Recent industrial developments have resulted in an increase in the use of so‐called technology‐critical elements (TCEs), for which the potential impacts on aquatic biota remain to be evaluated. In the present study, quantitative ion character–activity relationships (QICARs) have been developed to relate intrinsic metal properties to their toxicity toward freshwater aquatic organisms. In total, 23 metal properties were tested as predictors of acute median effect concentration (EC50) values for 12 data‐rich metals, for algae, daphnids, and fish (with and without species distinction). Simple and multiple linear regressions were developed using the toxicological data expressed as a function of the total dissolved metal concentrations. The best regressions were then tested by comparing the predicted EC50 values for the TCEs (germanium, indium, gold, and rhenium) and platinum group elements (iridium, platinum, palladium, rhodium, and ruthenium) with the few measured values that are available. The 8 “best” QICAR models (adjusted r² > 0.6) used the covalent index as the predictor. For a given metal ion, this composite parameter is a measure of the importance of covalent interactions relative to ionic interactions. Toxicity was reasonably well predicted for most of the TCEs, with values falling within the 95% prediction intervals for the regressions of the measured versus predicted EC50 values. Exceptions included Au(I) (all test organisms), Au(III) (algae and fish), Pt(II) (algae, daphnids), Ru(III) (daphnids), and Rh(III) (daphnids, fish). We conclude that QICARs show potential as a screening tool to review toxicity data and flag “outliers,” which might need further scrutiny, and as an interpolating or extrapolating tool to predict TCE toxicity. Environ Toxicol Chem 2021;40:1139–1148. © 2020 SETAC

中文翻译：

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开发定量离子特性-活性关系模型以解决技术关键元素毒理学数据的缺乏问题

最近的工业发展导致所谓的技术关键元素 (TCE) 的使用增加，其对水生生物群的潜在影响仍有待评估。在本研究中，定量离子特性-活性关系 (QICAR) 已被开发以将内在金属特性与其对淡水水生生物的毒性联系起来。总共测试了 23 种金属特性，作为 12 种数据丰富的金属、藻类、水蚤和鱼类（有和没有物种区分）的急性中值效应浓度 (EC50) 值的预测因子。使用表示为总溶解金属浓度函数的毒理学数据开发了简单和多元线性回归。然后通过比较 TCE（锗、铟、金、和铼）和铂族元素（铱、铂、钯、铑和钌），可用的测量值很少。8个“最佳”QICAR模型（​​调整r ²  > 0.6) 使用共价指数作为预测因子。对于给定的金属离子，该复合参数是衡量共价相互作用相对于离子相互作用的重要性的指标。大多数 TCE 的毒性得到了相当好的预测，对于测量的 EC50 值与预测的 EC50 值的回归，其值落在 95% 的预测区间内。例外情况包括 Au(I)（所有测试生物）、Au(III)（藻类和鱼）、Pt(II)（藻类、水蚤）、Ru(III)（水蚤）和 Rh(III)（水蚤、鱼） . 我们得出结论，QICAR 显示出作为审查毒性数据和标记“异常值”的筛选工具的潜力，这可能需要进一步审查，并作为预测 TCE 毒性的内插或外推工具。环境毒理学化学2021；40：1139-1148。© 2020 SETAC