ABSTRACT
MOTIVATION: Mouse embryonic stem cells (mESCs) have developed into a prime system to study the regulation of pluripotency in stable cell lines. It is well recognized that different, established protocols for the maintenance of mESC pluripotency support morphologically and functionally different cell cultures. However, it is unclear how characteristic properties of cell colonies develop over time and how they are re-established after cell passage depending on the culture conditions. Furthermore, it appears that cell colonies have an internal structure with respect to cell size, marker expression or biomechanical properties, which is not sufficiently understood. The analysis of these phenotypic properties is essential for a comprehensive understanding of mESC development and ultimately requires a bioinformatics approach to guarantee reproducibility and high-throughput data analysis. RESULTS: We developed an automated image analysis and colony tracking framework to obtain an objective and reproducible quantification of structural properties of cell colonies as they evolve in space and time. In particular, we established a method that quantifies changes in colony shape and (internal) motion using fluid image registration and image segmentation. The methodology also allows to robustly track motion, splitting and merging of colonies over a sequence of images. Our results provide a first quantitative assessment of temporal mESC colony formation and estimates of structural differences between colony growth under different culture conditions. Furthermore, we provide a stream-based visualization of structural features of individual colonies over time for the whole experiment, facilitating visual comprehension of differences between experimental conditions. Thus, the presented method establishes the basis for the model-based analysis of mESC colony development. It can be easily extended to integrate further functional information using fluorescence signals and differentiation markers. AVAILABILITY: The analysis tool is implemented C++ and Mathematica 8.0 (Wolfram Research Inc., Champaign, IL, USA). The tool is freely available from the authors. We will also provide the source code upon request. CONTACT: nico.scherf@tu-dresden.de.
Subject(s)
Algorithms , Embryonic Stem Cells/cytology , Image Processing, Computer-Assisted , Animals , Cell Culture Techniques , Cells, Cultured , Mice , Microscopy, Phase-Contrast , Time-Lapse ImagingABSTRACT
In a 6-year retrospective study the occurrence of autopsy-confirmed nosocomial infections in 282 deceased patients of an intensive care unit was investigated. The autopsy rate was 100%. In 107 deceased (37.9%) 126 nosocomial infections were confirmed. The most common nosocomial infection was bronchopneumonia (54%). The main ailment was non-tumorous diseases of the digestive system (43.9%). In nearly 60% of the 107 deaths, nosocomial infections were the immediate cause of death. In all 282 deceased, hospital infections were the direct cause of death in 22.7% of these cases. The study emphasizes the importance of nosocomial infections as a causal or contributory factor in the death of patients in an intensive care unit.
