A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.
Elisabeth JoossensPeter MackoTaina PalosaariKirsten GerloffIsaac Ojea-JiménezDouglas GillilandJaroslav NovakSalvador Fortaner TorrentJean-Michel GinesteIsabella RömerSophie Marie BriffaEugenia Valsami-JonesIseult LynchMaurice WhelanPublished in: Scientific data (2019)
The large amount of existing nanomaterials demands rapid and reliable methods for testing their potential toxicological effect on human health, preferably by means of relevant in vitro techniques in order to reduce testing on animals. Combining high throughput workflows with automated high content imaging techniques allows deriving much more information from cell-based assays than the typical readouts (i.e. one measurement per well) with optical plate-readers. We present here a dataset including data based on a maximum of 14 different read outs (including viable cell count, cell membrane permeability, apoptotic cell death, mitochondrial membrane potential and steatosis) of the human hepatoma HepaRG cell line treated with a large set of nanomaterials, coatings and supernatants at different concentrations. The database, given its size, can be utilized in the development of in silico hazard assessment and prediction tools or can be combined with toxicity results from other in vitro test systems.
Keyphrases
- high throughput
- human health
- single cell
- cell death
- high resolution
- risk assessment
- cell cycle arrest
- endothelial cells
- oxidative stress
- climate change
- induced apoptosis
- cell therapy
- insulin resistance
- machine learning
- healthcare
- high fat diet
- stem cells
- type diabetes
- metabolic syndrome
- emergency department
- cell proliferation
- signaling pathway
- high speed
- oxide nanoparticles
- photodynamic therapy
- artificial intelligence