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Journal articles on the topic 'Raman-MCR'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Hruška, Branislav, Rajesh Dagupati, Mária Chromčíková, Aleksandra Nowicka, Jan Macháček, Marek Liška, and Francisco Munoz. "Thermodynamic model and Raman spectra of MgO–P2O5 glasses." Journal of Thermal Analysis and Calorimetry 142, no. 5 (July 20, 2020): 2025–31. http://dx.doi.org/10.1007/s10973-020-10033-1.

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AbstractThe structure of binary glasses xMgO·(1−x)P2O5 (x = 0.30, 0.35, 0.40, 0.45, 0.50, and 0.55) was studied by thermodynamic model (TDM) of Shakhmatkin and Vedishcheva (SV) and Raman spectroscopy. In the TDM, six following system components were considered: MgO (M), P2O5 (P), MgO·2P2O5 (MP2), MgO·P2O5 (MP), 2MgO·P2O5 (M2P), 3MgO·P2O5 (M3P). The principal component analysis (PCA) of experimental Raman spectra resulted in three independent components. The baseline subtracted and thermally corrected Raman spectra were analyzed by the multivariate curve analysis (MCR) for three components. The MCR resulted in the Raman spectra and relative abundance of each component. The experimental spectra were reproduced by the MCR on the level of 99.9%. Correlation analysis attributed the MCR components to M2P, MP, and MP2. Then the Malfait’s decomposition was performed based on the TDM-SV equilibrium molar amounts of system components (MP2, MP, and M2P) resulting in partial Raman spectra (PRS). Normalized MCR loadings coincide with normalized PRS. Adjusted scores were reproduced with good accuracy equilibrium molar amounts of system components.

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2

Hruška, Branislav, Rajesh Dagupati, Mária Chromčíková, Aleksandra Nowicka, Jaroslava Michálková, Jacob A. Peterson, Marek Liška, and Francisco Munoz. "Structure and Raman spectra of binary barium phosphate glasses." Journal of Thermal Analysis and Calorimetry 142, no. 2 (January 27, 2020): 937–42. http://dx.doi.org/10.1007/s10973-020-09328-0.

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Abstract The structure of xBaO·(1 − x) P2O5 (x = 0.30, 0.35, 0.40, 0.45, and 0.50) glasses was studied by Raman spectroscopy and thermodynamic model Shakhmatkin and Vedishcheva (SVTDM). The seven system components (defined as stable crystalline phases of the BaO–P2O5 binary phase diagram) were considered in the SVTDM: BaO, P2O5, 4BaO·P2O5 (B4P), 3BaO·P2O5 (B3P), 2BaO·P2O5 (B2P), BaO·P2O5 (BP), and BaO·2 P2O5 (BP2). Only the equilibrium molar abundances of BP and BP2 were non-negligible in all studied glass compositions. Therefore, in the next step, multivariate curve analysis (MCR) of the baseline—subtracted, thermally—corrected experimental Raman spectra, was performed for two components (BP2 and BP). MCR resulted in the Raman spectra (loadings) and relative abundances (scores) of each considered component. The MCR method reproduced 98.93% of the spectral data variance. Then, the decomposition of Malfait was used. The perfect fit between the MCR loadings and the partial Raman spectra of BP2 and BP, obtained by Malfait’s decomposition, was found, confirming the validity of thermodynamic model.

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3

Andrew, Jeremy J., and Thomas M. Hancewicz. "Rapid Analysis of Raman Image Data Using Two-Way Multivariate Curve Resolution." Applied Spectroscopy 52, no. 6 (June 1998): 797–807. http://dx.doi.org/10.1366/0003702981944526.

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The application of standard two-way curve resolution methods is reported for analysis of three-way Raman image data. Two current curve resolution methods are described: principal factor multivariate curve resolution (PF-MCR), which uses principal factor analysis (PFA) combined with varimax rotation and alternating least-squares optimization (ALS), and orthogonal projection multivariate curve resolution (OP-MCR), which uses a Gram–Schmidt modified orthogonal projection approach (OPA) followed by ALS. The OP-MCR technique is shown to be an extremely rapid method of analysis producing results equivalent to those of PF-MCR in one-third to one-fourth the time. The results from MCR analysis using either method provide the number of chemical species present in the sample, the spectrum of each species for identification, and the concentration image for each species. The additional benefit of image noise reduction also results from the MCR techniques. A brief description of the theory is presented followed by analysis and comparison of results for two real Raman image data. A discussion is given addressing the rapid analysis aspects of OP-MCR and the relative merits and drawbacks of the technique in comparison to PF-MCR. The use of data subsampling is also discussed as a way of decreasing analysis time without loss in accuracy or performance.

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4

Ahmed, Mohammed, Ajay K. Singh, and Jahur A. Mondal. "Hydrogen-bonding and vibrational coupling of water in a hydrophobic hydration shell as observed by Raman-MCR and isotopic dilution spectroscopy." Physical Chemistry Chemical Physics 18, no. 4 (2016): 2767–75. http://dx.doi.org/10.1039/c5cp07014g.

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5

Mazivila, Sarmento J., Helena I. S. Nogueira, Ricardo N. M. J. Páscoa, David S. M. Ribeiro, João L. M. Santos, João M. M. Leitão, and Joaquim C. G. Esteves da Silva. "Portable and benchtop Raman spectrometers coupled to cluster analysis to identify quinine sulfate polymorphs in solid dosage forms and antimalarial drug quantification in solution by AuNPs-SERS with MCR-ALS." Analytical Methods 12, no. 18 (2020): 2407–21. http://dx.doi.org/10.1039/d0ay00693a.

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Raman spectrometers coupled to cluster analysis were able to identify two polymorphs of quinine sulfate in solid dosage forms. Gold nanoparticles-surface-enhanced Raman scattering with MCR-ALS was used to antimalarial drug quantification in solution.

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6

Bredt, Aria J., and Dor Ben-Amotz. "Influence of crowding on hydrophobic hydration-shell structure." Physical Chemistry Chemical Physics 22, no. 20 (2020): 11724–30. http://dx.doi.org/10.1039/d0cp00702a.

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The influence of molecular crowding on water structure, and the associated crossover behavior, is quantified using Raman multivariate curve resolution (Raman-MCR) hydration-shell vibrational spectroscopy of aqueous tert-butyl alcohol, 2-butyl alcohol and 2-butoxyethanol solutions of variable concentration and temperature.

