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. 2016 Oct 7:406:124-8.
doi: 10.1016/j.jtbi.2016.07.018. Epub 2016 Jul 16.

Gray level co-occurrence matrix algorithm as pattern recognition biosensor for oxidopamine-induced changes in lymphocyte chromatin architecture

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Gray level co-occurrence matrix algorithm as pattern recognition biosensor for oxidopamine-induced changes in lymphocyte chromatin architecture

Igor Pantic et al. J Theor Biol. .

Abstract

We demonstrate that a proapoptotic chemical agent, oxidopamine, induces dose dependent changes in chromatin textural patterns which can be quantified using the Gray level co-occurrence matrix (GLCM) method. Peripheral blood (heparin-pretreated) samples were treated with oxidopamine (6-OHDA, 6-hydroxydopamine) to achieve effective concentrations of 100, 200 and 300µM. The samples were smeared on microscope slides and fixated in methanol. The smears were stained using a modification of Feulgen method for DNA visualization. For each stained smear, a sample of 30 lymphocyte chromatin structures were visualized and analyzed. This way, textural parameters for a total of 120 nuclei micrographs were calculated. For each chromatin structure, five different GLCM features were calculated: angular second moment, GLCM entropy, inverse difference moment, GLCM correlation, and GLCM variance. Oxidopamine induced the rise of the values of GLCM entropy and variance, and the reduction of angular second moment, correlation, and inverse difference moment. The trends for GLCM parameter changes were found to be highly significant (p<0.001). These results indicate that GLCM mathematical algorithm might be successfully used in detection and evaluation of discrete early apoptotic structural changes in Feulgen-stained chromatin of peripheral blood lymphocytes that are not detectable using conventional microscopy/cell biology techniques.

Keywords: Blood; Dopamine; Homogeneity; Image analysis; Pattern.

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