In this study, Raman spectroscopy is employed for the characterization and comparison of two different classes of exo-polysaccharides including glucans and fructans which are produced by different bacteria. For this purpose, nine samples are used including five samples of glucans and four of fructans. Raman spectral results of all these polysaccharides show clear differences among various glucans as well as fructans showing the potential of this technique to identify the differences within the same class of the compounds. Moreover, these two classes are also compared on the basis of their Raman spectral data and can be differentiated on the basis of their unique Raman features. Multivariate data analysis techniques, Principle Component Analysis (PCA) is found very helpful for the comparison of the Raman spectral data of these classes of the carbohydrates.
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http://dx.doi.org/10.1016/j.saa.2020.118408 | DOI Listing |
Sensors (Basel)
December 2024
CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany.
Advancements in Raman light sheet microscopy have provided a powerful, non-invasive, marker-free method for imaging complex 3D biological structures, such as cell cultures and spheroids. By combining 3D tomograms made by Rayleigh scattering, Raman scattering, and fluorescence detection, this modality captures complementary spatial and molecular data, critical for biomedical research, histology, and drug discovery. Despite its capabilities, Raman light sheet microscopy faces inherent limitations, including low signal intensity, high noise levels, and restricted spatial resolution, which impede the visualization of fine subcellular structures.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
School of Physics, Changchun University of Science and Technology, Changchun 130012, China.
Tungsten oxide (WO) electrochromic devices are obtaining increasing interest due to their color change and thermal regulation. However, most previous work focuses on the absorption or transmission spectra of materials, rather than the optical parameters evolution in full spectrum in the electrochromic processes. Herein, we developed a systematic protocol of ex situ methods to clarify the evolutions of subtle structure changes, Raman vibration modes, and optical parameters of WO thin films in electrochromic processes as stimulated by dosage-dependent Li insertion.
View Article and Find Full Text PDFMolecules
December 2024
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.
The rapid and precise identification of microorganisms is essential in environmental science, pharmaceuticals, food safety, and medical diagnostics. Raman spectroscopy, valued for its ability to provide detailed chemical and structural information, has gained significant traction in these fields, especially with the adoption of various excitation wavelengths and tailored optical setups. The choice of wavelength and setup in Raman spectroscopy is influenced by factors such as applicability, cost, and whether bulk or single-cell analysis is performed, each impacting sensitivity and specificity in bacterial detection.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Leibniz-Institute of Photonic Technology (Leibniz-IPHT), Albert-Einstein-Str. 9, 07745 Jena, Germany.
Colorectal cancer is one of the most prevalent forms of cancer globally. The most common routine diagnostic methods are the examination of the interior of the colon during colonoscopy or sigmoidoscopy, which frequently includes the removal of a biopsy sample. Optical methods, such as Raman spectroscopy (RS) and optical coherence tomography (OCT), can help to improve diagnostics and reduce the number of unnecessary biopsies.
View Article and Find Full Text PDFFoods
December 2024
School of Physical Science and Technology, Tiangong University, Tianjin 300387, China.
The fast and accurate quantitative detection of camellia oil products is significant for multiple reasons. In this study, rice bran oil and corn oil, whose Raman spectra both hold great similarities with camellia oil, are blended with camellia oil, and the concentration of each composition is predicted by models with varying feature extraction methods and regression algorithms. Back propagation neural network (BPNN), which has been rarely investigated in previous work, is used to construct regression models, the performances of which are compared with models using random forest (RF) and partial least squares regression (PLSR).
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