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7

Matveeva, Irina, Ivan Bratchenko, Yulia Khristoforova, Lyudmila Bratchenko, Alexander Moryatov, Sergey Kozlov, Oleg Kaganov, and Valery Zakharov. "Multivariate Curve Resolution Alternating Least Squares Analysis of In Vivo Skin Raman Spectra." Sensors 22, no. 24 (December 7, 2022): 9588. http://dx.doi.org/10.3390/s22249588.

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In recent years, Raman spectroscopy has been used to study biological tissues. However, the analysis of experimental Raman spectra is still challenging, since the Raman spectra of most biological tissue components overlap significantly and it is difficult to separate individual components. New methods of analysis are needed that would allow for the decomposition of Raman spectra into components and the evaluation of their contribution. The aim of our work is to study the possibilities of the multivariate curve resolution alternating least squares (MCR-ALS) method for the analysis of skin tissues in vivo. We investigated the Raman spectra of human skin recorded using a portable conventional Raman spectroscopy setup. The MCR-ALS analysis was performed for the Raman spectra of normal skin, keratosis, basal cell carcinoma, malignant melanoma, and pigmented nevus. We obtained spectral profiles corresponding to the contribution of the optical system and skin components: melanin, proteins, lipids, water, etc. The obtained results show that the multivariate curve resolution alternating least squares analysis can provide new information on the biochemical profiles of skin tissues. Such information may be used in medical diagnostics to analyze Raman spectra with a low signal-to-noise ratio, as well as in various fields of science and industry for preprocessing Raman spectra to remove parasitic components.

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8

Hamla, Sabrina, Pierre-Yves Sacré, Allison Derenne, Ben Cowper, Erik Goormaghtigh, Philippe Hubert, and Eric Ziemons. "A New Alternative Tool to Analyse Glycosylation in Monoclonal Antibodies Based on Drop-Coating Deposition Raman imaging: A Proof of Concept." Molecules 27, no. 14 (July 9, 2022): 4405. http://dx.doi.org/10.3390/molecules27144405.

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Glycosylation is considered a critical quality attribute of therapeutic proteins as it affects their stability, bioactivity, and safety. Hence, the development of analytical methods able to characterize the composition and structure of glycoproteins is crucial. Existing methods are time consuming, expensive, and require significant sample preparation, which can alter the robustness of the analyses. In this context, we developed a fast, direct, and simple drop-coating deposition Raman imaging (DCDR) method combined with multivariate curve resolution alternating least square (MCR-ALS) to analyze glycosylation in monoclonal antibodies (mAbs). A database of hyperspectral Raman imaging data of glycoproteins was built, and the glycoproteins were characterized by LC-FLR-MS as a reference method to determine the composition in glycans and monosaccharides. The DCDR method was used and allowed the separation of excipient and protein by forming a “coffee ring”. MCR-ALS analysis was performed to visualize the distribution of the compounds in the drop and to extract the pure spectral components. Further, the strategy of SVD-truncation was used to select the number of components to resolve by MCR-ALS. Raman spectra were processed by support vector regression (SVR). SVR models showed good predictive performance in terms of RMSECV, R2CV.

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9

Mendes de Oliveira, Denilson, Samual R. Zukowski, Vladimir Palivec, Jérôme Hénin, Hector Martinez-Seara, Dor Ben-Amotz, Pavel Jungwirth, and Elise Duboué-Dijon. "Binding of divalent cations to acetate: molecular simulations guided by Raman spectroscopy." Physical Chemistry Chemical Physics 22, no. 41 (2020): 24014–27. http://dx.doi.org/10.1039/d0cp02987d.

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10

Passos, Aline Ribeiro, Camille La Fontaine, Sandra Helena Pulcinelli, Celso Valentim Santilli, and Valérie Briois. "Quick-EXAFS and Raman monitoring of activation, reaction and deactivation of NiCu catalysts obtained from hydrotalcite-like precursors." Physical Chemistry Chemical Physics 22, no. 34 (2020): 18835–48. http://dx.doi.org/10.1039/d0cp00380h.

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11

Chen, Peter C., Kyndra A. Cottingham, Rebecca M. Royster, and Candace C. Joyner. "High-Speed Gas Chromatography—Multiplex Coherent Raman Analysis of BTEX." Applied Spectroscopy 59, no. 11 (November 2005): 1310–14. http://dx.doi.org/10.1366/000370205774783313.

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Gas chromatography–multiplex coherent Raman (GC-MCR) is a new tandem technique that can be used for the high-speed analysis of volatile mixtures. BTEX serves as a useful and challenging test sample because of the similarity in boiling point and spectroscopic properties of its constituents. The ability to spectroscopically resolve isomers (e.g., m-xylene and p-xylene) allows GC-MCR to sacrifice chromatographic resolution for speed. The result is the analysis of BTEX in less than 5 min, which is relatively fast compared with other tandem GC techniques.

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12

Matveeva, Irina, Lyudmila Bratchenko, Oleg Myakinin, Elena Tupikova, and Valery Zakharov. "The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis." Journal of Biomedical Photonics & Engineering 7, no. 2 (June 30, 2021): 020309. http://dx.doi.org/10.18287/jbpe21.07.020309.

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Changes in the concentration of free amino acids in biological tissues is a sign of impaired protein metabolism in patients with cancer. Recently, Raman spectroscopy has been used for early diagnostics of oncological diseases. The concentrations of individual components of biological tissue (for instance, the concentrations of amino acids) can be obtained by decomposing the tissue Raman spectrum. This study was designed to evaluate the effect of noise in the Raman spectra of individual amino acids on the result of the decomposition of the spectra of an amino acid mixture. As a decomposition method, we used Multivariate Curve Resolution-Alternating Least Squares (MCR–ALS) analysis and investigate experimental Raman spectra of amino acids and mathematically simulated Raman spectra of amino acid mixtures. Noise with different signal-to-noise ratios (SNR) was artificially added to both the experimental spectra of pure amino acids and the spectra of the mixtures. Concentration values for each amino acid obtained as a result of applying the MCR–ALS analysis have been compared with the corresponding true values and the correlation coefficients have been calculated. The results show a less pronounced negative effect of noise in the case when the spectra of pure amino acids (which were used as a basis for the MCR–ALS analysis) are noisy, and a more pronounced negative effect when the spectrum of the mixture is noisy. The accuracy of reconstruction of an amino acid is also negatively affected by strong background fluorescence in the amino acid spectrum. Moreover, the results indicate that using the basis spectra with a high SNR (SNR = 5) makes it possible to successfully estimate the amino acid concentrations in a mixture even when the Raman spectrum of the mixture is noisy and has a low SNR (SNR < 5).

