine, and environmental science. The societal and technological impact of SERS biosensing by using semiconductor-based nanostructured smart substrates will be huge once minor technical pitfalls are solved. Herein, challenges in clinical routine testing are addressed in order to understand the context of how SERS can perform in real, in vivo sampling and bioassays for early neurodegenerative disease (ND) diagnosis. The main interest in translating SERS into clinical practice is reinforced by the practical advantages: portability of the designed setups, versatility in using nanomaterials of various matter and costs, readiness, and reliability. As we will present in this review, in the frame of technology readiness levels (TRL), the current maturity reached by semiconductor-based SERS biosensors, in particular that of zinc oxide (ZnO)-based hybrid SERS substrates, is situated at the development level TRL 6 (out of 9 levels). Three-dimensional, multilayered SERS substrates that provide additional plasmonic hot spots in the z-axis are of key importance in designing highly performant SERS biosensors for the detection of ND biomarkers.
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Affiliation(s)
- Alia Colniță
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Vlad-Alexandru Toma
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
- Department of Molecular Biology and Biotechnology, Faculty of Biology and Geology, Babeș-Bolyai University, 5-7 Clinicilor, 400006 Cluj-Napoca, Romania
- Institute of Biological Research, Department of Biochemistry and Experimental Biology, 48 Republicii, Branch of NIRDBS Bucharest, 400015 Cluj-Napoca, Romania
| | - Ioana Andreea Brezeștean
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Muhammad Ali Tahir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China
| | - Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
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Mohan B, Kumari R, Singh G, Singh K, Pombeiro AJL, Yang X, Ren P. Covalent organic frameworks (COFs) and metal-organic frameworks (MOFs) as electrochemical sensors for the efficient detection of pharmaceutical residues. ENVIRONMENT INTERNATIONAL 2023; 175:107928. [PMID: 37094512 DOI: 10.1016/j.envint.2023.107928] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/21/2023] [Accepted: 04/09/2023] [Indexed: 05/03/2023]
Abstract
Pharmaceutical residues are the undecomposed remains from drugs used in the medical and food industries. Due to their potential adverse effects on human health and natural ecosystems, they are of increasing worldwide concern. The acute detection of pharmaceutical residues can give a rapid examination of their quantity and then prevent them from further contamination. Herein, this study summarizes and discusses the most recent porous covalent-organic frameworks (COFs) and metal-organic frameworks (MOFs) for the electrochemical detection of various pharmaceutical residues. The review first introduces a brief overview of drug toxicity and its effects on living organisms. Subsequently, different porous materials and drug detection techniques are discussed with materials' properties and applications. Then the development of COFs and MOFs has been addressed with their structural properties and sensing applications. Further, the stability, reusability, and sustainability of MOFs/COFs are reviewed and discussed. Besides, COFs and MOFs' detection limits, linear ranges, the role of functionalities, and immobilized nanoparticles are analyzed and discussed. Lastly, this review summarized and discussed the MOF@COF composite as sensors, the fabrication strategies to enhance detection potential, and the current challenges in this area.
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Affiliation(s)
- Brij Mohan
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; Centro de Química Estrutural, Institute of Molecular Sciences, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Ritu Kumari
- Department of Chemistry, Kurukshetra University Kurukshetra -136119, India
| | - Gurjaspreet Singh
- Department of Chemistry and Centre of Advanced Studies Panjab University, Chandigarh-160014, India
| | - Kamal Singh
- Department of Physics, Chaudhary Bansi Lal University, Bhiwani, Haryana-127021, India
| | - Armando J L Pombeiro
- Centro de Química Estrutural, Institute of Molecular Sciences, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Xuemei Yang
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
| | - Peng Ren
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
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Jurina T, Sokač Cvetnić T, Šalić A, Benković M, Valinger D, Gajdoš Kljusurić J, Zelić B, Jurinjak Tušek A. Application of Spectroscopy Techniques for Monitoring (Bio)Catalytic Processes in Continuously Operated Microreactor Systems. Catalysts 2023. [DOI: 10.3390/catal13040690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
Abstract
In the last twenty years, the application of microreactors in chemical and biochemical industrial processes has increased significantly. The use of microreactor systems ensures efficient process intensification due to the excellent heat and mass transfer within the microchannels. Monitoring the concentrations in the microchannels is critical for a better understanding of the physical and chemical processes occurring in micromixers and microreactors. Therefore, there is a growing interest in performing in-line and on-line analyses of chemical and/or biochemical processes. This creates tremendous opportunities for the incorporation of spectroscopic detection techniques into production and processing lines in various industries. In this work, an overview of current applications of ultraviolet–visible, infrared, Raman spectroscopy, NMR, MALDI-TOF-MS, and ESI-MS for monitoring (bio)catalytic processes in continuously operated microreactor systems is presented. The manuscript includes a description of the advantages and disadvantages of the analytical methods listed, with particular emphasis on the chemometric methods used for spectroscopic data analysis.
