DeadEasy Caspase: Automatic Counting of Apoptotic Cells in Drosophila

PLoS ONE

Volumn 4, Issue 5, 2009, Pages

  Forero, Manuel G ^a   Pennack, Jenny A ^a,b   Learte, Anabel R ^a,c   Hidalgo, Alicia ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b JEALOTT S HILL INTERNATIONAL RESEARCH CENTRE   (United Kingdom)

^c CSIC   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; ANIMAL EMBRYO; APOPTOSIS; ARTICLE; AUTOMATION; CELL COUNT; COMPUTER PROGRAM; CYTOLOGY; DROSOPHILA; METHODOLOGY;

ANIMALS; APOPTOSIS; AUTOMATION; CELL COUNT; DROSOPHILA; EMBRYO, NONMAMMALIAN; SOFTWARE;

EID: 67649803491     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0005441     Document Type: Article

References (29)

1. Bier E, (2005) Drosophila, the golden bug, emerges as a tool for human genetics. Nature Reviwes Genetics 6: 9-23.
2. Burne JF, Staple JK, Raff MC, (1996) Glial cells are increased proportionally in transgenic optic nerves with increased numbers of axons. J Neurosci 16: 2064-2073.
3. Lee R, Kermani P, Teng KK, Hempstead BL, (2001) Regulation of Cell Survival by Secreted Proneurotrophins. Science 294: 1945-1948.
4. Conover JC, Erickson JT, Katz DM, Bianchi LM, Poueymirou WT, et al.(1995) Neuronal deficits, not involving motor neurons, in mice lacking BDNF and/or NT4. Nature 375: 235-241.
5. Soustelle L, Trousse F, Jacques C, Ceron J, Cochard P, et al.(2007) Neurogenic role of Gcm transcription factors is conserved in chicken spinal cord. Development 134: 625-634.
6. Maurange C, Cheng L, Gould AP, (2008) Temporal Transcription Factors and Their Targets Schedule the End of Neural Proliferation in Drosophila. Cell 133: 891-902.
7. Ragone G, Bor VEVD, Sorrentino S, Kammerer M, Galy A, et al.(2003) Transcriptional regulation of glial cell specification. Developmental Biology 255: 138-150.
8. Bowman SK, Rolland V, Betschinger J, Kinsey KA, Emery G, et al.(2008) The Tumor Suppressors Brat and Numb Regulate Transit-Amplifying Neuroblast Lineages in Drosophila. Developmental Cell 14: 535-546.
9. Griffiths RL, Hidalgo A, (2004) Prospero maintains the mitotic potential of glial precursors enabling them to respond to neurons. EMBO J 23: 2440-2450.
10. Booth GE, Kinrade EF, Hidalgo A, (2000) Glia maintain follower neuron survival during Drosophila CNS development. Development 127: 237-244.
11. Rogulja-Ortmann A, K. L, Seibert J, Rickert C, Technau GM, (2007) Programmed Cell Death in the embryonic central nervous system of Drosophila melanogaster. Development 134: 105-116.
12. Lin G, Adiga U, Olson K, Guzowski JF, Barnes CA, et al.(2003) A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A 56: 23-36.
13. Wählby C, (2003) Algorithms for applied digital image cytometry.
14. Wählby C, Sintorn IM, Erlandsson F, Borgefors G, Bengtsson E, (2004) Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections. Journal of Microscopy 215: 67-76.
15. Shimada T, Kato K, Kamikouchi A, Ito K, (2005) Analysis of the distribution of the brain cells of the fruit fly by an automatic cell counting algorithm. Physica A: Statistical and Theoretical Physics 350: 144-149.
16. Colombani J, Poleslello C, Josue F, Tapon N, (2006) Dmp53 activates the Hippo pathway to promote cell death in response to DNA damage. Current Biology 16: 1453-1458.
17. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, et al.(2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 7: R1000.
18. Gué M, Messaoudi C, Sun JS, Boudier T, (2005) Smart 3D-fish: Automation of distance analysis in nuclei of interphase cells by image processing. Cytometry 67A: 18-26.
19. Adiga PSU, Chaudhuri BB, (2000) Some efficient methods to correct confocal images for easy interpretation. Micron 32: 363-370.
20. Conchello JA, (1995) Fluorescence photobleaching correction for expectation maximization algorithm. In: Wilson TaC CJ, editors. Three-Dimensional microscopy: image acquisition and processing Proceedings of the 1995 IS\&T/SPIE symposium on electronic imaging Science and technology SPIE pp. 138-146.
21. Guan YQ, Cai YY, Zhang X, Lee YT, Opas M, (2008) Adaptive correction technique for 3D reconstruction of fluorescence microscopy images. Microscopy Research and Technique 71: 146-157.
22. Kervrann C, Legland D, Pardini L, (2004) Robust incremental compensation of the light attenuation with depth in 3D fluorescence microscopy. Journal of Microscopy 214: 297-314.
23. Rodenacker K, Hausner M, Kuhn M, Wuertz S, Purkayastha S, (2001) Depth intensity correction of biofilm volume data from confocal laser scanning microscopes. Image Anal Stereol 20 (Suppl 1): 556-560.
24. Roerdink JBTM, Bakker M, (1993) An FFT-based method for attenuation correction in fluorescence confocal microscopy. Journal of microscopy 169: 233-260.
25. Wu HX, Ji L, (2005) Fully automated intensity compensation for confocal microscopic images. Journal of microscopy 220 Pt. 1: 9-19.
26. Can A, Al-Kofahi O, Lasek S, Szarowski DH, Turner JN, et al.(2003) Attenuation correction in confocal laser microscopes: A novel two-view approach. Journal of Microscopy 211: 67-79.
27. Forero MG, Cristóbal G, Desco M, (2006) Automatic identification of Mycobacterium tuberculosis by Gaussian mixture models. Journal of Microscopy 223: 120-132.
28. Zhu B, Pennack J, McQuilton P, Forero MG, Mizuguchi K, et al.(2008) Drosophila neurotorphins reveal a common mechanism for nervous system formation. PLoS Biology 6: e284 doi:10.1371/journal.pbio.0060284.
29. Learte AR, Forero MG, Hidalgo A, (2008) Gliatrophic and gliatropic roles of PVF/PVR signaling during axon guidance. Glia 56: 164-176.