ArticleScientific reports2025
DNA metabarcoding and its potential in microbial risk assessment in waste sorting plants.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Bacteria and associated antibiotic resistance in air filter-derived biological material from utility vehicles at mechanical-biological treatment plants.International journal of occupational medicine and environmental health · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Exposure to hazardous microorganisms during waste handling is a potential health concern. Molecular biological techniques provide means of profiling the microbial community at high taxonomic resolution, allow the identification of critical human pathogens on the species level and thereby aid the risk assessment of work tasks. The present study used high-throughput sequencing to characterise the microbiome in personal full-shift air samples collected at contemporary waste sorting plants (WSPs) and identified large variations in community composition within (alpha diversity) and between (beta diversity) WSPs. Seasonality did not contribute to differences in the community composition. Cladosporium sp. was dominant among fungi, whereas Aerococcus sp. was dominant among bacteria. The personal air-samples contained potential human pathogens, such as Aspergillus sp., Fusarium sp. and Enterobacteriaceae, that encompass strains with the potential to develop drug-resistance. This study provided characterization of the microbial community composition of personal bioaerosol samples and provided evidence for the occurrence of potential human pathogens in contemporary waste sorting plants. Furthermore, this study highlighted the potential of microbial metabarcoding to detect critical human pathogens that may be encountered in working environments.
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