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Affiliation(s)
- Tamara Jurina
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
| | - Tea Sokač Cvetnić
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
| | - Anita Šalić
- Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10 000 Zagreb, Croatia
| | - Maja Benković
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
| | - Davor Valinger
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
| | - Jasenka Gajdoš Kljusurić
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
| | - Bruno Zelić
- Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10 000 Zagreb, Croatia
- Department for Packaging, Recycling and Environmental Protection, University North, Trg dr. Žarka Dolinara 1, 48 000 Koprivnica, Croatia
| | - Ana Jurinjak Tušek
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva ul. 6, 10 000 Zagreb, Croatia
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Mochizuki K, Kumamoto Y, Maeda S, Tanuma M, Kasai A, Takemura M, Harada Y, Hashimoto H, Tanaka H, Smith NI, Fujita K. High-throughput line-illumination Raman microscopy with multislit detection. BIOMEDICAL OPTICS EXPRESS 2023; 14:1015-1026. [PMID: 36950233 PMCID: PMC10026569 DOI: 10.1364/boe.480611] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/27/2022] [Accepted: 01/02/2023] [Indexed: 06/18/2023]
Abstract
Raman microscopy is an emerging tool for molecular imaging and analysis of living samples. Use of Raman microscopy in life sciences is, however, still limited because of its slow measurement speed for spectral imaging and analysis. We developed a multiline-illumination Raman microscope to achieve ultrafast Raman spectral imaging. A spectrophotometer equipped with a periodic array of confocal slits detects Raman spectra from a sample irradiated by multiple line illuminations. A comb-like Raman hyperspectral image is formed on a two-dimensional detector in the spectrophotometer, and a hyperspectral Raman image is acquired by scanning the sample with multiline illumination array. By irradiating a sample with 21 simultaneous illumination lines, we achieved high-throughput Raman hyperspectral imaging of mouse brain tissue, acquiring 1108800 spectra in 11.4 min. We also measured mouse kidney and liver tissue as well as conducted label-free live-cell molecular imaging. The ultrafast Raman hyperspectral imaging enabled by the presented technique will expand the possible applications of Raman microscopy in biological and medical fields.
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Affiliation(s)
- Kentaro Mochizuki
- Department of Applied Physics, Osaka University, Suita, Osaka 565-0871, Japan
- Department of Pathology and Cell Regulation, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
- These authors contributed equally
| | - Yasuaki Kumamoto
- Department of Applied Physics, Osaka University, Suita, Osaka 565-0871, Japan
- Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka 565-0871, Japan
- These authors contributed equally
| | - Shunsuke Maeda
- Department of Applied Physics, Osaka University, Suita, Osaka 565-0871, Japan
| | - Masato Tanuma
- Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Osaka 565-0871, Japan
| | - Atsushi Kasai
- Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Osaka 565-0871, Japan
| | - Masashi Takemura
- Department of Pathology and Cell Regulation, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Yoshinori Harada
- Department of Pathology and Cell Regulation, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Hitoshi Hashimoto
- Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka 565-0871, Japan
- Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Osaka 565-0871, Japan
- Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Osaka 565-0871, Japan
- Institute for Datability Science, Osaka University, Suita, Osaka 565-0871, Japan
- Department of Molecular Pharmaceutical Sciences, Graduate School of Medicine, Osaka University, Suita, Osaka 565-0871, Japan
| | - Hideo Tanaka
- Department of Pathology and Cell Regulation, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Nicholas Isaac Smith
- Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka 565-0871, Japan
- Biophotonics Laboratory, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan
| | - Katsumasa Fujita
- Department of Applied Physics, Osaka University, Suita, Osaka 565-0871, Japan
- Department of Pathology and Cell Regulation, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
- Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka 565-0871, Japan
- Advanced Photonics and Biosensing Open Innovation Laboratory, AIST-Osaka University, Osaka University, Suita, Osaka 565-0871, Japan