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13

Smith, Joseph P., Frank C. Smith, and Karl S. Booksh. "Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) with Raman Imaging Applied to Lunar Meteorites." Applied Spectroscopy 72, no. 3 (August 11, 2017): 404–19. http://dx.doi.org/10.1177/0003702817721715.

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Lunar meteorites provide a more random sampling of the surface of the Moon than do the returned lunar samples, and they provide valuable information to help estimate the chemical composition of the lunar crust, the lunar mantle, and the bulk Moon. As of July 2014, ∼96 lunar meteorites had been documented and ten of these are unbrecciated mare basalts. Using Raman imaging with multivariate curve resolution–alternating least squares (MCR-ALS), we investigated portions of polished thin sections of paired, unbrecciated, mare-basalt lunar meteorites that had been collected from the LaPaz Icefield (LAP) of Antarctica—LAP 02205 and LAP 04841. Polarized light microscopy displays that both meteorites are heterogeneous and consist of polydispersed sized and shaped particles of varying chemical composition. For two distinct probed areas within each meteorite, the individual chemical species and associated chemical maps were elucidated using MCR-ALS applied to Raman hyperspectral images. For LAP 02205, spatially and spectrally resolved clinopyroxene, ilmenite, substrate-adhesive epoxy, and diamond polish were observed within the probed areas. Similarly, for LAP 04841, spatially resolved chemical images with corresponding resolved Raman spectra of clinopyroxene, troilite, a high-temperature polymorph of anorthite, substrate-adhesive epoxy, and diamond polish were generated. In both LAP 02205 and LAP 04841, substrate-adhesive epoxy and diamond polish were more readily observed within fractures/veinlet features. Spectrally diverse clinopyroxenes were resolved in LAP 04841. Factors that allow these resolved clinopyroxenes to be differentiated include crystal orientation, spatially distinct chemical zoning of pyroxene crystals, and/or chemical and molecular composition. The minerals identified using this analytical methodology—clinopyroxene, anorthite, ilmenite, and troilite—are consistent with the results of previous studies of the two meteorites using electron microprobe analysis. To our knowledge, this is the first report of MCR-ALS with Raman imaging used for the investigation of both lunar and other types of meteorites. We have demonstrated the use of multivariate analysis methods, namely MCR-ALS, with Raman imaging to investigate heterogeneous lunar meteorites. Our analytical methodology can be used to elucidate the chemical, molecular, and structural characteristics of phases in a host of complex, heterogeneous geological, geochemical, and extraterrestrial materials.

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14

Ilchenko, O. O., Y. V. Pilgun, A. S. Reynt, and A. M. Kutsyk. "NNLS and MCR-ALS Decomposition of Raman and FTIR Spectra of Multicomponent Liquid Solutions." Ukrainian Journal of Physics 61, no. 6 (June 2016): 519–22. http://dx.doi.org/10.15407/ujpe61.06.0519.

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15

Shen, Yutan, Lu Liu, Qiancheng Zheng, Xi Zhao, Yuchun Han, Qianjin Guo, and Yilin Wang. "Quantitative insights into tightly and loosely bound water in hydration shells of amino acids." Soft Matter 17, no. 44 (2021): 10080–89. http://dx.doi.org/10.1039/d1sm01234g.

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Raman-MCR and DSC are used in combination to prove two kinds of bound water in the hydration shell of 20 zwitterionic amino acids, and the hydration water structure and H-bonding change in the hydration shell are also revealed.

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16

Iwasaki, Keita, Asuka Araki, C. Murali Krishna, Riruke Maruyama, Tatsuyuki Yamamoto, and Hemanth Noothalapati. "Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis." International Journal of Molecular Sciences 22, no. 2 (January 14, 2021): 800. http://dx.doi.org/10.3390/ijms22020800.

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Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis–alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells.

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17

Matveeva, I., Y. Khristoforova, A. Moryatov, O. Myakinin, I. Bratchenko, S. Kozlov, and V. Zakharov. "Classification of human skin Raman spectra using multivariate curve resolution (MCR) and partial least squares discriminant analysis (PLS-DA)." Journal of Physics: Conference Series 2127, no. 1 (November 1, 2021): 012065. http://dx.doi.org/10.1088/1742-6596/2127/1/012065.

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Abstract The main purpose of the paper is classification of the human skin Raman spectra using partial least squares discriminant analysis (PLS-DA) into classes depending on the disease. In vivo Raman spectra of normal skin, basal cell carcinoma, malignant melanoma and pigmented nevus are considered. A feature of the approach is the analysis not of the Raman spectra themselves, but of the concentrations of the eight most significant spectra components identified using multivariate curve resolution (MCR). As a result, the ROC curve was calculated and the optimal classification threshold was chosen. The accuracy of the classification models ranged from 63.3 to 86.7%, depending on the model. The findings suggest that this approach could also be useful for classification of specific diseases.

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18

Pérez-Guaita, David, Guillermo Quintás, Zeineb Farhane, Romá Tauler, and Hugh J. Byrne. "Combining Pharmacokinetics and Vibrational Spectroscopy: MCR-ALS Hard-and-Soft Modelling of Drug Uptake In Vitro Using Tailored Kinetic Constraints." Cells 11, no. 9 (May 5, 2022): 1555. http://dx.doi.org/10.3390/cells11091555.

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Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug and subsequent cellular responses difficult. Indeed, multivariate methods that relate spectral features to the inoculation time do not normally take into account the kinetics involved, and important theoretical information which could assist in the elucidation of the relevant spectral signatures is excluded. Here, we propose the integration of kinetic equations in the modelling of drug uptake and subsequent cellular responses using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and tailored kinetic constraints, based on a system of ordinary differential equations. Advantages of and challenges to the methodology were evaluated using simulated Raman spectral data sets and real Raman spectra acquired from A549 and Calu-1 human lung cells inoculated with doxorubicin, in vitro. The results suggest a dependency of the outcome on the system of equations used, and the importance of the temporal resolution of the data set to enable the use of complex equations. Nevertheless, the use of tailored kinetic constraints during MCR-ALS allowed a more comprehensive modelling of the system, enabling the elucidation of not only the time-dependent concentration profiles and spectral features of the drug binding and cellular responses, but also an accurate computation of the kinetic constants.

