Quantitative Three-Dimensional Imaging Analysis of HfO₂ Nanoparticles in Single Cells via Deep Learning Aided X-ray Nano-Computed Tomography.

ABSTRACT: It is crucial for understanding mechanisms of drug action to quantify the three-dimensional (3D) drug distribution within a single cell at nanoscale resolution. Yet it remains a great challenge due to limited lateral resolution, detection sensitivities, and reconstruction problems. The preferable method is using X-ray nano-computed tomography (Nano-CT) to observe and analyze drug distribution within cells, but it is time-consuming, requiring specialized expertise, and often subjective, particularly with ultrasmall metal nanoparticles (NPs). Furthermore, the accuracy of batch data analysis through conventional processing methods remains uncertain. In this study, we used radioenhancer ultrasmall HfO₂ nanoparticles as a model to develop a modular and automated deep learning aided N

SUBMITTER: Xi Z 

PROVIDER: S-EPMC11342356 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature