Detecting the bioaccumulation patterns of chemicals through data-driven approaches

作者：Grisoni Francesca^*; Consonni Viviana; Vighi Marco

来源：Chemosphere, 2018, 208: 273-284.

DOI：10.1016/j.chemosphere.2018.05.157

• Bioaccumulation
• Bioconcentration
• Machine-learning
• Self-organizing map
• Canonical correlation analysis

This work investigates the bioaccumulation patterns of 168 organic chemicals in fish, by comparing their bioconcentration factor (BCF), biomagnification factor (BMF) and octanol-water partitioning coefficient (K-OW). It aims to gain insights on the relationships between dietary and non-dietary bioaccumulation in aquatic environment, on the effectiveness of K-OW and BCF to detect compounds that bioaccumulate through diet, as well as to detect the presence of structure-related bioaccumulation patterns. A linear relationship between logBMF and logK(OW) was observed (logBMF = 1.14 . logBCF - 6.20) up to logK(OW) approximate to 4, as well as between logBMF and logBCF (logBMF = 0.96 . logBCF - 4.06) up to a logBCF approximate to 5.10% of compounds do not satisfy the linear BCF-BMF relationship. The deviations from such linear relationships were further investigated with the aid of a self-organizing map and canonical correlation analysis, which allowed us to shed light on some structure-related patterns. Finally, the usage of K-OW- and BCF-based thresholds to detect compounds that accumulate through diet led to many false positives (47%-91% for K-OW), and a moderate number of false negatives (up to 5% for BCF). These results corroborate the need of using the experimental BMF for hazard assessment practices, as well as of developing computational tools for BMF prediction.

• 出版日期2018-10