Tags

Type your tag names separated by a space and hit enter

Predicting the combined toxicity of binary metal mixtures (Cu-Ni and Zn-Ni) to wheat.
Ecotoxicol Environ Saf. 2020 Dec 01; 205:111334.EE

Abstract

In order to investigate and model toxicity and interactions between metals in mixtures, inhibition of wheat root elongation in response to additions of single-metals of copper (Cu), zinc (Zn), and nickel (Ni) and of binary mixed-metal combinations of Cu-Ni and Zn-Ni was tested, using water culture experiments under different Mg concentrations and pH values. A biotic ligand model (BLM) of single-metal Cu, Zn, and Ni was established. The results showed that the toxicity of Cu, Zn or Ni in isolation decreased with increasing Mg concentration whereas the effects of pH on Cu, Zn, or Ni toxicity were related not only to free Cu2+, Zn2+, and Ni2+ concentrations, but also to inorganic metal complexes. In binary mixtures, the two metals in the Cu-Ni mixture showed a weakly antagonistic effect, whereas the two metals in the Zn-Ni mixture showed greater antagonism. Using data from single-metal Cu, Zn, and Ni BLMs, combined with the toxicity index and the overall amounts of metal ions bound to the biotic ligands, one simple model was developed. This model consisted of the toxic unit (TUM, no competition included) and two extended BLMs, BLM-TUf (f as a function of TU, including competition between Mg2+ and metal ions) and BLM-fmix (including the competition between Mg2+ and metal ions, as well as between free metal ions). They were then used to predict the joint toxicity of Cu-Ni and Zn-Ni binary mixtures to wheat. Both of the extended BLMs could provide more accurate predictions of toxic effects of Cu-Ni and Zn-Ni than TUM. BLM-fmix performed best for the Zn-Ni binary mixture (r2 = 0.93; root-mean-square error, RMSE = 9.87). On the other hand, for the Cu-Ni mixture, the predictive effect based on BLM-TUf (r2 = 0.93; RMSE = 9.60) was similar to that of BLM-fmix (r2 = 0.93; RMSE = 9.56). The results provide a theoretical basis for the evaluation and remediation of soils contaminated with mixtures of heavy metals.

Links

Publisher Full Text (DOI)

Authors+Show Affiliations

Wang X
College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China. Electronic address: xdwang@cnu.edu.cn.
Luo X
College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
Wang Q
College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
Liu Y
Global Centre for Environmental Remediation, The University of Newcastle, Callaghan, NSW, 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), Callaghan, NSW, 2308, Australia.
Naidu R
Global Centre for Environmental Remediation, The University of Newcastle, Callaghan, NSW, 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), Callaghan, NSW, 2308, Australia.

MeSH

CopperDose-Response Relationship, DrugDrug AntagonismLigandsModels, BiologicalNickelPlant RootsSoil PollutantsTriticumZinc

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32961486

Citation

Wang, Xuedong, et al. "Predicting the Combined Toxicity of Binary Metal Mixtures (Cu-Ni and Zn-Ni) to Wheat." Ecotoxicology and Environmental Safety, vol. 205, 2020, p. 111334.
Wang X, Luo X, Wang Q, et al. Predicting the combined toxicity of binary metal mixtures (Cu-Ni and Zn-Ni) to wheat. Ecotoxicol Environ Saf. 2020;205:111334.
Wang, X., Luo, X., Wang, Q., Liu, Y., & Naidu, R. (2020). Predicting the combined toxicity of binary metal mixtures (Cu-Ni and Zn-Ni) to wheat. Ecotoxicology and Environmental Safety, 205, 111334. https://doi.org/10.1016/j.ecoenv.2020.111334
Wang X, et al. Predicting the Combined Toxicity of Binary Metal Mixtures (Cu-Ni and Zn-Ni) to Wheat. Ecotoxicol Environ Saf. 2020 Dec 1;205:111334. PubMed PMID: 32961486.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Predicting the combined toxicity of binary metal mixtures (Cu-Ni and Zn-Ni) to wheat. AU - Wang,Xuedong, AU - Luo,Xiaorong, AU - Wang,Qixin, AU - Liu,Yanju, AU - Naidu,Ravi, Y1 - 2020/09/19/ PY - 2020/07/04/received PY - 2020/09/09/revised PY - 2020/09/10/accepted PY - 2020/9/23/pubmed PY - 2020/10/24/medline PY - 2020/9/22/entrez KW - Biotic ligand model KW - Metal mixtures KW - Toxicity KW - Wheat SP - 111334 EP - 111334 JF - Ecotoxicology and environmental safety JO - Ecotoxicol Environ Saf VL - 205 N2 - In order to investigate and model toxicity and interactions between metals in mixtures, inhibition of wheat root elongation in response to additions of single-metals of copper (Cu), zinc (Zn), and nickel (Ni) and of binary mixed-metal combinations of Cu-Ni and Zn-Ni was tested, using water culture experiments under different Mg concentrations and pH values. A biotic ligand model (BLM) of single-metal Cu, Zn, and Ni was established. The results showed that the toxicity of Cu, Zn or Ni in isolation decreased with increasing Mg concentration whereas the effects of pH on Cu, Zn, or Ni toxicity were related not only to free Cu2+, Zn2+, and Ni2+ concentrations, but also to inorganic metal complexes. In binary mixtures, the two metals in the Cu-Ni mixture showed a weakly antagonistic effect, whereas the two metals in the Zn-Ni mixture showed greater antagonism. Using data from single-metal Cu, Zn, and Ni BLMs, combined with the toxicity index and the overall amounts of metal ions bound to the biotic ligands, one simple model was developed. This model consisted of the toxic unit (TUM, no competition included) and two extended BLMs, BLM-TUf (f as a function of TU, including competition between Mg2+ and metal ions) and BLM-fmix (including the competition between Mg2+ and metal ions, as well as between free metal ions). They were then used to predict the joint toxicity of Cu-Ni and Zn-Ni binary mixtures to wheat. Both of the extended BLMs could provide more accurate predictions of toxic effects of Cu-Ni and Zn-Ni than TUM. BLM-fmix performed best for the Zn-Ni binary mixture (r2 = 0.93; root-mean-square error, RMSE = 9.87). On the other hand, for the Cu-Ni mixture, the predictive effect based on BLM-TUf (r2 = 0.93; RMSE = 9.60) was similar to that of BLM-fmix (r2 = 0.93; RMSE = 9.56). The results provide a theoretical basis for the evaluation and remediation of soils contaminated with mixtures of heavy metals. SN - 1090-2414 UR - https://www.unboundmedicine.com/medline/citation/32961486/Predicting_the_combined_toxicity_of_binary_metal_mixtures__Cu_Ni_and_Zn_Ni__to_wheat_ DB - PRIME DP - Unbound Medicine ER -