Prediction of toxicity of heavy metal mixture by integrated model based on principal component regression
DENG Yang, QIN Li-Tang, ZENG Hong-Hu, QIN Meng, MO Ling-Yun, LIANG Yan-Peng, SONG Xiao-Hong
Collaborative Innovation Center for Water Pollution Control and Water Security in Guangxi Karst Area, Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology, College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
Abstract:In order to solve the problem of the prediction collinearity from CA and IA models, a new model with principal component regression (PCR-IAM) was developed. The PCR-IAM model is able to predict the joint toxicities of heavy metal mixtures with additive, synergetic and antagonistic effects. The PCR-IAM model was developed by using the experimental mixture concentration as dependent variable, and the principal component regression of concentration addition and independent action predictions as independent variable. Four binary mixture systems (Ni-Fe, Ni-Pb, Ni-Cd, and Ni-Cr) representing 20 mixture rays from 240 sampling points was used to verify the predictive power of the PCR-IAM model. The results showed that the coefficient of determination (R2) and leave-one-out cross-validation correlation coefficient (Q2) were greater than 0.95, which proved that the PCR-IAM model can accurately predict the mixture toxicities of 20mixture rays that presented additive, synergistic, and antagonistic effects. Therefore, the PCR-IAM model can precisely predict additive, synergistic, and antagonistic mixture toxicity, which provides a reliable method for risk assessment of environmental mixtures.
邓杨, 覃礼堂, 曾鸿鹄, 秦萌, 莫凌云, 梁延鹏, 宋晓红. 基于主成分回归的整合模型预测重金属混合物毒性[J]. 中国环境科学, 2018, 38(5): 1970-1978.
DENG Yang, QIN Li-Tang, ZENG Hong-Hu, QIN Meng, MO Ling-Yun, LIANG Yan-Peng, SONG Xiao-Hong. Prediction of toxicity of heavy metal mixture by integrated model based on principal component regression. CHINA ENVIRONMENTAL SCIENCECE, 2018, 38(5): 1970-1978.
Gao Y, Feng J, Kang L, et al. Concentration addition and independent action model:Which is better in predicting the toxicity for metal mixtures on zebrafish larvae[J]. Science of the Total Environment, 2017,610-611:442.
[3]
Liu S, Liu L, Chen F, et al. Application of the concentration addition model in the assessment of chemical mixture toxicity[J]. Acta Chimica Sinica, 2013,71(10):1335.
[4]
Nagai T. Predicting herbicide mixture effects on multiple algal species using mixture toxicity models[J]. Environmental Toxicology & Chemistry, 2017.
[5]
Qin L T, Liu S S, Zhang J, et al. A novel model integrated concentration addition with independent action for the prediction of toxicity of multi-component mixture[J]. Toxicology, 2011, 280(3):164-172.
[6]
Sanches A, Vieira B H, Reghini M V, et al. Single and mixture toxicity of abamectin and difenoconazole to adult zebrafish (Danio rerio)[J]. Chemosphere, 2017,188(11):582-587.
[7]
Wang S, Zhuang W, Chen M, et al. Co-exposure of freshwater microalgae to tetrabromobisphenol A and sulfadiazine:Oxidative stress biomarker responses and joint toxicity prediction[J]. Bulletin of Environmental Contamination & Toxicology, 2017:1-7.
Loewe S, Muischnek H. Effect of combinations:Mathematical basis of problem[J]. 1926.
[11]
Bliss C. I. The toxicity of poisons applied jointly[J]. Annals of Applied Biology, 1939,26(3):585-615.1939.
[12]
Regenmortel T V, De K S. Mixtures of Cu, Ni and Zn Act Mostly Non-Interactively on Pseudokirchneriella subcapitata Growth in Natural Waters[J]. Environmental Toxicology & Chemistry, 2017,37(2).
Mulaisho M, Wang X Z, Buontempo F V, et al. Prediction of Noninteractive Mixture Toxicity of Organic Compounds Based on a Fuzzy Set Method[J]. J Chem Inf Comput Sci, 2004,44(5):1763-1773.
Kim J. Development of a partial least squares-based integrated addition model for predicting mixture toxicity[J]. Human & Ecological Risk Assessment An International Journal, 2014, 20(1):174-200.
[18]
Qin L T, Wu J, Mo L Y, et al. Linear regression model for predicting interactive mixture toxicity of pesticide and ionic liquid[J]. Environmental Science & Pollution Research, 2015, 22(16):1-10.
[19]
Carusso S, Juárez A B, Moretton J, et al. Effects of three veterinary antibiotics and their binary mixtures on two green alga species[J]. Chemosphere, 2018,194:821-827.
Moa L, Zhenga M, Meng Q, et al. Quantitative characterization of the toxicities of Cd-Ni and Cd-Cr binary mixtures using combination index method[J]. BioMed Research International, 2016,(2016-12-1), 2016,2016(4):1-6.