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Biomedical subjects

Paul Midgley

Publications and source records attributed to Paul Midgley.

2 recordsLinked to original sources

Uptake of C60 by human monocyte macrophages, its localization and implications for toxicity: studied by high resolution electron microscopy and electron tomography.

Despite great interest in the engineering applications of carbon-based nanoparticles, recent studies have raised concerns about their potential toxicity and safety. The release of C(60) into the environment has been suggested to be a potential risk with possible ecological implications. Here we evaluate energy-filtered transmission electron microscopy (EFTEM) and scanning transmission electron microscopy (STEM)-based electron tomography as techniques for imaging the three-dimensional (3-D) distribution of nanoparticles within cells. Our aim was to establish if human monocyte macrophages internalise nanoparticles and to assess whether nanoparticles are modified by cells following uptake. Using these techniques we were able to show a marked increased in the amount of information gained from 3-D imaging. 3-D electron tomography revealed several sub-cellular compartments containing C(60) within the cell: secondary lysosomes, along the outer and nuclear membrane and most notably inside the nucleus of the cell. Using EFTEM and STEM-based techniques we were able to visualize cell structures such as membranes, the mitochondria, ribosomes and the nucleus, without the need for traditional staining techniques. In particular we demonstrate the potential of electron tomography for whole cell studies to enable 3-D distributions of particles within cells. The concentrations of C(60) used in this study were not toxic and were chosen to study which sub-cellular compartments accumulated C(60). Knowledge of the sites of accumulation of nanoparticles will allow us to predict vulnerability if the nanoparticles can generate free radicals.

Cell Culture Techniques↗

A novel dual-axis iterative algorithm for electron tomography.

A new algorithm for computing electron microscopy tomograms which combines iterative methods with dual-axis geometry is presented. Initial modelling using test data shows several improvements over both the weighted back-projection and simultaneous iterative reconstruction technique methods, with increased stability and tomogram fidelity under high-noise conditions. Preliminary experimental dual-axis reconstructions confirm the viability of the new algorithm.

Algorithms↗