Evidence map›Paper›PMID 40629191›Full record

ReviewArchives of virology2025

The application and discovery of animal models in enterovirus research.

Nana Du, Jing Chen, Yuwei Liu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Archives of virology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nana DuDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, 212003, P.R. China.
Jing ChenDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, 212003, P.R. China.
Yuwei LiuDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, 212003, P.R. China. liuyuwei@ujs.edu.cn.ORCID http://orcid.org/0000-0002-5495-2926

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enterovirus infection remains a significant global public health challenge, causing severe diseases such as hand, foot, and mouth disease (HFMD) and meningitis. Given the current lack of effective broad-spectrum antiviral therapies, it is important to investigate the pathogenic mechanisms of viruses using animal models in order to accelerate the development of intervention strategies. This review systematically examines the progress in the development of animal models for enterovirus research, with particular emphasis on non-human primates, rodents, and non-viral infection models. Non-human primates are considered ideal for studying natural enterovirus infections due to their high degree of physiological and immunological similarity to humans. Rodent models, while cost-effective and relatively easy to handle, often rely on the use of viruses with adaptive mutations or immunodeficient animals, which may not fully replicate the human immune response. Non-viral infection models can be used to obtain novel insights into virus-host interactions. Current challenges include the need to overcome discrepancies between animal models and human disease phenotypes, as well as the limitations imposed by the host specificity of viral strains. Future research should integrate multi-omics technologies, organoids, and artificial intelligence to optimize model construction, advance translational research, and provide precise tools for enterovirus prevention and control.

Indexed as

Disease Models, AnimalEnterovirusEnterovirus InfectionsAnimalsHumansPrimatesRodentiaAnimal modelsEnterovirusesNon-human primatesNon-viral animal modelsPathogenesisRodents

Identifiers

What OpenQuestion holds

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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.