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Record W4384914397 · doi:10.1016/j.eehl.2023.07.004

The hidden risk of microplastic-associated pathogens in aquatic environments

2023· review· en· W4384914397 on OpenAlexaff
Huan Zhong, Mengjie Wu, Christian Sonne, Su Shiung Lam, Raymond W. M. Kwong, Yuelu Jiang, Xiaoli Zhao, Xuemei Sun, Xuxiang Zhang, Chengjun Li, Yuanyuan Li, Guangbo Qu, Feng Jiang, Huahong Shi, Rong Ji, Hongqiang Ren

Bibliographic record

VenueEco-Environment & Health · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsYork University
FundersNational Natural Science Foundation of China
KeywordsTransmission (telecommunications)Human pathogenPathogenBiologyHuman healthMicroplasticsAquacultureEnvironmental healthRisk assessmentRisk analysis (engineering)EcologyFish <Actinopterygii>MedicineMicrobiologyFisheryEngineering

Abstract

fetched live from OpenAlex

Increasing studies of plastisphere have raised public concern about microplastics (MPs) as vectors for pathogens, especially in aquatic environments. However, the extent to which pathogens affect human health through MPs remains unclear, as controversies persist regarding the distinct pathogen colonization on MPs as well as the transmission routes and infection probability of MP-associated pathogens from water to humans. In this review, we critically discuss whether and how pathogens approach humans via MPs, shedding light on the potential health risks involved. Drawing on cutting-edge multidisciplinary research, we show that some MPs may facilitate the growth and long-range transmission of specific pathogens in aquatic environments, ultimately increasing the risk of infection in humans. We identify MP- and pathogen-rich settings, such as wastewater treatment plants, aquaculture farms, and swimming pools, as possible sites for human exposure to MP-associated pathogens. This review emphasizes the need for further research and targeted interventions to better understand and mitigate the potential health risks associated with MP-mediated pathogen transmission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.006

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.

Opus teacher head0.024
GPT teacher head0.264
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations87
Published2023
Admission routes1
Has abstractyes

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