Artificial neural network analysis of data from multiple in vitro assays for prediction of skin sensitization potency of chemicals
Artificial neural network analysis of data from multiple in vitro assays for prediction of skin sensitization potency of chemicals
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DOI：
10.1016/j.tiv.2013.02.013
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发表时间：
2013-06-01
影响因子：
3.2
通讯作者：
Aiba, Setsuya
中科院分区：
文献类型：
--
作者：
Hirota, Morihiko;Kouzuki, Hirokazu;Aiba, Setsuya
为了开发皮肤致敏的体外风险评估系统，从小鼠局部淋巴结测定（LLNA）中预测阈值是很重要的。我们首先证实，与单个测试相比，人类细胞系激活测试（h-CLAT）和SH测试的组合提高了LLNA数据预测的准确性和灵敏度。接下来，我们评估了SH试验中细胞表面硫醇的最大变化量（MAC值）、细胞毒性试验中的CV75值（给予75%细胞活力的浓度）、h-CLAT中EC150和EC200值（分别为CD86和CD54表达的阈值浓度）和64种化学物质的LLNA阈值之间的相互相关性。基于结果，我们选择了MAC值和CV75、EC150 （CD86）和EC200 （CD54）的最小值作为人工神经网络（ANN）系统输入层的描述符。人工神经网络预测值与报道的LLNA阈值有很好的相关性。我们还发现了SH试验和用于评估半胱甘肽蛋白复合物形成的肽结合试验之间的相关性。因此，这个模型，我们称之为“iSENS ver”。从体外试验数据中，可能对化学物质皮肤致敏潜力的风险评估有用。(C) 2013 Elsevier Ltd.版权所有。
In order to develop in vitro risk assessment systems for skin sensitization, it is important to predict a threshold from the murine local lymph node assay (LLNA). We first confirmed that the combination of the human Cell Line Activation Test (h-CLAT) and the SH test improved the accuracy and sensitivity of prediction of LLNA data compared with each individual test. Next, we assessed the mutual correlations among maximum amount of change of cell-surface thiols (MAC value) in the SH test, CV75 value (concentration giving 75% cell viability) in a cytotoxicity assay, EC150 and EC200 values (thresholds concentrations of CD86 and CD54 expression, respectively) in h-CLAT and published LLNA thresholds of 64 chemicals. Based on the results, we selected MAC value and the minimum of CV75, EC150 (CD86) and EC200 (CD54) as descriptors for the input layer of an artificial neural network (ANN) system. The ANN-predicted values were well correlated with reported LLNA thresholds. We also found a correlation between the SH test and the peptide-binding assay used to evaluate hapten-protein complex formation. Thus, this model, which we designate as the "iSENS ver. 1", may be useful for risk assessment of skin sensitization potential of chemicals from in vitro test data. (C) 2013 Elsevier Ltd. All rights reserved.