Heliyon (Sep 2024)

Nano-scale characterization of iron-carbohydrate complexes by cryogenic scanning transmission electron microscopy: Building the bridge to biorelevant characterization

  • Reinaldo Digigow,
  • Michael Burgert,
  • Marco Luechinger,
  • Alla Sologubenko,
  • Andrzej J. Rzepiela,
  • Stephan Handschin,
  • Amy E. Barton Alston,
  • Beat Flühmann,
  • Erik Philipp

Journal volume & issue
Vol. 10, no. 17
p. e36749

Abstract

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Iron deficiency and iron deficiency anemia pose significant health challenges worldwide. Iron carbohydrate nanoparticles administered intravenously are a mainstay of treatment to deliver elemental iron safely and effectively. However, despite decades of clinical use, a complete understanding of their physical structure and the significance for their behavior, particularly at the nano-bio interface, is still lacking, underscoring the need to employ more sophisticated characterization methods. Our study used cryogenic Scanning Transmission Electron Microscopy (cryo-STEM) to examine iron carbohydrate nanoparticle morphology. This method builds upon previous research, where direct visualization of the iron cores in these complexes was achieved using cryogenic Transmission Electron Microscopy (cryo-TEM). Our study confirms that the average size of the iron cores within these nanoparticles is approximately 2 nm across all iron-based products studied. Furthermore, our investigation revealed the existence of discernible cluster-like morphologies, not only for ferumoxytol, as previously reported, but also within all the examined iron-carbohydrate products. The application of cryo-STEM for the analyses of product morphologies provides high-contrast and high-resolution images of the nanoparticles, and facilitates the characterization at liquid nitrogen temperature, thereby preserving the structural integrity of these complex samples. The findings from this study offer valuable insights into the physical structure of iron-carbohydrate nanoparticles, a crucial step towards unraveling the intricate relationship between the structure and function of this widely used drug class in treating iron deficiency. Additionally, we developed and utilized the self-supervised machine learning workflow for the image analysis of iron-carbohydrate complexes, which might be further expanded into a useful characterization tool for comparability studies.

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