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In this work, we describe a methodology to visualize the biochemical markers of atherosclerotic plaque in cross sections of brachiocephalic arteries (BCA) taken from ApoE/LDLR(-/-) mice. The approach of the visualization of the same area of atherosclerotic plaque with the use of Raman, IR and AFM imaging enables the parallel characterisation of various features of atherosclerotic plaques. This support to the histochemical staining is utilized mainly in studies on mice models of atherosclerotic plaques, where micro and sub-micro resolutions are required. This work presents the methodology of the measurement and visualization of plaque features important for atherosclerosis development and plaques vulnerability analysis. Label-free imaging of cholesterol, cholesteryl esters, remodeled media, heme, internal elastic lamina, fibrous cap and calcification provides additional knowledge to previously presented quantitative measurements of average plaque features. AFM imaging enhanced the results obtained with the use of vibrational microspectroscopies with additional topographical information of the sample. To the best of our knowledge, this is the first work which demonstrates that co-localized measurement of atherosclerotic plaque with Raman, IR and AFM imaging provides a comprehensive insight into the biochemical markers of atherosclerotic plaques, and can be used as an integrated approach to assess vulnerability of the plaque.

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Spectroscopy-based approaches can provide an insight into the biochemical composition of a tissue sample. In the present work Fourier transform infrared (FT-IR) spectroscopy was used to develop a reliable methodology to study the content of free fatty acids, triglycerides, cholesteryl esters as well as cholesterol in aorta from mice with atherosclerosis (ApoE/LDLR(-/-) mice). In particular, distribution and concentration of palmitic, oleic and linoleic acid derivatives were analyzed. Spectral analysis of pure compounds allowed for clear discrimination between free fatty acids and other similar moieties based on the carbonyl band position (1699-1710 cm(-1) range). In order to distinguish cholesteryl esters from triglycerides a ratio of carbonyl band to signal at 1010 cm(-1) was used. Imaging of lipids in atherosclerotic aortic lesions in ApoE/LDLR(-/-) mice was followed by Hierarchical Cluster Analysis (HCA). The aorta from C57Bl/6J control mice (fed with chow diet) was used for comparison. The measurements were completed with an FT-IR spectrometer equipped with a 128 × 128 FPA detector. In cross-section of aorta from ApoE/LDLR(-/-) mice a region of atherosclerotic plaque was clearly identified by HCA, which was later divided into 2 sub-regions, one characterized by the higher content of cholesterol, while the other by higher contents of cholesteryl esters. HCA of tissues deposited on normal microscopic glass, hence limited to the 2200-3800 cm(-1) spectral range, also identified a region of atherosclerotic plaque. Importantly, this region correlates with the area stained by standard histological staining for atherosclerotic plaque (Oil Red O). In conclusion, the use of FT-IR and HCA may provide a novel tool for qualitative and quantitative analysis of contents and distribution of lipids in atherosclerotic plaque.

Nanocrystals composed of mixed chemical domains have diverse properties that are driving their integration in next-generation electronics, light sources, and biosensors. However, the precise spatial distribution of elements within these particles is difficult to measure and control, yet profoundly impacts their quality and performance. Here we synthesized a unique series of 42 different quantum dot nanocrystals, composed of two chemical domains (CdS:CdSe), arranged in 7 alloy and (core)shell structural classes. Chemometric analyses of far-field Raman spectra accurately classified their internal structures from their vibrational signatures. These classifications provide direct insight into the elemental arrangement of the alloy as well as an independent prediction of fluorescence quantum yield. This nondestructive, rapid approach can be broadly applied to greatly enhance our capacity to measure, predict and monitor multicomponent nanomaterials for precise tuning of their structures and properties.