Introduction
One goal of research in the field of vascular biology is a better understanding of the genetic causes behind vascular diseases like atherosclerosis and aneurysms. Methods of molecular biology, such as mouse models, are exploited to investigate inherited genetic variations which promote smooth muscle cell dysfunction and can lead to heart attack or aneurysm rupture [1-3]. The ultimate goal would be early-phase clinical research. Discoveries that lead to a better comprehension of the molecular mechanisms that effect vascular disease may one day be translated into therapies for them [1-3]. The results presented here show that the lamina, vascular cells, and nuclei of mouse aorta are more clearly resolved with a THUNDER Imager Tissue using Computational Clearing (CC) compared to conventional widefield microscopy.
Challenges
For this vascular disease research, it is practical to have an imaging solution that can quickly screen aorta specimens and acquire high-quality images which clearly resolve the targeted cells and structures. Thicker specimens require an imaging solution capable of good contrast at points deep inside them. Conventional widefield microscopy is fast and provides detection sensitivity, but the image contrast with thick specimens is significantly reduced by a blur or haze due to signals from out-of-focus planes [4,5].
Methods
Mouse aorta specimens expressing GFP, mCherry, and mOrange and stained with DAPI were imaged with a THUNDER Imager Tissue using Computational Clearing (CC). Vascular cells are green (GFP) and reddish orange (mOrange), elastic lamina are red (mCherry), and nuclei are blue (DAPI). With a THUNDER Imager and the