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19

Shen, Yutan, Bin Liu, Jie Cui, Junfeng Xiang, Meirong Liu, Yuchun Han, and Yilin Wang. "Hydration Shell Changes in Surfactant Aggregate Transitions Revealed by Raman-MCR Spectroscopy." Journal of Physical Chemistry Letters 11, no. 17 (August 17, 2020): 7429–37. http://dx.doi.org/10.1021/acs.jpclett.0c02140.

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20

Saikia, Dimple, Priyanka Jadhav, Arti R. Hole, Chilakapati Murali Krishna, and Surya P. Singh. "Unraveling the Secrets of Colistin Resistance with Label-Free Raman Spectroscopy." Biosensors 12, no. 9 (September 11, 2022): 749. http://dx.doi.org/10.3390/bios12090749.

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The rise in number of infections from multidrug-resistant (MDR) Gram-negative microbes has led to an increase in the use of a variety of ‘polymyxins’ such as colistin. Even though colistin is known to cause minor nephro- and neuro-toxicity, it is still considered as last resort antibiotic for treating MDR infections. In this study, we have applied Raman spectroscopy to understand the differences among colistin sensitive and resistant bacterial strains at community level. We have successfully generated colistin resistant clones and verified the presence of resistance-causing MCR-1 plasmid. A unique spectral profile associated with specific drug concentration has been obtained. Successful delineation between resistant and sensitive cells has also been achieved via principal component analysis. Overall findings support the prospective utility of Raman spectroscopy in identifying anti-microbial resistance.

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21

Barzan, Giulia, Alessio Sacco, Luisa Mandrile, Andrea Mario Giovannozzi, Chiara Portesi, and Andrea Mario Rossi. "Hyperspectral Chemical Imaging of Single Bacterial Cell Structure by Raman Spectroscopy and Machine Learning." Applied Sciences 11, no. 8 (April 10, 2021): 3409. http://dx.doi.org/10.3390/app11083409.

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In this work, biomolecules, such as membrane proteins, lipids, and DNA, were identified and their spatial distribution was mapped within a single Escherichia coli cell by Raman hyperspectral imaging. Raman spectroscopy allows direct, nondestructive, rapid, and cost-effective analysis of biological samples, minimizing the sample preparation and without the need of chemical label or immunological staining. Firstly, a comparison between an air-dried and a freeze-dried cell was made, and the principal vibrational modes associated to the membrane and nucleic acids were identified by the bacterium’s Raman chemical fingerprint. Then, analyzing the Raman hyperspectral images by multivariate statistical analysis, the bacterium biological status was investigated at a subcellular level. Principal components analysis (PCA) was applied for dimensionality reduction of the spectral data, then spectral unmixing was performed by multivariate curve resolution–alternating least squares (MCR-ALS). Thanks to multivariate data analysis, the DNA segregation and the Z-ring formation of a replicating bacterial cell were detected at a sub-micrometer level, opening the way to real-time molecular analysis that could be easily applied on in vivo or ex vivo biological samples, avoiding long preparation and analysis process.

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22

Arnfast, Lærke, Jeroen van Renterghem, Johanna Aho, Johan Bøtker, Dhara Raijada, Stefania Baldursdóttir, Thomas De Beer, and Jukka Rantanen. "Exploring the Complexity of Processing-Induced Dehydration during Hot Melt Extrusion Using In-Line Raman Spectroscopy." Pharmaceutics 12, no. 2 (February 1, 2020): 116. http://dx.doi.org/10.3390/pharmaceutics12020116.

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The specific aim in this study was to understand the effect of critical process parameters on the solid form composition of model drug compounds during hot melt extrusion using in-line Raman spectroscopy combined with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) modeling for semi-quantitative kinetic profiling. It was observed that the hydrate and anhydrate solid forms of two model drugs in the melts of nitrofurantoin (NF):polyethylene oxide (PEO) and piroxicam (PRX):PEO could be resolved from a MCR-ALS model without an external calibration dataset. Based on this model, the influence of two critical process parameters (shear and temperature) on the solid form composition could be evaluated in a real-time mode and the kinetics of complex transformation pathways could be explored. Additionally, the dehydration pathways of NF monohydrate and PRX monohydrate in molten PEO could be derived. It can be concluded that dehydration of both hydrates in PEO occurs via competing mechanisms—a solution-mediated transformation pathway and a solid–solid transformation, and that the balance between these mechanisms is determined by the combined effect of both temperature and shear. Another important observation was that the water released from these hydrate compounds has a detectable effect on the rheological characteristics of this mixture.

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23

Smith, Joseph P., Erin C. Holahan, Frank C. Smith, Veronica Marrero, and Karl S. Booksh. "A novel multivariate curve resolution-alternating least squares (MCR-ALS) methodology for application in hyperspectral Raman imaging analysis." Analyst 144, no. 18 (2019): 5425–38. http://dx.doi.org/10.1039/c9an00787c.

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A new multivariate curve resolution-alternating least squares (MCR-ALS) methodology is presented that uses approximate reference spectra to determine optimal model complexity for identifying chemical constituents within hyperspectral imaging data.

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24

Sricharoen, Nontawat, Thanyada Sukmanee, Prompong Pienpinijtham, Sanong Ekgasit, Yasutaka Kitahama, Yukihiro Ozaki, and Kanet Wongravee. "MCR-ALS with sample insertion constraint to enhance the sensitivity of surface-enhanced Raman scattering detection." Analyst 146, no. 10 (2021): 3251–62. http://dx.doi.org/10.1039/d1an00069a.

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25

Paidi, Santosh Kumar, Joel Rodriguez Troncoso, Piyush Raj, Paola Monterroso Diaz, Jesse D. Ivers, David E. Lee, Nathan L. Avaritt, et al. "Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy." Cancer Research 81, no. 22 (October 13, 2021): 5745–55. http://dx.doi.org/10.1158/0008-5472.can-21-1438.

