How microplastics affect chiral illicit drug methamphetamine in aquatic food chain? From green alga (Chlorella pyrenoidosa) to freshwater snail (Cipangopaludian cathayensis)
Why this work is in the frame
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Bibliographic record
Abstract
The biological impacts of microplastics on many organisms have been well documented. However, the combined effects of microplastics and chiral chemicals on the aquatic food chain are less clear. In the present study, the enantioselective environmental behaviors of methamphetamine co-exposed with microplastics through an aquatic food chain (from Chlorella pyrenoidosa to Cipangopaludian cathayensis) have been investigated in a laboratory environment. It was found that the acute toxicity of methamphetamine against these two species was significantly increased in the presence of microplastics: Chlorella pyrenoidosa showed an EC50 shift from 0.77 to 0.32 mg L−1, while cipangopaludian cathayensis showed an LC50 shift from 4.15 to 1.48 mg L−1, upon the addition of microplastics as a co-contaminant with methamphetamine. Upon exposure to methamphetamine and microplastics, the oxidative damage of algae (19.9 to 36.8 nmol mgprot−1), apoptosis (increase about 2.17 times) and filtration rate (41.2 to 65.4 mL h−1) of snails were observably higher when compared to exposure to methamphetamine alone. After ingestion and accumulation of microplastics, the enantioselectivity, BCFs, BMFs, and distribution of methamphetamine were significantly altered. These results provide evidence that the co-occurrence of microplastics and the chiral drug methamphetamine may increase the burden on aquatic species, with potential further impacts throughout aquatic food chain.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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