Measurement of cartilage sub‐component distributions through the surface by Raman spectroscopy‐based multivariate analysis

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Daniel Mason ◽  
Sangeeta Murugkar ◽  
Andrew D. Speirs
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Analysis

scholarly journals Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Siti Norbaini Sabtu ◽  
S. F. Abdul Sani ◽  
L. M. Looi ◽  
S. F. Chiew ◽  
Dharini Pathmanathan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Nucleic Acids ◽  
Raman Spectra ◽  
Cancer Progression ◽  
Component Analysis ◽  
Breast Cancer Tissue ◽  
Metabolic Changes ◽  
Cancer Tissue

AbstractThe epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600–1800 cm−1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey’s multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

In-line reaction monitoring of entacapone synthesis by Raman spectroscopy and multivariate analysis

2011 ◽  
Vol 54 (4) ◽  
pp. 660-666 ◽  
Author(s):  
Predrag Novak ◽  
Andrea Kišić ◽  
Tomica Hrenar ◽  
Tomislav Jednačak ◽  
Snežana Miljanić ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Reaction Monitoring

Precise Determination of Percent Cure of Epoxide Polymers and Composites via Fiber-Optic Raman Spectroscopy and Multivariate Analysis

1997 ◽  
Vol 51 (2) ◽  
pp. 247-252 ◽  
Author(s):  
Jeffrey F. Aust ◽  
Karl S. Booksh ◽  
Christopher M. Stellman ◽  
Richard S. Parnas ◽  
Michael L. Myrick
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Real Time ◽  
Fiber Optic ◽  
Precise Determination ◽  
Probe Design ◽  
Epoxide Polymers ◽  
Time Determination

A method for real-time determination of the percent cure of epoxies via in situ fiber-optic Raman spectroscopy has been developed. This method utilizes a probe design developed for real-time monitoring of polymer curing and multivariate analysis to interpret the data and determine percent cure. This method was demonstrated to be reliable to ±0.54% of cure in laboratory samples over a 50–99% cure range. A preliminary study measuring cure percentage in an industrial, glass-reinforced composite has been shown to be reliable to ±0.82% in the 40–90% cure range.

Multivariate Analysis of Mixed Lipid Aggregate Phase Transitions Monitored Using Raman Spectroscopy

2017 ◽  
Vol 72 (1) ◽  
pp. 102-113 ◽  
Author(s):  
Sharon L. Neal
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Minor Component ◽  
Data Matrix ◽  
Melting Transition ◽  
Spectral Features ◽  
Temperature Dependent ◽  
Spectral Parameters ◽  
Spectral Matrix ◽  
Lipid Response

The phase behavior of aqueous 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC)/1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) mixtures between 8.0 ℃ and 41.0 ℃ were monitored using Raman spectroscopy. Temperature-dependent Raman matrices were assembled from series of spectra and subjected to multivariate analysis. The consensus of pseudo-rank estimation results is that seven to eight components account for the temperature-dependent changes observed in the spectra. The spectra and temperature response profiles of the mixture components were resolved by applying a variant of the non-negative matrix factorization (NMF) algorithm described by Lee and Seung (1999). The rotational ambiguity of the data matrix was reduced by augmenting the original temperature-dependent spectral matrix with its cumulative counterpart, i.e., the matrix formed by successive integration of the spectra across the temperature index (columns). Successive rounds of constrained NMF were used to isolate component spectra from a significant fluorescence background. Five major components exhibiting varying degrees of gel and liquid crystalline lipid character were resolved. Hydrogen-bonded water networks exhibiting varying degrees of organization are associated with the lipid components. Spectral parameters were computed to compare the chain conformation, packing, and hydration indicated by the resolved spectra. Based on spectral features and relative amounts of the components observed, four components reflect long chain lipid response. The fifth component could reflect the response of the short chain lipid, DHPC, but there were no definitive spectral features confirming this assignment. A minor component of uncertain assignment that exhibits a striking response to the DMPC pre-transition and chain melting transition also was recovered. While none of the spectra resolved exhibit features unequivocally attributable to a specific aggregate morphology or step in the gelation process, the results are consistent with the evolution of mixed phase bicelles (nanodisks) and small amounts of worm-like DMPC/DHPC aggregates, and perhaps DHPC micelles, at low temperature to suspensions of branched and entangled worm-like aggregates above the DMPC gel phase transition and perforated multi-lamellar aggregates at high temperature.

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