Smuggling on the Nanoscale-Fusogenic Liposomes Enable Efficient RNA-Transfer with Negligible Immune Response In Vitro and In Vivo.

The efficient and biocompatible transfer of nucleic acids into mammalian cells for research applications or medical purposes is a long-standing, challenging task. Viral transduction is the most efficient transfer system, but often entails high safety levels for research and potential health impairments for patients in medical applications. Lipo- or polyplexes are commonly used transfer systems but result in comparably low transfer efficiencies.

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation.

In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their development. The key to analyzing acquired data is accurate and automated cell segmentation at the single-cell level.

The platform - enables identification of phenotypic diversity in root and shoot growth traits of agar grown plants.

Background: Root system architecture and especially its plasticity in acclimation to variable environments play a crucial role in the ability of plants to explore and acquire efficiently soil resources and ensure plant productivity. Non-destructive measurement methods are indispensable to quantify dynamic growth traits. For closing the phenotyping gap, we have developed an automated phenotyping platform, -, for non-destructive characterization of root and shoot traits of plants grown in transparent agar medium.

Practically Lossless Affine Image Transformation.

In this contribution we introduce an almost lossless affine 2D image transformation method. To this end we extend the theory of the well-known Chirp-z transform to allow for fully affine transformation of general n-dimensional images. In addition we give a practical spatial and spectral zero-padding approach dramatically reducing losses of our transform, where usual transforms introduce blurring artifacts due to sub-optimal interpolation.