2013
DOI: 10.1111/jmi.12091
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Time‐dependent reduction of structural complexity of the buccal epithelial cell nuclei after treatment with silver nanoparticles

Abstract: Summary Recent studies have suggested that silver nanoparticles (AgNPs) may affect cell DNA structure in in vitro conditions. In this paper, we present the results indicating that AgNPs change nuclear complexity properties in isolated human epithelial buccal cells in a time‐dependent manner. Epithelial buccal cells were plated in special tissue culture chamber / slides and were kept at 37°C in an RPMI 1640 cell culture medium supplemented with L‐glutamine. The cells were treated with colloidal silver nanoparti… Show more

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Cited by 14 publications
(12 citation statements)
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“…Our previous study also focused on testing similar time‐dependent changes in nuclear fractal dimension and lacunarity in buccal epithelial cells (Pantic et al ., ). We found very similar reduction of fractal dimension after treatment with colloidal silver nanoparticles.…”
Section: Discussionmentioning
confidence: 99%
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“…Our previous study also focused on testing similar time‐dependent changes in nuclear fractal dimension and lacunarity in buccal epithelial cells (Pantic et al ., ). We found very similar reduction of fractal dimension after treatment with colloidal silver nanoparticles.…”
Section: Discussionmentioning
confidence: 99%
“…The control cells were untreated (except for the addition of RPMI medium) and kept for 60 min after the start of the experiment, after which digital micrographs were made. The experimental protocol had some similarities with the one applied in our previously published study (Pantic et al, 2013c). A total of 120 nuclear structures (3 different time points + control cells) was visualised and analysed using fractal algorithm.…”
Section: Methodsmentioning
confidence: 99%
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“…Recently, it was demonstrated by Pantic et al . (,) that this method is capable of evaluating fine structural changes in nuclear structure that are otherwise undetectable during standard microscopy analysis, and thus is useful for the identification of nuclear abnormalities, tumour grading, and diagnosis (Kim et al ., ; Liautaud‐Roger et al ., ; van Velthoven et al ., ). Importantly, combining textural and morphological descriptors has been shown to improve the accuracy of biological measurements, in 2D and 3D imaging, particularly in identifying malignant cell types (Kim et al ., ).…”
Section: Morphometric Descriptorsmentioning
confidence: 99%
“…The Pearson product moment correlation coefficient is a statistical method used to describe the correlation between two or more data sets [35]. In particular, the coefficient value falls into the range [-1; 1], in particular (-1) for negative correlation, (+1) for positive correlation and (0) for no correlation.…”
Section: Pearson Product Moment Correlation Coefficientmentioning
confidence: 99%