Assessment of the toxicity of a mixture of five rare earth elements found in aquatic ecosystems in Hydra vulgaris
Bibliographic record
Abstract
Rare earth elements (REEs) are considered critical elements for technology and their extraction through mining activities is expected to increase in the future. Due to their chemical similarities, they often co-occur in minerals and thus their ecotoxicity should be assessed as a group/family. However, the available ecotoxicological studies focused mainly on the evaluation of the potential toxicological impacts of individual REEs rather than their mixtures. The aim of this study was therefore to evaluate the toxicity of a representative mixture of five REEs (La, Ce, Pr, Nd and Sm) spanning environmentally relevant concentrations ranging from 0.05X (29 µg REEs L−1) to 5X (2926 µg REEs L−1) to the test organism, Hydra vulgaris, at the morphological, reproductive and regenerative levels. The data showed that lethality occurred at concentrations near (2.5 fold) to those inducing sublethal effects after chronic exposure of 7 days. The mixture affected reproduction and head regeneration and even lethality at concentrations even below those reported at environmental concentration (0.5X = 293 µg REEs L−1) in lakes. This suggests that REEs concentrations found in lakes near mining activities could disrupt regeneration and impair embryonic development. Our data also revealed that combining the 5 REEs results in an antagonistic effect, suggesting that those elements share the same receptor and that low molecular weight and high radius elements (approaching iron) were less toxic. Taken together, hydra could be used as a sensitive model organism for the assessment of aquatic ecotoxicological risks of REE mixtures but further analyses of biochemical and gene expressions should improve our understanding of the long-term effects of REEs mixtures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".