Evidence map›Paper›PMID 40214108›Full record

ReviewFEBS letters2025

The power of microRNA regulation-insights into immunity and metabolism.

Stefania Oliveto, Nicola Manfrini, Stefano Biffo

Abstract readReview
In one paragraph

Review in FEBS letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Population-Specific Exploration ofInternational journal of molecular sciences · 2026
    Article
  3. Review
  4. Review
  5. Review
  6. Targeted NMR signal enhancement of RNA by site-directed bis-nitroxide labeling.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  7. Review
  8. Article
  9. 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

3 authors.

Stefania OlivetoINGM, National Institute of Molecular Genetics "Romeo ed Enrica Invernizzi", Milan, Italy.ORCID https://orcid.org/0000-0001-7765-1918
Nicola ManfriniINGM, National Institute of Molecular Genetics "Romeo ed Enrica Invernizzi", Milan, Italy.
Stefano BiffoINGM, National Institute of Molecular Genetics "Romeo ed Enrica Invernizzi", Milan, Italy.

Funding

World Cancer Research Fund Grant 220037
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are a prominent class of small non-coding RNAs that control gene expression. This comprehensive review explores the intricate roles of miRNAs in metabolism and immunity, as well as the emerging field of immunometabolism. The core of this work delves into the functional and regulatory capabilities of miRNAs, examining their complex influence on glucose and lipid metabolism, as well as their pivotal roles in shaping T-cell development and function. Specifically, this review addresses how miRNAs orchestrate the complex interaction between cellular metabolic processes and immune responses, underscoring the essential nature of these small regulatory molecules in maintaining homeostasis. Finally, we examine the emerging role of Artificial Intelligence (AI) in miRNA research, focusing on how machine learning techniques are revolutionizing the identification and validation of potential miRNA biomarkers. By integrating these diverse aspects, this review underscores the multifaceted roles of miRNAs in biological processes and their significant potential in advancing biomedical research and clinical applications.

Indexed as

ImmunityMicroRNAsAnimalsArtificial IntelligenceGene Expression RegulationGlucoseHumansLipid MetabolismT-LymphocytesGlucoseMicroRNAsimmunityimmunometabolismmetabolismmicroRNAT cellsTreg

Identifiers

PMID40214108
PMCPMC12258419

What OpenQuestion 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 OpenQuestion graph.