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Woodhouse N, Majer J, Marshall P, Hood S, Notingher I. Quantification of Drugs in Brain and Liver Mimetic Tissue Models Using Raman Spectroscopy. APPLIED SPECTROSCOPY 2023; 77:246-260. [PMID: 36320126 PMCID: PMC10034474 DOI: 10.1177/00037028221139494] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
Quantitative analysis of drug delivery with in biological systems is an integral challenge in drug development. Analytical techniques are important for assessing both drug target delivery, target action, and drug toxicology. Using mimetic tissue models, we have investigated the efficacy of Raman spectroscopy in quantitative detection of alkyne group and deuterated drugs in rat brain and rat liver tissue models. Lasers with 671 nm and 785 nm wavelengths were assessed for their feasibility in this application due to opposing relative benefits and disadvantages. Thin tissue sections have been tested as a practical means of reducing autofluorescent background by minimizing out-of-focus tissue and therefore maximizing photobleaching rates. Alkyne-tagged drugs were quantitatively measured at 18 ± 5 μg/g drug/tissue mass ratio in rat brain and at 34 ± 6 μg/g in rat liver. Quantification calibration curves were generated for a range of concentrations from 0-500 μg/g. These results show the potential of Raman spectroscopy as a diffraction-limited spatially resolved imaging technique for assessing drug delivery in tissue applications.
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Affiliation(s)
- Nathan Woodhouse
- School of Physics and Astronomy,
University
of Nottingham, Nottingham, UK
| | | | | | | | - Ioan Notingher
- School of Physics and Astronomy,
University
of Nottingham, Nottingham, UK
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Zhang S, Chen S, Zhu R. Electroporation-Assisted Surface-Enhanced Raman Detection for Long-Term, Label-Free, and Noninvasive Molecular Profiling of Live Single Cells. ACS Sens 2023; 8:555-564. [PMID: 36399395 DOI: 10.1021/acssensors.2c01582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Molecule characterization of live single cells is greatly important in disease diagnoses and personalized treatments. Conventional molecule detection methods, such as mass spectrography, gene sequencing, or immunofluorescence, are usually destructive or labeled and unable to monitor the dynamic change of live cellular molecules. Herein, we propose an electroporation-assisted surface-enhanced Raman scattering (EP-SERS) method using a microchip to implement label-free, noninvasive, and continuous detections of the molecules of live single cells. The microchip containing microelectrodes with nanostructured EP-SERS probes has a multifunction of cell positioning, electroporation, and SERS detection. The EP-SERS method capably detects both the intracellular and extracellular molecules of live single cells without losing cell viability so as to enable long-term monitoring of the molecular pathological process in situ. We detect the molecules of single cells for two breast cancer cell lines with different malignancies (MCF-7 and MDA-MB-231), one liver cancer cell line (Huh-7), and one normal cell line (293T) using the EP-SERS method and classify these cell types to achieve high accuracies of 91.4-98.3% using their SERS spectra. Furthermore, 24 h continuous monitoring of the heterogeneous molecular responses of different cancer cell lines under doxorubicin treatment is successfully implemented using the EP-SERS method. This work provides a long-term, label-free, and biocompatible approach to simultaneously detect intracellular and extracellular molecules of live single cells on a chip, which would facilitate research and applications of cancer diagnoses and personalized treatments.
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Affiliation(s)
- Shengsen Zhang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Shengjie Chen
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Rong Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
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Variabilities in global DNA methylation and β-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer. Eur J Nucl Med Mol Imaging 2023; 50:1792-1810. [PMID: 36757432 PMCID: PMC10119063 DOI: 10.1007/s00259-023-06121-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/21/2023] [Indexed: 02/10/2023]
Abstract
PURPOSE Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue. METHODS Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues. RESULTS The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of β-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies. CONCLUSIONS Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and β-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing.