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Abstract Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack of reliable biomarkers for prediction and evaluation of treatment response. Here, we demonstrate the first application of label-free Raman spectroscopy for elucidating biomolecular changes induced by anti–CTLA4 and anti–PD-L1 immune checkpoint inhibitors (ICI) in the tumor microenvironment (TME) of colorectal tumor xenografts. Multivariate curve resolution–alternating least squares (MCR-ALS) decomposition of Raman spectral datasets revealed early changes in lipid, nucleic acid, and collagen content following therapy. Support vector machine classifiers and random forests analysis provided excellent prediction accuracies for response to both ICIs and delineated spectral markers specific to each therapy, consistent with their differential mechanisms of action. Corroborated by proteomics analysis, our observation of biomolecular changes in the TME should catalyze detailed investigations for translating such markers and label-free Raman spectroscopy for clinical monitoring of immunotherapy response in cancer patients. Significance: This study provides first-in-class evidence that optical spectroscopy allows sensitive detection of early changes in the biomolecular composition of tumors that predict response to immunotherapy with immune checkpoint inhibitors.

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Pudney, Paul D. A., Thomas M. Hancewicz, and Dale G. Cunningham. "The use of confocal Raman spectroscopy to characterise the microstructure of complex biomaterials: foods." Spectroscopy 16, no. 3-4 (2002): 217–25. http://dx.doi.org/10.1155/2002/726874.

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The properties and behaviour of many biomaterials often depends crucially on their microstructure. This is especially true of the largest class of biomaterials in use, foods. They include general properties, e.g., food texture, and others, such as spreadability of margarine/butter, pourablity of ketchup, scoopablity of ice cream, and also flavour release (a problem that has much in common with drug delivery), to name but a few. Thus, most food laboratories do a large amount of work in rheology and microscopy to relate structure and properties. However, a knowledge gap exists, i.e., what is the location and quantity of ingredients/molecules within a structure? Both of these questions need to be answered if a complete understanding is to be obtained. The “what is where” question can sometimes be answered by using various microscopic labelling techniques, although there can be many problems with these methods. Bulk separation is often attempted, followed by some kind of more classical analysis, but this is often either not possible or may cause some kind of uncontrolled perturbation. Thus, the ability to obtain quantitative informationin situwithin a microstructure has been an unobtained goal in much of food science research. These types of questions are, of course, also asked in many related fields of research.This paper will illustrate how the advances in confocal Raman spectroscopy have allowed this problem to be tackled, in a non‒invasive way. It will show how careful development of experimental procedures and advances in data analysis methods, allow even quantitative maps of microstructures to be obtained. The details of this approach will be described including a discussion of the limitations of current methods, especially depth resolution, and how these were overcome. The use of these methods will be illustrated with a gelled mixture of two carbohydrate polymers, κ‒carageenan and gellan. Despite being similar polymers, and hence having highly overlapping spectra, the pure spectral components can be separated using a chemometrics based method, multivariate curve resolution (MCR). The principles of this method will be described. Under certain concentration regimes these two biopolymers phase separate. This property can be used to produce different microstructures. Two different microstructures were produced and mapped using Raman spectroscopy. This data was analysed using the MCR method to show the relative locations of the two polymers within the microstructure. Furthermore, by augmenting the data from these maps with calibration data for the two bioploymers, quantitative maps were produced. The resultant concentrations can then be used to produce tie lines for the κ‒carageenan/gellan phase diagram, which is essential for understanding and manipulating the structure and properties in a systematic way. This methodology can be readily extended to much more complex multicomponent systems, such as complete food products.This paper shows that the combination of the confocal Raman spectroscopy and MCR data analysis methodology is very powerful and is readily applicable in many areas of research, especially the biomaterial/biomedical fields.

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Ghosh, Nishith, Subhadip Roy, Anisha Bandyopadhyay, and Jahur Alam Mondal. "Vibrational Raman Spectroscopy of the Hydration Shell of Ions." Liquids 3, no. 1 (December 27, 2022): 19–39. http://dx.doi.org/10.3390/liquids3010003.

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Ionic perturbation of water has important implications in various chemical, biological and environmental processes. Previous studies revealed the structural and dynamical perturbation of water in the presence of ions, mainly with concentrated electrolyte solutions having significant interionic interactions. These investigations highlighted the need of selective extraction of the hydration shell water from a dilute electrolyte solution that is largely free from interionic interactions. Double-difference infrared (DDIR) and Raman multivariate curve resolution (Raman-MCR), as well as MD simulation, provided valuable insight in this direction, suggesting that the perturbed water mainly resides in the immediate vicinity of the ion, called the hydration shell. Recently, we have introduced Raman difference spectroscopy with simultaneous curve fitting (Raman-DS-SCF) analysis that can quantitatively extract the vibrational response of the perturbed water pertaining to the hydration shell of fully hydrated ions/solute. The DS-SCF analysis revealed novel hydrogen-bond (H-bond) structural features of hydration water, such as the existence of extremely weakly interacting water–OH (νmax ~ 3600 cm−1) in the hydration shell of high-charge-density metal ions (Mg2+, Dy3+). In addition, Raman-DS-SCF retrieves the vibrational response of the shared water in the water–shared-ion pair (WSIP), which is different from the hydration shell water of either the interacting cation and anion. Herein, we discuss the perturbation of water H-bonding in the immediate vicinity of cation, anion, zwitterion and hydrophobes and also the inter-ionic interactions, with a focus on the recent results from our laboratory using Raman-DS-SCF spectroscopy.

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Neves, Ana Carolina de Oliveira, Mohammed Zougagh, Ángel Ríos, Romà Tauler, Kazumasa Wakamatsu, and Ismael Galván. "Pheomelanin subunit non-destructive quantification by Raman spectroscopy and multivariate curve resolution-alternating least squares (MCR-ALS)." Chemometrics and Intelligent Laboratory Systems 217 (October 2021): 104406. http://dx.doi.org/10.1016/j.chemolab.2021.104406.

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Villa, Javier E. L., Celio Pasquini, and Ronei J. Poppi. "Surface-enhanced Raman spectroscopy and MCR-ALS for the selective sensing of urinary adenosine on filter paper." Talanta 187 (September 2018): 99–105. http://dx.doi.org/10.1016/j.talanta.2018.05.022.

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Simpson, John V., Gurusamy Balakrishnan, and Renee D. JiJi. "MCR-ALS analysis of two-way UV resonance Raman spectra to resolve discrete protein secondary structural motifs." Analyst 134, no. 1 (2009): 138–47. http://dx.doi.org/10.1039/b814392g.

