Dataset Open Access

Shedding Light on Metal-Based Nanoparticles in Zebrafish by Computed Tomography with Micrometer Resolution


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  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.6606043", 
  "container_title": "Small", 
  "language": "eng", 
  "title": "Shedding Light on Metal-Based Nanoparticles in Zebrafish by Computed Tomography with Micrometer Resolution", 
  "issued": {
    "date-parts": [
  "abstract": "<p>Supplementary 3D image stacks of microtomography data.</p>\n\n<p>100 layer xy, xz, and yz image stacks</p>\n\n<p>Publication included as PDF file (open access, DOI: 10.1002/smll.202000746)</p>\n\n<p>********************************************</p>\n\n<p>Metal-based nanoparticles are clinically used for diagnostic and therapeutic<br>\napplications. After parenteral administration, they will distribute throughout<br>\ndifferent organs. Quantification of their distribution within tissues in the 3D<br>\nspace, however, remains a challenge owing to the small particle diameter.<br>\nIn this study, synchrotron radiation-based hard X-ray tomography (SR&mu;CT)<br>\nin absorption and phase contrast modes is evaluated for the localization of<br>\nsuperparamagnetic iron oxide nanoparticles (SPIONs) in soft tissues based<br>\non their electron density and X-ray attenuation. Biodistribution of SPIONs<br>\nis studied using zebrafish embryos as a vertebrate screening model. This<br>\nlabel-free approach gives rise to an isotropic, 3D, direct space visualization<br>\nof the entire 2.5 mm-long animal with a spatial resolution of around 2<br>\n&mu;m. High resolution image stacks are available on a dedicated internet<br>\npage ( X-ray tomography is combined with<br>\nphysico-chemical characterization and cellular uptake studies to confirm the<br>\nsafety and effectiveness of protective SPION coatings. It is demonstrated<br>\nthat SR&mu;CT provides unprecedented insights into the zebrafish embryo<br>\nanatomy and tissue distribution of label-free metal oxide nanoparticles.</p>", 
  "author": [
      "family": "HUWYLER J\u00f6rg"
  "volume": "DOI: 10.1002/smll.202000746", 
  "version": "1.0", 
  "type": "dataset", 
  "id": "6606043"
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