Evidence map›Paper›PMID 40430942›Full record

ReviewPharmaceutics2025

From Mechanism to Therapy: The Role of MSC-EVs in Alleviating Radiation-Induced Injuries.

Chong Huang, Heng Li, Zhiyue Zhang, Ting Mou, Dandan Wang, Chenlu Li, Lei Tian, Chunlin Zong

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. FeBioengineering (Basel, Switzerland) · 2026
    Article
  4. Radiomitigators: Breakthroughs in Post-Radiation Recovery.Antioxidants (Basel, Switzerland) · 2026
    Review
  5. Article
  6. Review
  7. 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

8 authors.

Chong HuangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.ORCID 0009-0003-2168-6523
Heng LiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.
Zhiyue ZhangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.
Ting MouSchool of Stomatology, Jiamusi University, Jiamusi 154007, China.
Dandan WangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.
Chenlu LiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.
Lei TianState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.ORCID 0000-0002-1929-3953
Chunlin ZongState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an 710032, China.ORCID 0000-0003-1271-8741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiation injury is a severe issue in both nuclear accidents and cancer radiotherapy. Ionizing radiation impairs the regenerative and repair capabilities of tissues and organs, resulting in a scarcity of effective therapeutic approaches to prevent or mitigate such injuries. Mesenchymal stem cells (MSCs) possess favorable biological characteristics and have emerged as ideal candidates for the treatment of radiation injury. However, the use of MSCs as therapeutic agents is associated with uncertainties in therapeutic efficacy, transient effects, and the risk of immune rejection. Recent advances in research have revealed that extracellular vesicles (EVs) derived from mesenchymal stem cells (MSC-EVs) exhibit similar beneficial properties to MSCs and represent a promising cell-free therapy for mitigating radiation injuries. MSC-EVs are enriched with microRNAs (miRNAs), proteins, and lipids, which can modulate immune responses, inflammatory reactions, cell survival, and proliferation in irradiated tissues. This review synthesizes recent studies on the application of MSC-EVs in radiation injury, focusing on the therapeutic effects and mechanisms of MSC-EVs derived from various sources in radiation-induced diseases of different organs. The therapeutic potential of MSC-EVs for radiation injury provides valuable insights for addressing ionizing radiation-induced injuries and offers a reference for future clinical applications.

Indexed as

extracellular vesiclesmesenchymal stem cellsradiation-induced injuries

Identifiers

PMID40430942
PMCPMC12114651

What OpenQuestion 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 OpenQuestion graph.