Evidence map›Paper›PMID 40498321›Full record

ReviewFEMS microbiology reviews2025

Ex vivo study of neuroinvasive and neurotropic viruses: what is current and what is next.

Alexandre Lalande, Cyrille Mathieu

Abstract readReview
In one paragraph

Review in FEMS microbiology reviews, 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. Review
  2. Article
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

2 authors.

Alexandre LalandeCIRI, Centre International de Recherche en Infectiologie, NeuroInvasion TROpism and VIRal Encephalitis Team, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 21 Avenue Tony Garnier, F-69007 Lyon, France.ORCID 0000-0003-3917-1598
Cyrille MathieuCIRI, Centre International de Recherche en Infectiologie, NeuroInvasion TROpism and VIRal Encephalitis Team, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, 21 Avenue Tony Garnier, F-69007 Lyon, France.ORCID 0000-0002-6682-2029

Funding

Agence de l'innovation de DéfenseAgence Nationale de la Recherche ANR-21-CE11-0012-01Agence Nationale de Recherches sur le Sida et les Hépatites Virales ANRS-23-PEPR-MIE 0008CIRI AO-9-2024/25Direction Générale de l'Armement ANR-22-ASTR-0021
6 · The paper itself

Abstract

Numerous pathogens, including viruses, enter the central nervous system and cause neurological disorders, such as encephalitis. Viruses are the main etiologic agents of such neurological diseases, and some of them cause a high death toll worldwide. Our knowledge about neuroinvasive and encephalitogenic virus infections is still limited due to the relative inaccessibility of the brain. To mitigate this shortcoming, neural ex vivo models have been developed and turned out to be of paramount importance for understanding neuroinvasive and neurotropic viruses. In this review, we describe the major ex vivo models for the central nervous system, including neural cultures, brain organoids, and organotypic brain cultures. We highlight the key findings from these models and illustrate how these models inform on viral processes, including neurotropism, neuroinvasion, and neurovirulence. We discuss the limitations of ex vivo models, highlight ongoing progress, and outline next-generation ex vivo models for virus research at the interface of neuroscience and infectious diseases.

Indexed as

VirusesAnimalsBrainHumansVirus Diseasesex vivoneuroinvasionneurotropismorganoidorganotypic culturevirus

Identifiers

PMID40498321
PMCPMC12199766

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.