Assessment of Biofilm Growth on Microplastics in Freshwaters Using a Passive Flow-Through System
Bibliographic record
Abstract
Biofilms that colonize on the surface of microplastics (MPs) in freshwaters may pose a potential health risk. This study examined factors that influence MP-associated biofilm growth, including polymer type, degree of weathering, and source water quality. Weathered MPs produced in-lab were employed in biofilm trials conducted on site using a passive flow-through system with raw water at drinking water treatment facility intakes. Adenosine triphosphate (ATP) was used to quantify biofilm abundance; biofilm composition was assessed via metagenomic sequencing. Biofilm growth was observed on all polymer types examined and most prevalent on polyvinyl chloride (PVC), where ATP levels were 6 to 12 times higher when compared to other polymers. Pathogen-containing species including Salmonella enterica and Escherichia coli were present on all polymers with relative abundance up to 13.7%. S. enterica was selectively enriched on weathered MPs in specific water matrices. These findings support the need to research the potential accumulation of pathogenic organisms on microplastic surfaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".