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Zeng Q, Chen C, Chen C, Song H, Li M, Yan J, Lv X. Serum Raman spectroscopy combined with convolutional neural network for rapid diagnosis of HER2-positive and triple-negative breast cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 286:122000. [PMID: 36279798 DOI: 10.1016/j.saa.2022.122000] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/26/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
Breast cancer is common in women, and its number of patients ranks first among female malignant tumors. Breast cancer is highly heterogeneous, and different types of breast cancer have different biological behaviors and prognoses. Therefore, identifying the different types of breast cancer is of great help in formulating individualized treatment plans. Based on serum Raman spectroscopy and deep learning algorithms, we propose a fast and low-cost diagnosis method for screening triple-negative breast cancer, human epidermal growth factor receptor 2 (HER2)-positive breast cancer, and healthy controls. We collected 75 serum samples in this study, including 23 triple-negative breast cancers, 22 HER2-positive breast cancers, and 30 healthy controls. Using the preprocessed Raman spectra as the input of deep learning, three deep learning models, neural network language model (NNLM), bidirectional long-short-term memory network (BiLSTM), and convolutional neural network (CNN), were established, and the accuracy rates of the three models were 87.78%, 90.37%, and 91.11%, respectively. The experimental results demonstrate the feasibility of serum Raman spectroscopy combined with deep learning algorithms to diagnose breast cancer, which can be used as an effective auxiliary diagnosis method for breast cancer.
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Affiliation(s)
- Qinggang Zeng
- College of Information Science and Engineering Xinjiang University, Urumqi 830046, China
| | - Cheng Chen
- College of Software, Xinjiang University, Urumqi 830046, China.
| | - Chen Chen
- College of Information Science and Engineering Xinjiang University, Urumqi 830046, China; Xinjiang Cloud Computing Application Laboratory, Karamay 834099, China
| | - Haitao Song
- Department of Breast, Head and Neck Surgery, Xinjiang Medical University Affiliated Tumor Hospital, Urumqi, China
| | - Min Li
- College of Information Science and Engineering Xinjiang University, Urumqi 830046, China
| | - Junyi Yan
- College of Software, Xinjiang University, Urumqi 830046, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi 830046, China; Key Laboratory of Signal Detection and Processing, Xinjiang University, Urumqi 830046, Xinjiang, China
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Sheehy G, Picot F, Dallaire F, Ember K, Nguyen T, Petrecca K, Trudel D, Leblond F. Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:025002. [PMID: 36825245 PMCID: PMC9941747 DOI: 10.1117/1.jbo.28.2.025002] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 01/30/2023] [Indexed: 05/25/2023]
Abstract
SIGNIFICANCE Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing. AIM An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise. RESULTS Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility. CONCLUSIONS A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.
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Affiliation(s)
- Guillaume Sheehy
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Fabien Picot
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Frédérick Dallaire
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Katherine Ember
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Tien Nguyen
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Division of Neuropathology, Department of Pathology, Montreal, Quebec, Canada
| | - Dominique Trudel
- Institut du cancer de Montréal, Montreal, Quebec, Canada
- Université de Montréal, Department of Pathology and Cellular Biology, Montreal, Quebec, Canada
- Center Hospitalier de l’Université de Montréal, Department of Pathology, Montreal, Quebec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
- Institut du cancer de Montréal, Montreal, Quebec, Canada
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Lenski M, Bruno C, Darrouzain F, Allorge D. Métabolomique : principes et applications en toxicologie biologique et médicolégale. TOXICOLOGIE ANALYTIQUE ET CLINIQUE 2023. [DOI: 10.1016/j.toxac.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
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Szymoński K, Chmura Ł, Lipiec E, Adamek D. Vibrational spectroscopy – are we close to finding a solution for early pancreatic cancer diagnosis? World J Gastroenterol 2023; 29:96-109. [PMID: 36683712 PMCID: PMC9850953 DOI: 10.3748/wjg.v29.i1.96] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 10/03/2022] [Accepted: 10/31/2022] [Indexed: 01/04/2023] Open
Abstract
Pancreatic cancer (PC) is an aggressive and lethal neoplasm, ranking seventh in the world for cancer deaths, with an overall 5-year survival rate of below 10%. The knowledge about PC pathogenesis is rapidly expanding. New aspects of tumor biology, including its molecular and morphological heterogeneity, have been reported to explain the complicated “cross-talk” that occurs between the cancer cells and the tumor stroma or the nature of pancreatic ductal adenocarcinoma-associated neural remodeling. Nevertheless, currently, there are no specific and sensitive diagnosis options for PC. Vibrational spectroscopy (VS) shows a promising role in the development of early diagnosis technology. In this review, we summarize recent reports about improvements in spectroscopic methodologies, briefly explain and highlight the drawbacks of each of them, and discuss available solutions. The important aspects of spectroscopic data evaluation with multivariate analysis and a convolutional neural network methodology are depicted. We conclude by presenting a study design for systemic verification of the VS-based methods in the diagnosis of PC.
