Evidence map›Paper›PMID 39338502›Full record

ReviewMicroorganisms2024

The Future Exploring of Gut Microbiome-Immunity Interactions: From In Vivo/Vitro Models to In Silico Innovations.

Sara Bertorello, Francesco Cei, Dorian Fink, Elena Niccolai, Amedeo Amedei

Abstract readReview
In one paragraph

Review in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Synthetic and systems biotechnology · 2027
    Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. A Combined Probiotic-International journal of molecular sciences · 2026
    Article
  7. Article
  8. Synergistic effects ofmSystems · 2026
    Article
  9. Article
  10. Review
  11. Pharmaceutics · 2025
    Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. 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

5 authors.

Sara BertorelloDepartment of Experimental and Clinical Medicine, University of Florence, 50139 Florence, Italy.ORCID 0009-0005-2267-7551
Francesco CeiDepartment of Experimental and Clinical Medicine, University of Florence, 50139 Florence, Italy.
Dorian FinkDepartment of Experimental and Clinical Medicine, University of Florence, 50139 Florence, Italy.
Elena NiccolaiDepartment of Experimental and Clinical Medicine, University of Florence, 50139 Florence, Italy.ORCID 0000-0002-9205-8079
Amedeo AmedeiDepartment of Experimental and Clinical Medicine, University of Florence, 50139 Florence, Italy.ORCID 0000-0002-6797-9343

Funding

European Union B83C22003920001Ministry of University and Research PE0000006University of Florence B55F21007810001
6 · The paper itself

Abstract

Investigating the complex interactions between microbiota and immunity is crucial for a fruitful understanding progress of human health and disease. This review assesses animal models, next-generation in vitro models, and in silico approaches that are used to decipher the microbiome-immunity axis, evaluating their strengths and limitations. While animal models provide a comprehensive biological context, they also raise ethical and practical concerns. Conversely, modern in vitro models reduce animal involvement but require specific costs and materials. When considering the environmental impact of these models, in silico approaches emerge as promising for resource reduction, but they require robust experimental validation and ongoing refinement. Their potential is significant, paving the way for a more sustainable and ethical future in microbiome-immunity research.

Indexed as

immunityinflammationin silico modelsin vitro modelsin vivo modelsmicrobiome

Identifiers

PMID39338502
PMCPMC11434319

What OpenQuestion holds

Textmetadata
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.