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Karadag, Ahmet, Ersin Kaygisiz, Timur Nikitin, Sinan Ongen, Gulce Ogruc Ildiz, Namik Aysal, Ayberk Yilmaz, and Rui Fausto. "Micro-Raman Spectroscopy and X-ray Diffraction Analyses of the Core and Shell Compartments of an Iron-Rich Fulgurite." Molecules 27, no. 10 (May 10, 2022): 3053. http://dx.doi.org/10.3390/molecules27103053.

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Fulgurites are naturally occurring structures that are formed when lightning discharges reach the ground. In this investigation, the mineralogical compositions of core and shell compartments of a rare, iron-rich fulgurite from the Mongolian Gobi Desert were investigated by X-ray diffraction and micro-Raman spectroscopy. The interpretation of the Raman data was helped by chemometric analysis, using both multivariate curve resolution (MCR) and principal component analysis (PCA), which allowed for the fast identification of the minerals present in each region of the fulgurite. In the core of the fulgurite, quartz, microcline, albite, hematite, and barite were first identified based on the Raman spectroscopy and chemometrics analyses. In contrast, in the shell compartment of the fulgurite, the detected minerals were quartz, a mixture of the K-feldspars orthoclase and microcline, albite, hematite, and goethite. The Raman spectroscopy results were confirmed by X-ray diffraction analysis of powdered samples of the two fulgurite regions, and are consistent with infrared spectroscopy data, being also in agreement with the petrographic analysis of the fulgurite, including scanning electron microscopy with backscattering electrons (SEM-BSE) and scanning electron microscopy with energy dispersive X-ray (SEM-EDX) data. The observed differences in the mineralogical composition of the core and shell regions of the studied fulgurite can be explained by taking into account the effects of both the diffusion of the melted material to the periphery of the fulgurite following the lightning and the faster cooling at the external shell region, together with the differential properties of the various minerals. The heavier materials diffused slower, leading to the concentration in the core of the fulgurite of the iron and barium containing minerals, hematite, and barite. They first underwent subsequent partial transformation into goethite due to meteoric water within the shell of the fulgurite. The faster cooling of the shell region kinetically trapped orthoclase, while the slower cooling in the core area allowed for the extensive formation of microcline, a lower temperature polymorph of orthoclase, thus justifying the prevalence of microcline in the core and a mixture of the two polymorphs in the shell. The total amount of the K-feldspars decreases only slightly in the shell, while quartz and albite appeared in somewhat larger amounts in this compartment of the fulgurite. On the other hand, at the surface of the fulgurite, barite could not be stabilized due to sulfate lost (in the form of SO2 plus O2 gaseous products). The conjugation of the performed Raman spectroscopy experiments with the chemometrics analysis (PCA and, in particular, MCR analyses) was shown to allow for the fast identification of the minerals present in the two compartments (shell and core) of the sample. This way, the XRD experiments could be done while knowing in advance the minerals that were present in the samples, strongly facilitating the data analysis, which for compositionally complex samples, such as that studied in the present investigation, would have been very much challenging, if possible.

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Hisazumi, Jin, and Peter Kleinebudde. "In-line monitoring of multi-layered film-coating on pellets using Raman spectroscopy by MCR and PLS analyses." European Journal of Pharmaceutics and Biopharmaceutics 114 (May 2017): 194–201. http://dx.doi.org/10.1016/j.ejpb.2017.01.017.

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Fornasaro, Stefano, Annalisa Vicario, Luigina De Leo, Alois Bonifacio, Tarcisio Not, and Valter Sergo. "Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies." Integrative Biology 10, no. 6 (2018): 356–63. http://dx.doi.org/10.1039/c8ib00028j.

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Hancewicz, Thomas M., Chunhong Xiao, Shuliang Zhang, and Manoj Misra. "Improved Modeling of in Vivo Confocal Raman Data Using Multivariate Curve Resolution (MCR) Augmentation of Ordinary Least Squares Models." Applied Spectroscopy 67, no. 12 (December 2013): 1463–72. http://dx.doi.org/10.1366/12-06815.

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35

Ghosh, Nishith, Subhadip Roy, Mohammed Ahmed, and Jahur A. Mondal. "Water in the hydration shell of cryoprotectants and their non-cryoprotecting structural analogues as observed by Raman-MCR spectroscopy." Journal of Molecular Liquids 266 (September 2018): 118–21. http://dx.doi.org/10.1016/j.molliq.2018.06.073.

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36

Cordeiro Dantas, Willian Francisco, Julio Cesar Laurentino Alves, and Ronei Jesus Poppi. "MCR-ALS with correlation constraint and Raman spectroscopy for identification and quantification of biofuels and adulterants in petroleum diesel." Chemometrics and Intelligent Laboratory Systems 169 (October 2017): 116–21. http://dx.doi.org/10.1016/j.chemolab.2017.04.002.

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37

Xie, Yong, Wenjin Cao, Sampathkumar Krishnan, Hong Lin, and Nina Cauchon. "Characterization of Mannitol Polymorphic Forms in Lyophilized Protein Formulations Using a Multivariate Curve Resolution (MCR)-Based Raman Spectroscopic Method." Pharmaceutical Research 25, no. 10 (June 4, 2008): 2292–301. http://dx.doi.org/10.1007/s11095-008-9624-1.

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38

More, Yogesh W., Sunil U. Tekale, Nitishkumar S. Kaminwar, László Kótai, Tibor Pasinszki, Pravin S. Kendrekar, and Rajendra P. Pawar. "Synthesis of 3,4-Dihydropyrano[c]chromenes Using Carbon Microsphere Supported Copper Nanoparticles (Cu-NP/C) Prepared from Loaded Cation Exchange Resin as a Catalyst." Current Organic Synthesis 16, no. 2 (March 26, 2019): 288–93. http://dx.doi.org/10.2174/1570179415666181116104931.

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Aim and Objective: The present study was performed with the aim to develop an efficient and environmentally benign protocol for the synthesis of biologically siginifcant 3, 4-dihydropyrano[c]chromenes using a new catalytic material. The protocol involves the use of a reusable, environment friendly materials and solvents with operational simplicity. Materials and Methods: Carbon microsphere supported copper nanoparticles (Cu-NP/C) prepared from loaded cation exchange resin were synthesized, characterized with well versed analytical techniques such as XRD, SEM and Raman spectroscopy and the synthesized material was used as a catalyst for the environmentally benign synthesis of 3,4-dihydropyrano[c]chromenes. Results: The formation of carbon microsphere supported copper nanoparticles (Cu-NP/C) prepared from loaded cation exchange resin was confirmed by XRD, SEM and Raman spectroscopy which was employed as a heterogeneous material for the synthesis of 3,4-dihydropyrano[c]chromenes. The products formed were characterized by the analysis of spectroscopic data - NMR, IR and mass. The safe catalytic system offers several advantages including operational simplicity, environmental friendliness, high yield, and reusability of catalyst and green chemical transformation. Conclusion: Herein we report an easy and efficient protocol for the one-pot synthesis of dihydropyrano[ c]chromenes using environmentally benign MCR approach in ethanol as the green solvent. The method developed herein constitutes a valuable addition to the existing methods for the synthesis of titled compounds.

