The wheel of time: The environmental dance of aged micro- and nanoplastics and their biological resonance
Bibliographic record
Abstract
The aging of micro- and nanoplastics (MNPs) significantly affects their environmental behavior and ecological impacts in both aquatic and terrestrial ecosystems. This review explored the known effects of aging on MNPs and identified several key perspectives. Firstly, aging can alter the environmental fate and transport of MNPs due to changes in their surface properties. This alteration accelerates their accumulation in specific habitats like oceans and soils, resulting in increased bioaccumulation by organisms. In addition, aged MNPs interact differently with living organisms than their pristine counterparts by influencing the attachment of biofilms and other microorganisms in aquatic ecosystems. Moreover, the aging processes of MNPs exhibit adverse effects on aquatic and terrestrial organisms via increasing the bioavailability and potential toxicity of MNPs as degradation products are released. Last but not least, the biodegradation potential of MNPs can be altered by the aging process, thus affecting their degradation rates and pathways in the environment. However, there are still knowledge gaps regarding the natural aging behaviors of MNPs, such as the aging mechanisms of different types of plastic, the influence of environmental factors, the release of pollutants, and even the effects of aging on their transformation in different ecosystems. Therefore, a great contribution can be made to sustainable plastic use and environmental preservation by studying the natural aging of common MNPs and their subsequent biological effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".