Evidence map›Paper›PMID 38275336›Full record

ArticleAntibiotics (Basel, Switzerland)2024

Source Attribution of Antibiotic Resistance Genes in Estuarine Aquaculture: A Machine Learning Approach.

Helena Sofia Salgueiro, Ana Cristina Ferreira, Ana Sofia Ribeiro Duarte, Ana Botelho

Abstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2024. 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. Review
  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

4 authors.

Helena Sofia SalgueiroFaculty of Veterinary Medicine, University of Lisbon, 1300-477 Lisbon, Portugal.
Ana Cristina FerreiraNational Institute for Agrarian and Veterinary Research (INIAV IP), Av. da República, Quinta do Marquês, 2780-157 Oeiras, Portugal.ORCID 0000-0002-9607-7576
Ana Sofia Ribeiro DuarteNational Food Institute, Technical University of Denmark, Kemitorvet 204, 2800 Kongens Lyngby, Denmark.ORCID 0000-0002-8794-0542
Ana BotelhoNational Institute for Agrarian and Veterinary Research (INIAV IP), Av. da República, Quinta do Marquês, 2780-157 Oeiras, Portugal.ORCID 0000-0002-1843-9455

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aquaculture located in urban river estuaries, where other anthropogenic activities may occur, has an impact on and may be affected by the environment where they are inserted, namely by the exchange of antimicrobial resistance genes. The latter may ultimately, through the food chain, represent a source of resistance genes to the human resistome. In an exploratory study of the presence of resistance genes in aquaculture sediments located in urban river estuaries, two machine learning models were applied to predict the source of 34 resistome observations in the aquaculture sediments of oysters and gilt-head sea bream, located in the estuaries of the Sado and Lima Rivers and in the Aveiro Lagoon, as well as in the sediments of the Tejo River estuary, where Japanese clams and mussels are collected. The first model included all 34 resistomes, amounting to 53 different antimicrobial resistance genes used as source predictors. The most important antimicrobial genes for source attribution were tetracycline resistance genes

Indexed as

antimicrobial resistanceaquaculture sedimentsmachine learningresistomessource attribution

Identifiers

PMID38275336
PMCPMC10812778

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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.