Issue 8, 2016

Re-analysis of narcotic critical body residue data using the equilibrium distribution concept and refined partition coefficients

Abstract

Narcosis occurs as a result of the accumulation of chemicals in the phospholipid membrane. The toxic threshold concentration in the membrane is thought to be relatively constant across different chemicals and species. Hence, estimating chemical concentrations in the membrane is expected to reduce the variability of narcotic critical body residue (CBR) data. In this study, a high quality CBR dataset for three aquatic species reported recently in the literature was evaluated with the internal equilibrium distribution concept. The raw wet-weight-based CBR values were converted to membrane-weight-based CBR values by assuming that the chemical is distributed in storage lipids, membranes, proteins, and water according to the respective equilibrium partition coefficients. Several sets of partition coefficients were compared for this analysis. The results were consistent with the notion that the use of a structural protein instead of serum albumin as a surrogate for the body protein fraction could reduce the variability of CBRs. Partition coefficients predicted by polyparameter linear free energy relationships (PP-LFERs) reduced the variability of CBRs as much as or even more than experimental partition coefficients did. It is suggested that CBR data for chemicals with larger structural diversity and biological species with more distinct compositions are needed to evaluate further the equilibrium distribution concept and the constant membrane threshold hypothesis.

Graphical abstract: Re-analysis of narcotic critical body residue data using the equilibrium distribution concept and refined partition coefficients

Supplementary files

Article information

Article type
Paper
Submitted
18 Marts 2016
Accepted
20 Apr. 2016
First published
21 Apr. 2016

Environ. Sci.: Processes Impacts, 2016,18, 1024-1029

Re-analysis of narcotic critical body residue data using the equilibrium distribution concept and refined partition coefficients

S. Endo, Environ. Sci.: Processes Impacts, 2016, 18, 1024 DOI: 10.1039/C6EM00180G

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