References of "Beckers, Simone"
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See detailMetabolic profiling using HPLC allows classification of drugs according to their mechanisms of action in HL-1 cardiomyocytes.
Strigun, Alexander; Wahrheit, Judith; Beckers, Simone et al

in Toxicology and applied pharmacology (2011), 252(2), 183-91

Along with hepatotoxicity, cardiotoxic side effects remain one of the major reasons for drug withdrawals and boxed warnings. Prediction methods for cardiotoxicity are insufficient. High content screening ... [more ▼]

Along with hepatotoxicity, cardiotoxic side effects remain one of the major reasons for drug withdrawals and boxed warnings. Prediction methods for cardiotoxicity are insufficient. High content screening comprising of not only electrophysiological characterization but also cellular molecular alterations are expected to improve the cardiotoxicity prediction potential. Metabolomic approaches recently have become an important focus of research in pharmacological testing and prediction. In this study, the culture medium supernatants from HL-1 cardiomyocytes after exposure to drugs from different classes (analgesics, antimetabolites, anthracyclines, antihistamines, channel blockers) were analyzed to determine specific metabolic footprints in response to the tested drugs. Since most drugs influence energy metabolism in cardiac cells, the metabolite "sub-profile" consisting of glucose, lactate, pyruvate and amino acids was considered. These metabolites were quantified using HPLC in samples after exposure of cells to test compounds of the respective drug groups. The studied drug concentrations were selected from concentration response curves for each drug. The metabolite profiles were randomly split into training/validation and test set; and then analysed using multivariate statistics (principal component analysis and discriminant analysis). Discriminant analysis resulted in clustering of drugs according to their modes of action. After cross validation and cross model validation, the underlying training data were able to predict 50%-80% of conditions to the correct classification group. We show that HPLC based characterisation of known cell culture medium components is sufficient to predict a drug's potential classification according to its mode of action. [less ▲]

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See detailHigh throughput, non-invasive and dynamic toxicity screening on adherent cells using respiratory measurements.
Beckers, Simone; Noor, Fozia UL; Muller-Vieira, Ursula et al

in Toxicology in vitro : an international journal published in association with BIBRA (2010), 24(2), 686-94

A dynamic respiration assay based on luminescence decay time detection of oxygen for high throughput toxicological assessment is presented. The method uses 24-well plates (OxoDishes) read with the help of ... [more ▼]

A dynamic respiration assay based on luminescence decay time detection of oxygen for high throughput toxicological assessment is presented. The method uses 24-well plates (OxoDishes) read with the help of a sensor dish reader placed in a humidified CO(2)-incubator. Adherent primary rat hepatocytes and the human hepatic cell line Hep G2 were exposed to known toxic compounds. Dissolved oxygen concentration, a measure of respiration, was measured with an oxygen sensor optode immobilized in the centre of each well. The cells were maintained in the dishes during the assay period and can afterwards be processed for further analyses. This dynamic, non-invasive measurement allowed calculation of 50% lethal concentrations (LC(50)) for any incubation time point giving concentration-time-dependent responses without further manipulation or removal of the cells from the incubator. Toxicokinetic profiles are compared with Sulforhodamine B assay, a common cytotoxicity assay. The novel assay is robust and flexible, very easy to carry out and provides continuous online respiration data reflecting dynamic toxicity responses. It can be adapted to any cell-based system and the calculated kinetics contributes to understanding of cell death mechanisms. [less ▲]

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