Loading...
Please wait, while we are loading the content...
Similar Documents
Towards automatic image analysis and assessment of the multicellular apoptosis process
| Content Provider | PubMed Central |
|---|---|
| Author | Ziraldo, Riccardo Link, Nichole Abrams, John Lan, Ma |
| Abstract | Apoptotic programmed cell death (PCD) is a fundamental aspect of developmental maturation. However, the authors’ understanding of apoptosis, especially in the multi-cell regime, is incomplete because of the difficulty of identifying dying cells by conventional strategies. Real-time in vivo microscopy of Drosophila, an excellent model system for studying the PCD during development, has been used to uncover plausible collective apoptosis at the tissue level, although the dynamic regulation of the process remains to be deciphered. In this work, the authors have developed an image-analysis program that can quantitatively analyse time-lapse microscopy of live tissues undergoing apoptosis with a fluorescent nuclear marker, and subsequently extract the spatiotemporal patterns of multicellular response. The program can process a large number of cells (>103) automatically tracked across sets of image frames. It is applied to characterise the apoptosis of Drosophila wing epithelium at eclosion. Using the natural anatomic structures as reference, the authors identify dynamic patterns in the progression of PCD within the Drosophila tissues. The results not only confirm the previously observed collective multi-cell behaviour from a quantitative perspective, but also reveal a plausible role played by the anatomic structures, such as the wing veins, in the PCD propagation across the Drosophila wing. |
| Related Links | http://dx.doi.org/10.1049/iet-ipr.2014.0531 |
| Ending Page | 433 |
| Page Count | 10 |
| Starting Page | 424 |
| File Format | |
| ISSN | 17519659 |
| e-ISSN | 17519667 |
| Journal | IET image processing / IET |
| Issue Number | 5 |
| Volume Number | 9 |
| Language | English |
| Publisher Date | 2015-05-01 |
| Access Restriction | Open |
| Subject Keyword | Signal Processing Electrical and Electronic Engineering Software Computer Vision and Pattern Recognition Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