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Affiliation(s)
- Krzysztof Szymoński
- Department of Pathomorphology, Jagiellonian University Medical College, Cracow 33-332, Poland
- Department of Pathomorphology, University Hospital in Cracow, Cracow 31-501, Poland
| | - Łukasz Chmura
- Department of Pathomorphology, Jagiellonian University Medical College, Cracow 33-332, Poland
- Department of Pathomorphology, University Hospital in Cracow, Cracow 31-501, Poland
| | - Ewelina Lipiec
- M. Smoluchowski Institute of Physics, Jagiellonian University, Cracow 30-348, Poland
| | - Dariusz Adamek
- Department of Pathomorphology, University Hospital in Cracow, Cracow 31-501, Poland
- Department of Neuropathology, Jagiellonian University Medical College, Cracow 33-332, Poland
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Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning. Pharmaceutics 2023; 15:pharmaceutics15010203. [PMID: 36678833 PMCID: PMC9862809 DOI: 10.3390/pharmaceutics15010203] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/11/2023] Open
Abstract
The most commonly occurring malignant brain tumors are gliomas, and among them is glioblastoma multiforme. The main idea of the paper is to estimate dependency between glioma tissue and blood serum biomarkers using Raman spectroscopy. We used the most common model of human glioma when continuous cell lines, such as U87, derived from primary human tumor cells, are transplanted intracranially into the mouse brain. We studied the separability of the experimental and control groups by machine learning methods and discovered the most informative Raman spectral bands. During the glioblastoma development, an increase in the contribution of lactate, tryptophan, fatty acids, and lipids in dried blood serum Raman spectra were observed. This overlaps with analogous results of glioma tissues from direct Raman spectroscopy studies. A non-linear relationship between specific Raman spectral lines and tumor size was discovered. Therefore, the analysis of blood serum can track the change in the state of brain tissues during the glioma development.
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Harris G, Rickard JJS, Butt G, Kelleher L, Blanch RJ, Cooper J, Oppenheimer PG. Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury. IEEE Rev Biomed Eng 2023; 16:530-559. [PMID: 35320105 PMCID: PMC9888755 DOI: 10.1109/rbme.2022.3161352] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 02/11/2022] [Accepted: 03/15/2022] [Indexed: 11/06/2022]
Abstract
The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.
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Affiliation(s)
- Georgia Harris
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
| | - Jonathan James Stanley Rickard
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
- Department of Physics, Cavendish LaboratoryUniversity of CambridgeCB3 0HECambridgeU.K.
| | - Gibran Butt
- Ophthalmology DepartmentUniversity Hospitals Birmingham NHS Foundation TrustB15 2THBirminghamU.K.
| | - Liam Kelleher
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
| | - Richard James Blanch
- Department of Military Surgery and TraumaRoyal Centre for Defence MedicineB15 2THBirminghamU.K.
- Neuroscience and Ophthalmology, Department of Ophthalmology, University Hospitals Birmingham NHS Foundation TrustcBirminghamU.K.
| | - Jonathan Cooper
- School of Biomedical EngineeringUniversity of GlasgowG12 8LTGlasgowU.K.
| | - Pola Goldberg Oppenheimer
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
- Healthcare Technologies Institute, Institute of Translational MedicineB15 2THBirminghamU.K.
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Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning. Nat Commun 2023; 14:48. [PMID: 36599851 DOI: 10.1038/s41467-022-35696-2] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 12/15/2022] [Indexed: 01/06/2023] Open
Abstract
Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.
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