Evidence map›Paper›PMID 39728985›Full record

ArticleVeterinary sciences2024

Antimicrobial Resistance Profiling of Pathogens from Cooked Donkey Meat Products in Beijing Area in One Health Context.

Yiting Liu, Hongyun Duan, Luo Yang, Hong Chen, Rongzheng Wu, Yi Li, Yiping Zhu, Jing Li

Abstract read
In one paragraph

Article in Veterinary sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

8 authors.

Yiting LiuEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Hongyun DuanShenzhen Youlan Medical Technology Co., Ltd., Shenzhen 518102, China.
Luo YangEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Hong ChenEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Rongzheng WuEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Yi LiEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Yiping ZhuEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Jing LiEquine Clinical Diagnostic Centre, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.ORCID 0000-0002-1361-4525

Funding

National Natural Science Foundation of China 32202861
6 · The paper itself

Abstract

The prevalence of foodborne diseases has raised concerns due to the potential transmission of zoonotic bacterial pathogens through meat products. The objective of this study was to determine the occurrence and antimicrobial resistance (AMR) profiles of pathogenic bacteria in cooked donkey meat products from Beijing. Twenty-one cooked donkey meat samples were collected from different delis, subjected to homogenization, and analyzed for bacterial contamination. Molecular identification was performed through polymerase chain reaction (PCR) amplification and sequencing targeting the 16S rDNA gene. The antimicrobial susceptibility of the isolates was evaluated using the disk diffusion method. A total of forty bacterial isolates were identified, with

Indexed as

antimicrobial resistancedonkey meat productKlebsiella pneumoniaeOne HealthProteus mirabilis

Identifiers

PMID39728985
PMCPMC11680287

What OpenQuestion holds

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LicenceCC BY
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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.