Natural Solar Irradiation Produces Fluorescent and Biodegradable Nanoplastics
Bibliographic record
Abstract
Nanoplastics (NPs) have raised global concern owing to their potential health effects. Herein, after simulated and natural solar irradiation, polyethylene, polypropylene, polystyrene, and poly(vinyl chloride) nanoplastics (PVC NPs) were observed to exhibit enhanced fluorescence, particularly PVC NPs. Furthermore, the role of photoaged NPs as a potential fluorescence indicator was evaluated by exposing a model aquatic organism Daphnia magna to these NPs. Our results revealed that photoaged NPs exhibited strong fluorescence owing to the generation of conjugated π bonds, which can achieve π–π* electron transition with low energy consumption. Photogenerated fluorescence also enabled the photoaged NPs to act as efficient fluorescent tracers, which can help track NP migration in various organisms. The results of two-photon laser confocal scanning microscopy revealed that the photoaged NPs could translocate across biological barriers and accumulate in extraintestinal tissues in addition to being ingested and excreted. Moreover, compared with pristine NPs, the photoaged NPs underwent biodegradation more easily, probably because of increased hydrophilicity due to photogenerated oxygen-containing moieties. Therefore, in addition to producing fluorescent NPs without the attachment of external fluorescent dyes, the natural photoaging process can promote the migration and degradation of photoaged NPs in food chains.
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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".