Publications

Introducing SimpliPyTEM, a Python library and accompanying GUI that simplifies the post-acquisition evaluation of transmission electron microscopy (TEM) images, helping streamline the workflow. After an imaging session, a folder of image and/or video files, typically containing low contrast and large file size 32-bit images, can be quickly processed via SimpliPyTEM into high-quality, high-contrast.jpg images with suitably sized scale bars. The app can also generate HTML or PDF files containing the processed images for easy viewing and sharing. Additionally, SimpliPyTEM specifically focuses on in situ TEM videos, an emerging field of EM involving the study of dynamic processes whilst imaging. The package allows fast data processing into preview movies, averages, image series, or motion-corrected averages. The accompanying Python library offers many standard image processing methods, all simplified to a single command, plus a module to analyse particle morphology and population. This latter application is particularly useful for life sciences investigations. User-friendly tutorials and clear documentation are included to help guide users through the processing and analysis. We invite the EM community to contribute to and further develop this open-source package.

JTD Keywords: Image processing, computer-assisted, Microscopy, electron, transmission, Mobile applications, Software

The functionalization of nanoparticles with functional moieties is a key strategy to achieve cell targeting in nanomedicine. The interplay between size and ligand number is crucial for the formulation performance and needs to be properly characterized to understand nanoparticle structure-activity relations. However, there is a lack of methods able to measure both size and ligand number at the same time and at the single particle level. Here, we address this issue by introducing a correlative light and electron microscopy (CLEM) method combining super-resolution microscopy (SRM) and transmission electron microscopy (TEM) imaging. We apply our super-resCLEM method to characterize the relationship between size and ligand number and density in PLGA-PEG nanoparticles. We highlight how heterogeneity found in size can impact ligand distribution and how a significant part of the nanoparticle population goes completely undetected in the single-technique analysis. Super-resCLEM holds great promise for the multiparametric analysis of other parameters and nanomaterials.

JTD Keywords: cellular uptake, correlative light and electron microscopy (clem), density, electron microscopy (em), functionalization, heterogeneity, nanomedicine, nanoparticles, pegylation, plga, progress, quantification, size, Correlative light and electron microscopy (clem), Electron microscopy (em), Heterogeneity, Ligands, Microscopy, electron, transmission, Microscopy, fluorescence, Nanomedicine, Nanoparticles, Physicochemical characterization, Super-resolution microscopy (srm)