State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Chemosphere. 2019 Jun;224:833-839. doi: 10.1016/j.chemosphere.2019.03.007. Epub 2019 Mar 3.
Endocrine disrupting chemicals (EDCs) threaten the reproductive fitness of aquatic organisms at concentrations lower than those associated with longevity and development. However, the small number of aquatic species assessed for reproductive toxicity has limited the ecological risk assessment of EDCs, making sensible decisions more difficult. In response to this, interspecies correlation estimation (ICE) models were established for EDCs to enable the estimation of reproduction toxicity values to a wider range of organisms. A total of 16 ICE models of EDCs for 6 surrogate species were statistically significant. Of the 16 models, 37.5% (6 models) had a cross-validation success rate > 60%, with a relatively small model squared error, indicating that the model fit is robust. These model results implied that the action of EDCs for each species pair might involve the same mechanisms, and taxonomic relationships did not influence the prediction precision. The cross-validation success rate corroborated the consistency between the projected and experimental values for the EDC ICE models. Sixty-seven percent of the projected values fell within a 10-fold difference of the experimental data. The results indicated that a proven ICE model can greatly increase the amount of EDCs chronic toxicity data for predicted species, without the need for extensive animal experiments, thus providing substitute chronic toxicity data for rapid assessment of EDCs ecological risks.
内分泌干扰化学物质（EDCs）在低于与寿命和发育相关的浓度下就会威胁水生生物的生殖健康，但由于评估生殖毒性的水生物种数量较少，限制了 EDC 的生态风险评估，使得做出明智的决策变得更加困难。针对这一问题，建立了 EDC 的种间相关估算（ICE）模型，以能够估算更广泛的生物体的生殖毒性值。共有 16 种 EDC 对 6 种替代物种的 ICE 模型具有统计学意义。在 16 个模型中，有 37.5%（6 个模型）的交叉验证成功率大于 60%，且模型平方误差较小，表明模型拟合稳健。这些模型结果表明，每种物种对的 EDC 作用可能涉及相同的机制，而分类学关系并不影响预测精度。交叉验证成功率证实了 EDC ICE 模型的预测值与实验值之间的一致性。67%的预测值与实验数据相差 10 倍以内。结果表明，经过验证的 ICE 模型可以大大增加预测物种的 EDC 慢性毒性数据量，而无需进行广泛的动物实验，从而为快速评估 EDC 的生态风险提供替代的慢性毒性数据。
