Effects of aging of polyethylene microplastics and polystyrene nanoplastics on antibiotic resistance gene transfer during primary sludge fermentation
Bibliographic record
Abstract
The increasing presence of nano and microplastics (NPs/MPs) in wastewater treatment plants and their inevitable accumulation in the sludge has raised serious concerns in recent years. This study investigated the effects of pristine and aged polyethylene microplastics (PEMPs), polystyrene nanoplastics (PsNPs), and their mixtures on the primary sludge fermentation process. Pristine MPs/NPs (150 μg/L and 2 g/L for PsNPs and PEMPs, respectively) underwent two weeks of weathering in the presence of humic and alginic acids. The results from a batch fermentation experiment (15 days, pH 10) revealed that the exposure to aged PEMPs/PsNPs experienced greater VFA production than pristine samples. Notably, the aged PEMPs/PsNPs mixture showed a 23.12% increase in VFA production over the pristine mixture. The relative abundance and total concentration of antibiotic resistance genes (ARGs) increased in all PEMPs/PsNPs batches compared to the control, with the most significant rise in total ARGs observed in the aged PEMPs sample. Aged PEMPs exhibited a 26.22-fold increase in tetA genes, while aged mix samples showed a 19.68-fold increase in tetM genes compared to their pristine counterparts. Both pristine and aged PEMPs/PsNPs, particularly the aged PEMPs adversely affected the microbial communities at the genus level and altered the microbial structure. Microbial richness and diversity were enhanced in samples exposed to pristine PEMPs/PsNPs and aged PsNPs but decreased in aged PEMPs and in the aged mixture group, suggesting a negative impact of aged polyethylene microplastics on microbial communities. Correlation analysis suggested that phyla Planctomycetes, Proteobacteria, and TM7 are potential hosts of ARGs. These findings manifest the substantial effects of aged nano/microplastics compared to their pristine forms, emphasizing the complex interplay between various forms of PEMPs/PsNPs and microbial dynamics in sludge fermentation processes.
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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) | 0.000 | 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".