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Quantification of Lipoprotein Uptake Using Magnetic Particle Imaging and Spectroscopy.

ACS nano

Authors: Staffan Hildebrand, Norbert Löwa, Hendrik Paysen, Raluca M Fratila, Laia Reverte-Salisa, Thithawat Trakoolwilaiwan, Zheming Niu, Georgios Kasparis, Stephanie Franziska Preuss, Olaf Kosch, Jesus M de la Fuente, Nguyen Thi Kim Thanh, Frank Wiekhorst, Alexander Pfeifer

Lipids are a major source of energy for most tissues, and lipid uptake and storage is therefore crucial for energy homeostasis. So far, quantification of lipid uptake has primarily relied on radioactive isotope labeling, exposing human subjects or experimental animals to ionizing radiation. Here, we describe the quantification of uptake of chylomicrons, the primary carriers of dietary lipids, in metabolically active tissues using magnetic particle imaging (MPI) and magnetic particle spectroscopy (MPS). We show that loading artificial chylomicrons (ACM) with iron oxide nanoparticles (IONPs) enables rapid and highly sensitive detection of lipid uptake using MPS. Importantly, by utilizing highly magnetic Zn-doped iron oxide nanoparticles (ZnMNPs), we generated ACM with MPI tracer properties superseding the current gold-standard, Resovist, enabling quantification of lipid uptake from whole-animal scans. We focused on brown adipose tissue (BAT), which dissipates heat and can consume a large part of nutrient lipids, as a model for tightly regulated and inducible lipid uptake. High BAT activity in humans correlates with leanness and improved cardiometabolic health. However, the lack of nonradioactive imaging techniques is an important hurdle for the development of BAT-centered therapies for metabolic diseases such as obesity and type 2 diabetes. Comparison of MPI measurements with iron quantification by inductively coupled plasma mass spectrometry revealed that MPI rivals the performance of this highly sensitive technique. Our results represent radioactivity-free quantification of lipid uptake in metabolically active tissues such as BAT.

PMID: 33306343

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