Raman Spectroscopic Imaging of Cholesterol and Docosahexaenoic Acid Distribution in the Retinal Rod Outer Segment

Schultz, Zachary D.

doi:10.1071/ch11019

Cited by 18 publications

(8 citation statements)

References 57 publications

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“…The loadings of the first principal component PC 1 (Fig. 10b) have frequencies and relative intensities, which are well matched to those of docosahexaenoic acid and one of its esters [59], [63], [64].…”

Section: Resultsmentioning

confidence: 98%

New Insights on Cytological and Metabolic Features of Ostreopsis cf. ovata Fukuyo (Dinophyceae): A Multidisciplinary Approach

et al. 2013

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The harmful dinoflagellate Ostreopsis cf. ovata has been causing toxic events along the Mediterranean coasts and other temperate and tropical areas, with increasing frequency during the last decade. Despite many studies, important biological features of this species are still poorly known. An integrated study, using different microscopy and molecular techniques, Raman microspectroscopy and high resolution liquid chromatography-mass spectrometry (HR LC-MS), was undertaken to elucidate cytological aspects, and identify main metabolites including toxins. The species was genetically identified as O. cf. ovata, Atlantic-Mediterranean clade. The ultrastructural results show unique features of the mucilage network abundantly produced by this species to colonize benthic substrates, with a new role of trichocysts, never described before. The amorphous polysaccharidic component of mucilage appears to derive from pusule fibrous material and mucocysts. In all stages of growth, the cells show an abundant production of lipids. Different developmental stages of chloroplasts are found in the peripheral cytoplasm and in the centre of cell. In vivo Raman microspectroscopy confirms the presence of the carotenoid peridinin in O. cf. ovata, and detects in several specimen the abundant presence of unsaturated lipids structurally related to docosahexaenoic acid. The HR LC-MS analysis reveals that ovatoxin-a is the predominant toxin, together with decreasing amounts of ovatoxin-b, -d/e, -c and putative palytoxin. Toxins concentration on a per cell basis increases from exponential to senescent phase. The results suggest that benthic blooms of this species are probably related to features such as the ability to create a unique mucilaginous sheath covering the sea bottom, associated with the production of potent toxins as palytoxin-like compounds. In this way, O. cf. ovata may be able to rapidly colonize benthic substrates outcompeting other species.

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Section: Resultsmentioning

confidence: 98%

New Insights on Cytological and Metabolic Features of Ostreopsis cf. ovata Fukuyo (Dinophyceae): A Multidisciplinary Approach

et al. 2013

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“…Bile acid spectra are significantly less intense than that of R6G measured using the same substrates, which was expected given the low Raman cross-sections reported for similar steroid-like molecules. 55 Furthermore, since they share several functional groups with Raman bands in the same locations, the challenge posed by the identification of one species from another is an excellent opportunity to evaluate the performance of the CNN model. In particular, the spectra measured for bile acid species CA and GCDCA and the blank substrate were exceedingly similar.…”

Section: Resultsmentioning

confidence: 99%

Pushing the Limits of Surface-Enhanced Raman Spectroscopy (SERS) with Deep Learning: Identification of Multiple Species with Closely Related Molecular Structures

et al. 2022

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Raman spectroscopy is a non-destructive and label-free molecular identification technique capable of producing highly specific spectra with various bands correlated to molecular structure. Moreover, the enhanced detection sensitivity offered by Surface-Enhanced Raman spectroscopy (SERS) allows analyzing mixtures of related chemical species in a relatively short measurement time. Combining SERS with deep learning algorithms allows in some cases to increase detection and classification capabilities even further. The present study evaluates the potential of applying deep learning algorithms to SERS spectroscopy to differentiate and classify different species of bile acids, a large family of molecules with low Raman cross sections and molecular structures that often differ by a single hydroxyl group. Moreover, the study of these molecules is of interest for the medical community since they have distinct pathological roles and are currently viewed as potential markers of gut microbiome imbalances. A Convolutional Neural Network (CNN) model was developed and used to classify SERS spectra from five bile acid species. The model succeeded in identifying the five analytes despite very similar molecular structures and was found to be reliable even at low analyte concentrations.

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“…While in the endometriosis group (Figure 4G), no spectral cluster could be separated to contain similar band intensity. The mean spectra of the separated cluster of the control group were depicted in Figure 4I, revealing Raman features at 701, 1442 and 1674 cm −1 , which were the most intense cholesterol Raman bands 23,24 . Though the collected Raman spectra were a contribution of many macromolecules, the molecule of higher concentration would have a stronger contribution to the spectra in terms of band intensities, such as in the cholesterol cluster (Figure 4I).…”

Section: Resultsmentioning

confidence: 99%

Single‐cell Raman trapping analysis revealed immunometabolism changes in peritoneal fluid in endometriosis

et al. 2021

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In endometriosis, an aberrant immune response in the peritoneal environment is evident, but the underlying mechanism remains unclear. In recent years, some emerging data support an important role for the changes in intracellular metabolic pathways of immune cells in controlling their function. In this study, we aim to investigate the phenotypic and immunometabolism profiling of peritoneal fluid cells in endometriosis patients. By flow cytometry, our results show phenotypic profiling of peritoneal fluid cells with higher percentages of CD45+, CD3+, CD3+CD8+, CD3+CD56+, and CD14+CD68+ cells and the ratio of M2 to M1 macrophages but less CD14−CD86+ dendritic cells in endometriosis when compared with control. Label‐free single‐cell Raman trapping analysis shows intracellular changes in decreased collagen, proteins and lipids levels in CD45+ immune cells in endometriosis. In the supernatant of peritoneal fluid from endometriosis patients, Raman results reveal extracellular decreased protein and carbohydrate levels but increased lipid and fatty acid levels. Especially, Raman bands indicate both intracellular and extracellular levels of cholesterol and carotenoids decrease in endometriosis patients when compared with controls. This study provides immunometabolism features of the specific microenvironment in the peritoneal cavity and identifies some biological molecules associated with immune dysfunction in endometriosis, which may offer new clues for understanding disease pathology and therapeutic targets.

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Raman Spectroscopic Imaging of Cholesterol and Docosahexaenoic Acid Distribution in the Retinal Rod Outer Segment

Cited by 18 publications

References 57 publications

New Insights on Cytological and Metabolic Features of Ostreopsis cf. ovata Fukuyo (Dinophyceae): A Multidisciplinary Approach

New Insights on Cytological and Metabolic Features of Ostreopsis cf. ovata Fukuyo (Dinophyceae): A Multidisciplinary Approach

Pushing the Limits of Surface-Enhanced Raman Spectroscopy (SERS) with Deep Learning: Identification of Multiple Species with Closely Related Molecular Structures

Single‐cell Raman trapping analysis revealed immunometabolism changes in peritoneal fluid in endometriosis

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