Evidence map›Paper›PMID 39753861›Full record

ArticleScientific reports2025

Impact of urbanization on antimicrobial resistance in soil microbial communities.

Davide Bongiovanni, Simon Masson, Matteo Chialva, Valentina Fiorilli, Cristina Votta, Luisa Lanfranco, Irene Stefanini

Abstract read
In one paragraph

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

7 authors.

Davide Bongiovanni *Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Simon Masson *Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Matteo ChialvaDepartment of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Valentina FiorilliDepartment of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Cristina VottaDepartment of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Luisa LanfrancoDepartment of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
Irene StefaniniDepartment of Life Sciences and Systems Biology, University of Turin, Turin, Italy. irene.stefanini@unito.it.

Funding

The European Union - NextGenerationEU CN_00000033
6 · The paper itself

Abstract

Soil is one of the most important reservoirs of antibiotic resistance, global threat that needs to be addressed with the One Health approach. Despite urban parks playing a fundamental role in urban ecosystems, the diffusion, maintenance, and human impact of antibiotic-resistance genes in this substrate are still poorly addressed. To fill in this gap, we adopted a molecular and culturomics approach to study antibiotic resistance in urban parks, accounting for the environmental matrix and the level of urbanization. A higher abundance of efflux-mediated mechanisms in undisturbed environments was observed, while antibiotic alteration or inactivation, and target replacement were more abundant in areas with a higher level of urbanization, also confirmed by significant correlations with anthropogenic features of the environmental matrix. Overall, this study highlights the crucial need to monitor antibiotic resistance in urban parks' soil through a dual molecular and culturomics approach to fully understand and fight antibiotic resistance diffusion.

Indexed as

Soil MicrobiologyUrbanizationAnti-Bacterial AgentsBacteriaDrug Resistance, BacterialDrug Resistance, MicrobialEcosystemHumansMicrobiotaSoilAnti-Bacterial AgentsSoil

Identifiers

PMID39753861
PMCPMC11698744

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.