Thanks to the development of new 3D Imaging techniques, volumetric data of thick samples, especially tissues, are commonly available. Several algorithms were proposed to analyze cells or nuclei in tissues, however these tools are limited to two dimensions. Within any given tissue, cells are not likely to be organized randomly and as such have specific patterns of cell-cell interaction forming complex communication networks. In this paper, we propose a new set of tools as an approach to segment and analyze tissues in 3D with single cell resolution.
In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the image processing algorithm.
OpenSegSPIM is an open access and user friendly 3-D automatic quantitative analysis tool for Single Plane Illumination Microscopy (SPIM) data. The software is designed to extract, in a user friendly way, quantitative relevant information from SPIM image stacks, such as the number of nuclei or cells. It provides quantitative measurement (volume, sphericity, distance, intensity) on Light Sheet Fluorescent Microscopy (LSFM) images.
The recent discovery of intracellular carbonatogenesis in several cyanobacteria species
has challenged the traditional view that this process was extracellular and not controlled. However,
a detailed analysis of the size distribution, chemical composition and 3-D-arrangement of carbonates
in these cyanobacteria is lacking. Here, we characterized these features in Candidatus Gloeomargarita
lithophora C7 and Candidatus Synechococcus calcipolaris G9 by conventional transmission electron
microscopy, tomography, ultramicrotomy, and scanning transmission X-ray microscopy (STXM).
Hutchinson-Gilford progeria (HGPS) is a premature ageing syndrome caused by a mutation in LMNA, resulting in a truncated form of lamin A called progerin. Progerin triggers loss of the heterochromatic marker H3K27me3, and premature senescence, which is prevented by telomerase. However, the mechanism how progerin causes disease remains unclear. Here, we describe an inducible cellular system to model HGPS and find that LAP2α (lamina-associated polypeptide-α) interacts with lamin A, while its interaction with progerin is significantly reduced.