ABSTRACT
The lack of targeting efficacy has frequently led functionalized nanoparticles to accumulate in unwanted cells and tissues while boosting toxicity-related effects. Conversely, viruses are natural nanoparticles that precisely and responsively interact with the biological machinery through an effective-driven fashion. This interaction is enhanced by a meticulous spatial arrangement which results in a quasi-crystalline distribution of proteins on the viruses' surface. Amidst the COVID-19 pandemic, we propose to look at the SARS-CoV-2 nanoscale viral scaffold as an example of a highly-ordered architecture that must inspire and tailor the production of targeted synthetic nanoparticles.
ABSTRACT
A hybrid method of stitching X-ray computed tomography (CT) datasets is proposed and the feasibility to apply the scheme in a synchrotron tomography beamline with micrometre resolution is shown. The proposed method enables the field of view of the system to be extended while spatial resolution and experimental setup remain unchanged. The approach relies on taking full tomographic datasets at different positions in a mosaic array and registering the frames using Fourier phase correlation and a residue-based correlation. To ensure correlation correctness, the limits for the shifts are determined from the experimental motor position readouts. The masked correlation image is then minimized to obtain the correct shift. The partial datasets are blended in the sinogram space to be compatible with common CT reconstructors. The feasibility to use the algorithm to blend the partial datasets in projection space is also shown, creating a new single dataset, and standard reconstruction algorithms are used to restore high-resolution slices even with a small number of projections.