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Legner, Robin, Alexander Wirtz, and Martin Jaeger. "Using Compact 1H NMR, NIR, and Raman Spectroscopy Combined with Multivariate Data Analysis to Monitor a Biocatalyzed Reaction in a Microreaction System." Journal of Spectroscopy 2018 (December 2, 2018): 1–11. http://dx.doi.org/10.1155/2018/5120789.

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Process analytical technology aims at process knowledge and process improvement, efficiency, and sustainability. A prerequisite is process monitoring. The combination of microreaction systems and spectroscopy proved suitable due to dimension and compound reduction and real-time monitoring capabilities. Compact 1H NMR, NIR, and Raman spectroscopy were used to monitor the biocatalyzed hydrolysis and esterification of acetic anhydride to isoamyl acetate using immobilized Candida antarctica lipase B (CALB) in a microreaction system in real-time. To facilitate the identification of signals suitable for the extraction of concentration-time (c-t) graphs, 2D heterocorrelation spectra were generated through covariance transformations applied to 1D Raman, NIR, and NMR data. By means of this purely mathematical statistical procedure, the relevant signals of the process media were assigned to educts and products and thus made applicable for univariate data evaluation. The data obtained were interpreted in terms of a first-order kinetic model, and corresponding reaction rate constants were extracted. An alternative, elegant, and fit-for-automation approach for the kinetic analysis of the spectra was demonstrated in using multivariate curve resolution (MCR). The results of the univariate and multivariate approaches were comparable with regard to reaction rates and concentrations. While the manual integration of the 1H NMR spectra followed by univariate analysis allowed to establish a concentration profile of the final product isoamyl acetate hence revealing more details, multivariate analysis was found more suitable for process automation.

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Haddad, Abed, Diana Hartman, and Ana Martins. "Complex Relationships: A Materials Study of Édouard Vuillard’s Interior, Mother and Sister of the Artist." Heritage 4, no. 4 (September 30, 2021): 2903–17. http://dx.doi.org/10.3390/heritage4040162.

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Édouard Vuillard (1868–1949) is well known for his small atmospheric paintings, often portraying his own home and family as the subject matter. Interior, Mother and Sister of the Artist (1893) underwent at least one restoration treatment before being acquired by the Museum of Modern Art (MoMA) in 1934. The painting was treated again in 1954, but no analysis was carried out to understand the artist’s methods and materials at that time. To better understand the choices of Vuillard in Interior, Mother and Sister of the Artist, a comprehensive suite of imaging and spectroscopic analyses was undertaken, including: XRR, UVF and IRR Photography, XRF, Raman spectroscopy and SERS, and µ-FTIR. Statistical analysis on the XRF data using MCR-ALS further revealed some of the intricacies of Vuillard’s technique and color choices, where a large number of pigments were used in designing this intimate composition, including lead white, zinc white, bone black, ochre, umber, vermilion, Geranium lake, red lead, ultramarine, Prussian blue, chrome yellow, chrome orange, zinc yellow, strontium yellow, cadmium yellow, and a chromium oxide green.

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SAEKI, Morihisa, Takumi YOMOGIDA, Daiju MATSUMURA, Takumi SAITO, Ryuzo NAKANISHI, Takuya TSUJI, and Hironori OHBA. "Application of an Augmentation Method to MCR-ALS Analysis for XAFS and Raman Data Matrices in the Structural Change of Isopolymolybdates." Analytical Sciences 36, no. 11 (November 10, 2020): 1371–78. http://dx.doi.org/10.2116/analsci.20p147.

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42

Zhang, Lesheng, Tom Cambron, Yueqing Niu, Zigang Xu, Ning Su, Hongyan Zheng, Karl Wei, and Paula Ray. "MCR Approach Revealing Protein, Water, and Lipid Depth Profile in Atopic Dermatitis Patients’ Stratum Corneum via in Vivo Confocal Raman Spectroscopy." Analytical Chemistry 91, no. 4 (January 23, 2019): 2784–90. http://dx.doi.org/10.1021/acs.analchem.8b04597.

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43

Paidi, Santosh K., Joel R. Troncoso, Narasimhan Rajaram, and Ishan Barman. "Abstract 1943: Elucidating early tumor microenvironmental changes due to immunotherapy with label-free Raman spectroscopy and machine learning." Cancer Research 82, no. 12_Supplement (June 15, 2022): 1943. http://dx.doi.org/10.1158/1538-7445.am2022-1943.

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Abstract Clinical benefit is observed in only a limited fraction of patients that undergo immunotherapy for a variety of cancer types. Therefore, the determination of robust biomarkers for accurate prediction of response to immunotherapeutic agents remains one of the grand challenges of 21st century. Our primary goal was to investigate if phenotypic differences due to treatment with ICI can be recognized with minimally perturbative molecular tools and guide personalization of immunotherapy. In this work, we provide first-in-class evidence that Raman spectroscopy (an optical method) and machine learning allows sensitive detection of early changes in biomolecular composition of tumors in response to immunotherapy with immune checkpoint inhibitors (ICI). By studying the widely investigated CT26 murine model of colorectal cancer treated with anti-CTLA-4 (n = 8) and anti-PD-L1 (n = 7) ICIs and controls (n = 10), we revealed new biological insights into the nature and degree of microenvironmental modifications induced by exposure to clinically relevant doses of ICI. Multivariate curve resolution-alternating least squares (MCR-ALS) decomposition of Raman spectral datasets revealed early changes in lipid, nucleic acid, and collagen content of the tumors following therapy. We trained supervised classification models - support vector machines and random forests on the spectral datasets and showed that the models provided excellent prediction accuracies for response to both ICIs and delineated spectral markers specific to each therapy, consistent with their differential mechanisms of action. On the basis of these findings, we sought to determine if the tumor microenvironment changes delineated by Raman spectroscopy correspond to proteomic alterations via quantitative mass spectrometry. Of the more than 6600 proteins identified, about 136 proteins were found to be significantly different in treated tumors relative to controls (p < 0.05 and log2 fold change of > 2). A subset of these differentially expressed proteins is known to regulate lipid metabolism and extracellular matrix composition, while others are known to control transcriptome dynamics or are associated with response to ICI therapy, thereby corroborating our Raman spectroscopic measurements. Our observation of biomolecular changes in the TME should catalyze detailed investigations for translating such markers and label-free Raman spectroscopy for clinical monitoring of immunotherapy response in cancer patients. Citation Format: Santosh K. Paidi, Joel R. Troncoso, Narasimhan Rajaram, Ishan Barman. Elucidating early tumor microenvironmental changes due to immunotherapy with label-free Raman spectroscopy and machine learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1943.

