A novel mixture sampling strategy combining latin hypercube sampling with optimized one factor at a time method: A case study on mixtures of antibiotics and pesticides

Ting-Ting Ding; Shu-Shen Liu; Ze-Jun Wang; Peng Huang; Meng-Ting Tao; Zhong-Wei Gu

doi:10.1016/j.jhazmat.2023.132568

A novel mixture sampling strategy combining latin hypercube sampling with optimized one factor at a time method: A case study on mixtures of antibiotics and pesticides

J Hazard Mater. 2024 Jan 5:461:132568. doi: 10.1016/j.jhazmat.2023.132568. Epub 2023 Sep 17.

Authors

Ting-Ting Ding¹, Shu-Shen Liu², Ze-Jun Wang³, Peng Huang¹, Meng-Ting Tao⁴, Zhong-Wei Gu¹

Affiliations

¹ Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China.
² Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China. Electronic address: ssliuhl@263.net.
³ National and Local Joint Engineering Laboratory of Municipal Sewage Resource Utilization Technology, School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, PR China.
⁴ Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China.

PMID: 37734309
DOI: 10.1016/j.jhazmat.2023.132568

Abstract

Global sensitivity analysis in conjunction with quantitative high-throughput screening presents a novel technique for identifying the key components that induce the toxicities of mixtures. However, the mixtures currently designed with this method suffer from unequal frequency sampling, repeated mixtures, and only odd factor levels being considered. Accordingly, we use latin hypercube sampling to generate the starting points of the trajectories to achieve equal frequency sampling and non-repeated mixtures, as well as apply different one factor at a time methods for factors with odd and even levels to achieve suitability for factors with both odd and even levels. This method is called LHS-OAT. LHS-OAT was successfully applied to design 110 equal-frequency and non-repeated mixtures consisting of six antibiotics and four pesticides. It was found that four factors, roxithromycin (A5), tetracycline (A6), dichlorvos (P1), and demeton-S (P3), induce the toxicities of mixtures, and A5 and P1 in the Shaying River Basin have risk quotients ≥ 1. Additionally, we developed the toxicity deviation ratio to correct the risk quotients of interacting mixtures for effective risk assessments. This study provides a rational and effective method for mixture design that accurately identifies the important factors that induce the toxicities of mixtures.

Keywords: Important factors; Interaction; Risk assessment; Sensitivity indices; Vibrio qinghaiensis sp.-Q67.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Anti-Bacterial Agents / toxicity
Dichlorvos
Pesticides* / toxicity
Tetracycline / toxicity
Vibrio*

Substances

Pesticides
Anti-Bacterial Agents
Dichlorvos
Tetracycline