Predictive Toxicology of cobalt ferrite nanoparticles: comparative in-vitro study of different cellular models using methods of knowledge discovery from data
Background: Cobalt-ferrite nanoparticles (Co-Fe NPs) are attractive for nanotechnology-based therapies. Thus,
exploring their effect on viability of seven different cell lines representing different organs of the human body is
highly important.
Methods: The toxicological effects of Co-Fe NPs were studied by in-vitro exposure of A549 and NCIH441 cell-lines
(lung), precision-cut lung slices from rat, HepG2 cell-line (liver), MDCK cell-line (kidney), Caco-2 TC7 cell-line (intestine),
TK6 (lymphoblasts) and primary mouse dendritic-cells. Toxicity was examined following exposure to Co-Fe NPs in the
concentration range of 0.05 -1.2 mM for 24 and 72 h, using Alamar blue, MTT and neutral red assays. Changes in
oxidative stress were determined by a dichlorodihydrofluorescein diacetate based assay. Data analysis and predictive
modeling of the obtained data sets were executed by employing methods of Knowledge Discovery from Data with
emphasis on a decision tree model (J48).
Results: Different dose–response curves of cell viability were obtained for each of the seven cell lines upon exposure to
Co-Fe NPs. Increase of oxidative stress was induced by Co-Fe NPs and found to be dependent on the cell type. A high
linear correlation (R2=0.97) was found between the toxicity of Co-Fe NPs and the extent of ROS generation following their
exposure to Co-Fe NPs. The algorithm we applied to model the observed toxicity belongs to a type of supervised
classifier. The decision tree model yielded the following order with decrease of the ranking parameter: NP concentrations
(as the most influencing parameter), cell type (possessing the following hierarchy of cell sensitivity towards viability
decrease: TK6 > Lung slices > NCIH441 > Caco-2 = MDCK > A549 > HepG2 = Dendritic) and time of exposure, where the
highest-ranking parameter (NP concentration) provides the highest information gain with respect to toxicity. The validity
of the chosen decision tree model J48 was established by yielding a higher accuracy than that of the well-known “naive
bayes” classifier.
Conclusions: The observed correlation between the oxidative stress, caused by the presence of the Co-Fe NPs, with the
hierarchy of sensitivity of the different cell types towards toxicity, suggests that oxidative stress is one possible mechanism
for the toxicity of Co-Fe NPs.
Keywords: Nanotoxicology, Cobalt-ferrite nanoparticles, Comparative cytotoxicity, Data mining
HOREV-AZARIA Limor;
BALDI Giovanni;
BENO Delila;
BONACCHI Daniele;
GOLLA-SCHINDLER Ute;
KIRKPATRICK James C;
KOLLE Susanne;
LANDSIEDEL Robert;
MAIMON Oded;
MARCHE Patrice N;
PONTI Jessica;
ROMANO Roni;
ROSSI Francois;
SOMMER Dieter;
UBOLDI C.;
UNGER Ronald E;
VILLIERS Christian;
KORENSTEIN Rafi;
2014-01-23
BIOMED CENTRAL LTD
JRC88239
1743-8977,
http://www.particleandfibretoxicology.com/content/10/1/32,
https://publications.jrc.ec.europa.eu/repository/handle/JRC88239,
10.1186/1743-8977-10-32,
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