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Smolle, J; Hofmann-Wellenhof, R; Fink-Puches, R; Auersperg, N.
Assessment of tumor cell cohesion in vivo using pattern interpretation by cellular automata.
Anal Quant Cytol Histol. 1996; 18(3):199-204
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Leading authors Med Uni Graz: Smolle Josef
Co-authors Med Uni Graz: Fink-Puches Regina; Hofmann-Wellenhof Rainer
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Abstract:: OBJECTIVE: There is abundant evidence that patterning in life sciences may be closely related to the functional properties of the constitutive elements. In order to estimate some of these functional properties by examining the static pattern evolved, pattern interpretation by cellular automata (PICA) was introduced and applied to the mechanisms of tumor growth. Previously it was shown that the estimates concerning tumor cell proliferation and motility were consistent with those obtained by other methods. STUDY DESIGN: Morphologic patterns obtained by growing two variants of the C4 cervical carcinoma cell lines with different in vitro adhesive properties in the hamster cheek pouch were evaluated by PICA. RESULTS: PICA estimates of tumor cell cohesion turned out to be significantly higher in tumors derived from the C4-I cell line (0.73 +/- 0.02 SD) with high in vitro cohesiveness than in tumors derived from the less adhesive C4-II cell line (0.32 +/- 0.04 SD; t test, P = .001). CONCLUSION: These results indicate that functional estimates concerning tumor cell cohesion obtained by PICA may be in good agreement with in vitro observations of the same cellular property and further underscore that PICA may be a useful tool for the functional interpretation of static histologic patterns.
Find related publications in this database (using NLM MeSH Indexing): Animals -; Cell Adhesion -; Cell Count -; Cell Division - physiology; Cricetinae - physiology; Female - physiology; Humans - physiology; Image Processing, Computer-Assisted - physiology; Mitosis - physiology; Pattern Recognition, Automated - physiology; Tumor Cells, Cultured - cytology; Uterine Cervical Neoplasms - pathology
Find related publications in this database (Keywords): Pattern Recognition; Pattern Interpretation by Cellular Automata