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2013, Number 1

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Rev Mex Ing Biomed 2013; 34 (1)

Intracellular calcium variation analysis of follicular cells

Herrera-Navarro AM, Terol-Villalobos IR, Jiménez-Hernández H, Peregrina-Barreto H, González BJJ

Language: Spanish
References: 23
Page: 71-87
PDF size: 2314.78 Kb.


ABSTRACT

This paper presents a method for the measurement of the variation of intracellular calcium in follicular cells. This proposal consists in two stages: (i) The detection of the cell’s nuclei, and (ii) the analysis of the fluorescence variations. The first stage is performed with the modified-watershed transformation, where the marker process is controlled by establishing own criterion. The detection process homogenizes the luminance conditions through a morphological filter and uses as descriptors the edges of the cells. In the second stage, the variations of fluorescence are associated with changes in intracellular Ca2+, which are modeled as an exponential decay function. Then, we present a new morphological process called medium reconstruction process, that smoothes the data in the process of model creation. This process uses the information of under and over model of the signal, through the properties of reconstruction operators, keeping the internal structure of the original signal. Finally, using amphibian cells in an experimental process, the results obtained are showed after applying the proposal to a group of cells.


REFERENCES

  1. Berridge MJ, Lipp P, Bootman MD. “The versality of calcium singalling”, Nature Rev. Mol. Cell Biol. 2000; 4: 11-21.

  2. Berridge MJ, Bootman MD, Roderick HL. “Calcium signalling: dynamics, homeostasis and remodeling”, Nature Rev. Mol. Cell Biol. 2003; 4(7): 4517-529.

  3. Trump BF, Berezesky I.K. “Role of sodium and calcium regulation in toxic cell injury”, In: Drug Metabolism and Drug Toxicity, Ravern Press, New York, 1984.

  4. Stricker SA, Cenzoten VE, Paddock SW, Shatten, G. “Confocal microscopy of fertilization-induced calcium dynamics in sea urching eggs”. Dev. Biol. 1992; 149: 370-380.

  5. Trum BF, Berezesky IK, Laiho HU, Osornio AR, Mergner WJ, Smith MW, et al. “The role of calcium in cell injury. A review”. Scan Electron Microsc. 1980; 437- 462.

  6. Whitaker M and Paterl R. “Calcium and cell cycle control”. Development, 1990; 4(108):525-542.

  7. Elter M, Daum V, Wittenber T. “Maximum-Intensity-Linking for Segmentation of Fluorescente-Stained Cells”, Jahresberucg , Annual Report, 2007.

  8. Nattkemper TW, Wersing H, Schubert W, Ritter H. “Neural network architecture for automatic segmentation of fluorescence micrographs”. Neurocomputing, 2002; 48(1-4): 357-367.

  9. Pham TD, Crane DI, Tran TH, Nguyen TH. “Extraction of fluorescent cell puncta by adaptive fuzzi segmentation”, Bioinformatics, 2004; 20(14): 2189-2196.

  10. Anoraganingrum D. “Cell image segmentation: Global vs. Local adaptive segmentation”, in proceedings of ISSM Kassel, Germany October 1999.

  11. Gauthier KWD, Levine M. Live cell image segmentation, Bioinformatics, 2004; 20(14): 2189-2196.

  12. Metzler V, Lenhmann T, Bienert H, Mottaghy K, Spitzer K. “Scaleindependent shape analysis for quantitative cytology using mathematical morphology”, computers in Medicine an Biology, 2000; 30:135-151.

  13. Wählby C, Lindblad J, Vondrus M, Bengtsson E, Bjorksten, L. “Algorithm for cytoplasm segmentation of fluorescence labeled cells”. Analytical Cellular Pathology. 2002; 24: 101-111.

  14. Metzler V, Tlehmann T, Bienert H, Mottaghy, Spitzer, K. “Scale-independent shape analysis for quantitative cytology using mathematical morphology”. Computers in Biology and Medicine, 2000; 30(3): 135-151.

  15. Meyer F, Beucher S. “Morphological segmentation”. J. Vis. Commun, Image Represent. 1990; 1(1): 21-46.

  16. Luc V, Soille P. “Watershed in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991; 13(6):583-598.

  17. Wilkinson M. “Connected filtering by reconstruction: basis and new advances”. IEEE International Conference on Image Processing, 2008; 2180-2183.

  18. Serra J. Image Analysis and Mathematical Morphology. Theoretical advances, 1988.Vol. 2, Academic Press, New York.

  19. Palomino NC, Luzmila PC. “Watershed: un algoritmo eficiente y flexible para segmentación de imágenes de geles 2-DE”, Revista de Investigación de Sistemas e Informática, 2010; 7(2): 36-41.

  20. Luc V. “Morphological grayscale reconstruction in image analysis: applications and efficient algorithms”, IEEE Trans. on Image Processing. 1993: 2(2): 176-201.

  21. Svalbe I. “Characterizing alternating sequential filters”, IEEE Workshop on Nonlinear Signal Analysis and Image Processing, Neos Marmaras, Greece, 1995; 464-467.

  22. Gómez Fernández C, “Implicación de la entrada de Ca2+ regulada por depósitos intracelulares en la señalización diada por Ca2+ en ovocitos de ratón”, Tesis Doctoral, Departamiento de Bioquimica, Biologia Molecular y Genética, Facultad de Ciencas, Univ. Extremadura, Febrero, 2010.

  23. Moor RM, Smith MW, Dawson, RMC. “Measurement of intercellular coupling between oocytes and cumulus cells using intracellular markers”. Exp. Cell. Res., 1980, 126: 15-29.




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