Individual and combined toxicity of polystyrene nanoplastics and clothianidin toward <i>Daphnia magna</i>, <i>Lemna minor</i>, <i>Chlamydomonas reinhardtii</i>, and <i>Microcystis aeruginosa</i>
Bibliographic record
Abstract
Nanoplastics (NPs) and neonicotinoids are common pollutants in aquatic ecosystems. Although their co-occurrence is expected in multiple environments, studies assessing their combined effects are still limited. This toxicological assessment investigated the potential effects of polystyrene NPs (PSNPs), clothianidin (CLO), and their mixtures on four aquatic species: the freshwater cladoceran Daphnia magna, the duckweed Lemna minor, the green algae Chlamydomonas reinhardtii, and the cyanobacteria Microcystis aeruginosa. Toxicological tests were performed following International Organization for Standardization and Organisation for Economic Co-operation and Development protocols. Acute, chronic (multigenerational) and swimming behavior tests were performed with D. magna, and growth inhibition tests were run with L. minor, C. reinhardtii, and M. aeruginosa. Abbott's model was used to predict the toxicological interactions of the mixtures for each one of the tested species. The D. magna immobility and swimming behavior tests revealed that the combined toxicities of PSNPs and CLO are decreased when the compounds are present as a mixture. Antagonistic interactions were also observed for C. reinhardtii growth, whereas for L. minor and M. aeruginosa, interactions ranged from antagonism to additivity. Chronic multigenerational tests with D. magna revealed that neonates obtained from the exposed parental generation showed a delay in the first brood during the recovery (nonexposure) phase, but this effect disappeared at the next generation, which indicates that microcrustaceans will probably be able to recover on a long-term scale if contamination is stopped. Our results provide new insights into the combined toxicity and ecological risk of NPs and neonicotinoids toward aquatic organisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".