Trophic transfer effects of PS nanoplastics and field-derived nanoplastics in the freshwater clam Corbicula fluminea
Bibliographic record
Abstract
Plastic pollution is of global concern. Many studies investigated the effect of micro and nanoplatics towards aquatic organisms. However, relatively few studies were assessed on freshwater organisms. Another aspect of this pollution is the impact of trophic transfer on plastic distribution and on food chain in order to evaluate its potential risk towards environmental and human health. In this context, the objective of this study was to assess the ecotoxicological impacts of different types of nanoplastics (NPs) on freshwater organisms exposed through trophic transfer. Freshwater microalgae Scenedesmus subspicatus were contaminated for 48 h with realistic concentrations of NPs (0.008, 10 and 100 µg/L). Two types of NPs were tested: commercial PS NPs and NPs generated from macro-sized plastics collected in the field (ENV NPs). Freshwater Corbicula fluminea bivalves were then fed with the contaminated algae every 48 h for 21 days. Results showed that trophic exposure led to the induction of oxidative stress (CAT activity). Overall, NPs trophic exposure caused downregulations of genes implicated in many cellular processes (immunity, oxidative stress, neurotoxicity, endocytosis, apoptosis). This present study allowed to demonstrate the relevance of investigating the trophic transfer effects of NPs on a freshwater trophic chain. Further studies should focus more on larger levels of the food chain.
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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) | 0.000 | 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".