Evidence mapPaperPMID 40891672Full record

RevieweLife2025

Toll-like receptors (TLRs) in the trained immunity era.

Lena Alexopoulou, Magali Irla

Abstract readReview
In one paragraph

Review in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Multi-Kingdom Synergy ofLife (Basel, Switzerland) · 2026
    Review
  5. Article
  6. Review
  7. Article
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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.

Lena Alexopoulou *Aix Marseille University, CNRS UMR7280, INSERM U1104 Centre d'immunologie de Marseille-Luminy (CIML), Marseille, France.ORCID https://orcid.org/0000-0003-4619-697X
Magali Irla *Aix Marseille University, CNRS UMR7280, INSERM U1104 Centre d'immunologie de Marseille-Luminy (CIML), Marseille, France.ORCID https://orcid.org/0000-0001-8803-9708

Funding

Agence Nationale de la Recherche ANR-18-CE120022Agence Nationale de la Recherche ANR-22-CE15-0045
6 · The paper itself

Abstract

The long-term functional adaptation of innate immune cells following an initial stimulation, referred to as trained immunity or innate immune memory, enhances responsiveness and protection against secondary infections. Toll-like receptors (TLRs), an evolutionarily conserved family, recognize microbial-associated molecular patterns, initiating innate and adaptive immune responses. TLR signaling cascades induce the production of pro-inflammatory cytokines, antimicrobial peptides, and interferons, promoting pathogen clearance, while also driving epigenetic and metabolic reprogramming that enhances immune responses and protection to subsequent challenges. However, TLRs also recognize endogenous ligands contributing to chronic inflammation and autoimmune diseases. This review examines the role of TLRs and their various agonists in mediating trained immunity across diverse immune cell types, with an emphasis on their dual role in protecting against infections and chronic inflammation. It highlights recent clinical trials of TLR agonists as immunomodulatory agents and their therapeutic potential in infectious diseases and cancer. By providing an in-depth analysis of TLR-driven trained immunity, this review highlights the extensive influence of TLRs on immune cell populations and their implications for the development of novel, broad-spectrum immunotherapies.

Indexed as

Adaptive ImmunityImmunity, InnateImmunologic MemoryToll-Like ReceptorsAnimalsHumansSignal TransductionTrained ImmunityToll-Like Receptorschronic inflammationimmunologyinflammationinnate immunitymicrobial infectionToll-like receptorstrained immunity

Identifiers

PMID40891672
PMCPMC12404611

What Socratic holds

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Registered trials

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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.