Evidence map›Paper›PMID 40400225›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2025

Modeling antimicrobial fate in the circular food system.

Weixin Huang, Marlous Focker, H J van der Fels-Klerx

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Modeling antimicrobial fate in the circular food system.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Weixin HuangWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.ORCID 0009-0004-0286-765X
Marlous FockerWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.ORCID 0000-0001-8483-0551
H J van der Fels-KlerxWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.ORCID 0000-0002-7801-394X

Funding

Ministerie van Landbouw, Visserij, Voedselzekerheid en Natuur KB-34-004-024Ministerie van Landbouw, Visserij, Voedselzekerheid en Natuur KB-37-002-038
6 · The paper itself

Abstract

The livestock sector plays a critical role in the circular food production system, but excessive use of antimicrobials (AMs) in livestock farming can lead to AM residue contamination in human food. CirFSafe, a model framework was developed to predict the fate of five different AMs in a primary circular food production system, comprising mixed farms with arable (maize) and animal (bovine) components. Two bovine exposure scenarios to AMs were simulated: annual constant exposure and a one-off exposure in the first year of circularity. Over a 5-year timeframe, model predictions suggest that fertilizing soil with animal manure and feeding animals with maize grown in the same soil are unlikely to cause AM residues in milk or meat exceeding European regulatory limits. Nevertheless, the distinct residual patterns of different AMs across the system underscore the need for precautionary monitoring, particularly for the routine use of flumequine (FLU) and doxycycline (DOX), which exhibits a greater tendency to transfer into food products.

Indexed as

Anti-Infective AgentsFood ContaminationAgricultureAnimalsCattleHumansLivestockManureMeatMilkModels, TheoreticalRisk AssessmentAnti-Infective AgentsManureagriculturechemical hazardscircular economyfood safetypredictive model

Identifiers

PMID40400225
PMCPMC12474533

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.