ArticleScientific data2019
A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.
Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Review
- In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation.Computational and structural biotechnology journal · 2024Article
- Investigating the dependency of in vitro benchmark concentrations on exposure time in transcriptomics experiments.Toxicology in vitro : an international journal published in association with BIBRA · 2024Article
- The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential.Beilstein journal of nanotechnology · 2024Article
- Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line.Archives of toxicology · 2023Article
- Experimental and Computational Nanotoxicology-Complementary Approaches for Nanomaterial Hazard Assessment.Nanomaterials (Basel, Switzerland) · 2022Review
- Integrating in vitro metabolomics with a 96-well high-throughput screening platform.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics.Metabolites · 2022Article
- A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.Scientific data · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.