Evidence map›Paper›PMID 38987937›Full record

ReviewAnimal models and experimental medicine2024

Applications and advancements in animal models for antiviral research on mosquito-borne arboviruses.

Megan Caifeng Tang, Ka Heng Wong, Adzzie Shazleen Azman, Rafidah Lani

Abstract readReview
In one paragraph

Review in Animal models and experimental medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Megan Caifeng TangSchool of Science, Monash University Malaysia, Sunway, Selangor, Malaysia.
Ka Heng WongSchool of Science, Monash University Malaysia, Sunway, Selangor, Malaysia.
Adzzie Shazleen AzmanSchool of Science, Monash University Malaysia, Sunway, Selangor, Malaysia.ORCID 0000-0002-1703-8350
Rafidah LaniDepartment of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vector-borne diseases caused by arthropod-borne viruses (arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms, vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate (NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible; however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.

Indexed as

ArbovirusesArbovirus InfectionsDisease Models, AnimalAnimalsCulicidaeHumansMiceMosquito Vectorsanimal modelsarbovirusbiomedical researchethicsinfectious diseases

Identifiers

PMID38987937
PMCPMC11528384

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.