Evidence map›Paper›PMID 41410975›Full record

ReviewCardiovascular drugs and therapy2026

Extracellular Vesicles in Cardiac Cell Crosstalk: from Intercellular Communication to Clinical Translation.

Rahul Sanwlani, Patrizia Camelliti

Abstract readReview
In one paragraph

Review in Cardiovascular drugs and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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.

Rahul SanwlaniFaculty of Health and Medical Sciences, School of Biosciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom. rs0093@surrey.ac.uk.ORCID 0000-0002-0282-6768
Patrizia CamellitiFaculty of Health and Medical Sciences, School of Biosciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.

Funding

British Heart Foundation PG/22/11172
6 · The paper itself

Abstract

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality globally, accounting for nearly one-third of deaths worldwide. Intercellular communication between cardiomyocytes and non-cardiomyocytes is fundamental to maintaining cardiac homeostasis and adapting to stress or injury. Among the mediators of this communication, extracellular vesicles (EVs) have emerged as pivotal regulators of cardiac function and remodelling, transporting bioactive molecules that reflect the state and origin of their parent cells. This review provides a systems-level synthesis of EV-mediated crosstalk in the heart, integrating evidence from cardiomyocyte- and non-cardiomyocyte-derived EVs, including fibroblast, endothelial, vascular smooth muscle, and immune cell sources. We discuss how these vesicles orchestrate signalling networks that influence cardiac remodelling, injury response, and disease progression. Distinct from prior reviews, our article extends beyond mechanistic summaries to explore the translational continuum of cardiac EVs-from their potential as diagnostic and prognostic biomarkers to emerging therapeutic and bioengineering strategies. Finally, we critically evaluate current technical and regulatory barriers impeding clinical translation, including isolation, characterisation, and validation challenges, and propose a forward-looking roadmap to advance EV-based diagnostics and therapeutics in cardiovascular medicine.

Indexed as

Cardiovascular DiseasesCell CommunicationExtracellular VesiclesMyocytes, CardiacAnimalsHumansSignal TransductionTranslational Research, BiomedicalCardiac extracellular vesiclesCardiac fibroblast EVsCardiac nonmyocytesCardiac pathophysiologyCardiomyocytesCardiovascular diseases

Identifiers

PMID41410975
PMCPMC13388533

What OpenQuestion holds

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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.