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Castro, Rafael C., David S. M. Ribeiro, João L. M. Santos, and Ricardo N. M. J. Páscoa. "Comparison of near infrared spectroscopy and Raman spectroscopy for the identification and quantification through MCR-ALS and PLS of peanut oil adulterants." Talanta 230 (August 2021): 122373. http://dx.doi.org/10.1016/j.talanta.2021.122373.

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45

Saha, Subhamoy, Subhadip Roy, P. Mathi, and Jahur A. Mondal. "Polyatomic Iodine Species at the Air–Water Interface and Its Relevance to Atmospheric Iodine Chemistry: An HD-VSFG and Raman-MCR Study." Journal of Physical Chemistry A 123, no. 13 (March 4, 2019): 2924–34. http://dx.doi.org/10.1021/acs.jpca.9b00828.

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Soares, Frederico Luis Felipe, Benedito Roberto de Alvarenga Junior, and Renato Lajarim Carneiro. "SERS-TLC Device for Simultaneous Determination of Sulfamethoxazole and Trimethoprim in Milk." Chemosensors 10, no. 12 (December 12, 2022): 528. http://dx.doi.org/10.3390/chemosensors10120528.

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The aim of this work is to develop a device based on thin-layer chromatography coupled with surface-enhanced Raman spectroscopy (TLC-SERS) to analyze sulfamethoxazole (SMX) and trimethoprim (TMP) in commercial milk samples using chemometric tools. Samples were eluted in TLC plates, and a central composite design (CCD) of two factors was performed to optimize the gold nanoparticle dispersion on TLC plates for SERS, aiming at the detection of both drugs at concentrations close to their maximum residual limits (MRLs). Following the optimization, hyperspectral images from the SERS were captured of the TLC plates. Multivariate curve resolution (MCR-ALS) and independent component analysis (ICA) chemometric techniques were used to extract the signals of the analytes. All the samples presented recovery values of 81–128% for TMP. The quantification of SMX was not possible due to SERS suppression by an interferent. However, it was possible to detect SMX at a concentration of two times the MRL (8.0 × 10−7 mol·L−1). The results demonstrate that the TLC-SERS device is a potential tool for the quantification of TMP and the detection of SMX in milk.

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Marro, Monica, Claudia Nieva, Anna de Juan, and Angels Sierra. "Unravelling the Metabolic Progression of Breast Cancer Cells to Bone Metastasis by Coupling Raman Spectroscopy and a Novel Use of Mcr-Als Algorithm." Analytical Chemistry 90, no. 9 (March 28, 2018): 5594–602. http://dx.doi.org/10.1021/acs.analchem.7b04527.

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48

Smith, Joseph P., Frank C. Smith, Joshua Ottaway, Alexandra E. Krull-Davatzes, Bruce M. Simonson, Billy P. Glass, and Karl S. Booksh. "Raman Microspectroscopic Mapping with Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) Applied to the High-Pressure Polymorph of Titanium Dioxide, TiO2-II." Applied Spectroscopy 71, no. 8 (March 7, 2017): 1816–33. http://dx.doi.org/10.1177/0003702816687573.

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49

Ruiz, José Javier, Monica Marro, Ismael Galván, José Bernabeu-Wittel, Julián Conejo-Mir, Teresa Zulueta-Dorado, Ana Belén Guisado-Gil, and Pablo Loza-Álvarez. "Novel Non-Invasive Quantification and Imaging of Eumelanin and DHICA Subunit in Skin Lesions by Raman Spectroscopy and MCR Algorithm: Improving Dysplastic Nevi Diagnosis." Cancers 14, no. 4 (February 18, 2022): 1056. http://dx.doi.org/10.3390/cancers14041056.

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Malignant melanoma (MM) is the most aggressive form of skin cancer, and around 30% of them may develop from pre-existing dysplastic nevi (DN). Diagnosis of DN is a relevant clinical challenge, as these are intermediate lesions between benign and malignant tumors, and, up to date, few studies have focused on their diagnosis. In this study, the accuracy of Raman spectroscopy (RS) is assessed, together with multivariate analysis (MA), to classify 44 biopsies of MM, DN and compound nevus (CN) tumors. For this, we implement a novel methodology to non-invasively quantify and localize the eumelanin pigment, considered as a tumoral biomarker, by means of RS imaging coupled with the Multivariate Curve Resolution-Alternative Least Squares (MCR-ALS) algorithm. This represents a step forward with respect to the currently established technique for melanin analysis, High-Performance Liquid Chromatography (HPLC), which is invasive and cannot provide information about the spatial distribution of molecules. For the first time, we show that the 5, 6-dihydroxyindole (DHI) to 5,6-dihydroxyindole-2-carboxylic acid (DHICA) ratio is higher in DN than in MM and CN lesions. These differences in chemical composition are used by the Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm to identify DN lesions in an efficient, non-invasive, fast, objective and cost-effective method, with sensitivity and specificity of 100% and 94.1%, respectively.

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Mitsutake, Hery, Lígia N. M. Ribeiro, Gustavo H. Rodrigues da Silva, Simone R. Castro, Eneida de Paula, Ronei J. Poppi, and Márcia C. Breitkreitz. "Evaluation of miscibility and polymorphism of synthetic and natural lipids for nanostructured lipid carrier (NLC) formulations by Raman mapping and multivariate curve resolution (MCR)." European Journal of Pharmaceutical Sciences 135 (July 2019): 51–59. http://dx.doi.org/10.1016/j.ejps.2019.05.002.

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