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Prevalidation of the ex vivo model PCLS for the prediction of acute inhalation toxicity

Authors :
Sewald, Katherina
Hess, A.
Lauenstein, Lan
Schneider, X.
Vogel, S.
Steinfath, M.
Pirow, R.
Liebsch, M.
Kolle, S.
Ma-Hock, L.
Landsiedel, R.
Martin, C.
Braun, Armin
Publica
Publication Year :
2014

Abstract

In acute inhalation toxicity studies, animals inhale substances at given concentrations. Without additional information, it is difficult to estimate the appropriate starting concentration for in vivo inhalation studies. The goal of this BMBF funded project was the standardization and pre-validation of precision cut lung slices (PCLS) as a suitable ex vivo alternative approach to reduce animal numbers used in inhalation toxicology. The project was conducted in three independent laboratories (Fraunhofer ITEM, BASF SE, RWTH Aachen). BfR provided support in biostatistics. In all participating laboratories, rat PCLS were prepared and exposed to 20 substances under standard submerged culture conditions for 1 hour. Toxicity was assessed by measurement of released lactate dehydrogenase (LDH assay) and mitochondrial activity (WST-1 assay) after 23 hours post-incubation. In addition, protein content and IL-1 were measured. For all endpoints a sigmoid dose-response model was fitted to the data and IC50 values were calculated. This study shows the final results for all 20 chemicals. More than 900 dose-response curves were fitted and analysed. Log10[IC50 (M)] obtained for all assay endpoints showed best intra-laboratory consistency for the data obtained by WST-1 and BCA assays. While WST-1 and LDH indicated toxic effects for majority of the substances, only few of the substances induced increase in IL-1. The reproducibility within the participating laboratories appeared to have acceptably low between-laboratory variations for WST-1 and BCA assay. The results show (i) that the test protocol used in this study is adequately transferable for practical use and (ii) that the tissue model using the WST-1 endpoint is reliable. Binary prediction model showed promising results.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od.......610..c6a23e25671b3c7d978ba650eaf6dba5