In vivo isotopically labeled atherosclerotic aorta plaques in ApoE KO mice and molecular profiling by matrix‐assisted laser desorption/ionization mass spectrometric imaging

Abstract

The ability to couple stable isotope based protocols with MALDI-MSI enables a novel strategy to characterize the effects of therapeutic treatments on atherosclerotic plaque formation, regression and potential remodeling of the complex lipid components with high chemical specificity and spatiotemporal information.

Three‐dimensional imaging MS of lipids in atherosclerotic plaques: Open‐source methods for reconstruction and analysis

“…Therefore, applying advanced tissue characterization techniques can help unravel the biology of atherosclerosis. Indeed, IMS has been applied to atherosclerosis using SIMS imaging [23][24][25][26] and MALDI IMS [27][28][29]. A 3D reconstruction was performed using SIMS on a mouse heart [30].…”

Detection of Localized Hepatocellular Amino Acid Kinetics by using Mass Spectrometry Imaging of Stable Isotopes

“…It was demonstrated that rates of lipid synthesis are altered in different tumor cell subpopulations, thus highlighting the need to study localized synthesis kinetics in tumor metabolism. In addition, MALDI‐MSI in combination with stable isotopes has been applied to study the formation of atherosclerotic plaques and the nitrogen cycle within plants …”

MALDI mass spectrometric imaging meets “omics”: recent advances in the fruitful marriage

“…In the case of head and neck cancer, the spatial molecular characterization is important, since half of the patients develop a locoregional recurrence although radical therapy was prescribed. 147 Besides, cancer applications, various other diseases, such as infections of hepatitis B virus, 81 atherosclerosis, 148 fabry, 79 peridontal, 149 alzheimer's, [150][151][152] epilepsia, 153 stroke, 154 schizophrenia, 155 and stargardt disease 82 have been investigated to shade light into the underlying disease mechanism. 50 With the help of computational algorithms, the head and neck tissue sample was subdivided into six clusters based on the spectral similarities (Figure 3 A).…”