Ecotoxicity of a Representative Urban Mixture of Rare Earth Elements to Hydra vulgaris
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rare earth elements (REEs) are considered as emerging contaminants due to their use in the fabrication process of current technologies. As such, their aquatic toxicity, especially as a mixture, is not well understood, as it has been scarcely investigated. The purpose of this study was to shed light on the sublethal and lethal toxicity of a realistic mixture of five REE in Hydra vulgaris. The REE mixture was composed of five elements (Gd, Ce, Nd, Y and Dy, with a total REE concentration of 0.137 µg/L = 1× concentration) that were found in six municipal effluents in Canada at the same concentration ratios. The organisms were exposed to increasing concentrations (0.5, 1, 5, 10, 25, 50 and 100×) of the mixture for 96 h at 20 °C. The lethal and sublethal toxicities were evaluated by morphological changes and the gene expression (mRNA) involved in oxidative stress, damaged protein salvaging (autophagy for the reabsorption of damaged proteins), regeneration, neural activity and DNA repair of oxidatively damaged DNA. The data revealed that the total REE concentration of the environmental mixture was well below the lethal concentrations of the individual REEs, which occur generally at concentrations > 200 µg/L. This study proposes a novel gene transcription set to investigate the mode of action where gene expression changes occurred at concentrations below those reported in municipal effluents, suggesting long-term toxic effects in hydras close to municipal effluent discharges. This suggests that the release of REEs by municipal/hospital (for Gd) effluents should be more closely monitored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.005 | 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 it