Weijs Liesbeth, Roach Anthony C, Yang Raymond S H, McDougall Robin, Lyons Michael, Housand Conrad, Tibax Detlef, Manning Therese, Chapman John, Edge Katelyn, Covaci Adrian, Blust Ronny
Department of Biology, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium; Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium.
Chemosphere. 2014 Jan;94:91-6. doi: 10.1016/j.chemosphere.2013.09.019. Epub 2013 Sep 27.
Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to properly explain the kinetics of pollutants in marine mammals. Therefore, several parameters for a PBPK model for the bioaccumulation and pharmacokinetics of PCB 153 in long-finned pilot whales were estimated in the present study using the Bayesian approach executed with Markov chain Monte Carlo (MCMC) simulations. This method uses 'prior' information of the parameters, either from the literature or from previous model runs. The advantage is that this method uses such 'prior' parameters to calculate probability distributions to determine 'posterior' values that best explain the field observations. Those field observations or datasets were PCB 153 concentrations in blubber of long-finned pilot whales from Sandy Cape and Stanley, Tasmania, Australia. The model predictions showed an overall decrease in PCB 153 levels in blubber over the lifetime of the pilot whales. All parameters from the Sandy Cape model were updated using the Stanley dataset, except for the concentration of PCB 153 in the milk. The model presented here is a promising and preliminary start to PBPK modeling in long-finned pilot whales that would provide a basis for non-invasive studies in these protected marine mammals.
由于信息稀缺以及该领域尚处于萌芽阶段，针对野生动物种群（如海洋哺乳动物）的基于生理的药代动力学（PBPK）模型通常具有高度的模型不确定性和变异性。海洋哺乳动物模型中使用的参数值通常取自其他哺乳动物物种（如大鼠或小鼠），可能并不完全适合用来恰当解释海洋哺乳动物体内污染物的动力学。因此，在本研究中，采用马尔可夫链蒙特卡罗（MCMC）模拟执行的贝叶斯方法，对长鳍领航鲸体内多氯联苯153的生物累积和药代动力学PBPK模型的若干参数进行了估计。该方法使用来自文献或先前模型运行的参数“先验”信息。其优势在于，此方法利用这些“先验”参数来计算概率分布，以确定最能解释实地观测结果的“后验”值。这些实地观测结果或数据集是来自澳大利亚塔斯马尼亚州桑迪角和斯坦利的长鳍领航鲸鲸脂中多氯联苯153的浓度。模型预测显示，在领航鲸的一生中，其鲸脂中多氯联苯153的水平总体呈下降趋势。除了乳汁中多氯联苯153的浓度外，桑迪角模型的所有参数都使用斯坦利数据集进行了更新。这里提出的模型是长鳍领航鲸PBPK建模有前景的初步开端，将为这些受保护海洋哺乳动物的非侵入性研究提供基础。
