Evidence map›Paper›PMID 39039539›Full record

ReviewCell communication and signaling : CCS2024

Advancing stroke therapy: innovative approaches with stem cell-derived extracellular vesicles.

Jiahao Song, Da Zhou, Lili Cui, Chuanjie Wu, Lina Jia, Mengqi Wang, Jingrun Li, Jingyuan Ya, Xunming Ji, Ran Meng

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cell communication and signaling : CCS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Extracellular vesicles in laboratory medicine: a review and outlook.Frontiers in cell and developmental biology · 2025
    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

10 authors.

Jiahao Song *Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.ORCID 0009-0001-7809-0187
Da Zhou *Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. popdoctor@foxmail.com.ORCID 0000-0003-1376-4213
Lili CuiDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.ORCID 0009-0005-1486-2503
Chuanjie WuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Lina JiaDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Mengqi WangDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Jingrun LiDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Jingyuan YaAcademic Unit of Mental Health and Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, England.
Xunming JiDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Ran MengDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. victor65@126.com.ORCID 0000-0003-1190-4710

Funding

National Natural Science Foundation of China 82101390, 82171297, and 82001258the General Science and Technology Programme of Beijing Municipal Education Commission KM202110025020
6 · The paper itself

Abstract

Stroke is a leading cause of mortality and long-term disability globally, with acute ischemic stroke (AIS) being the most common subtype. Despite significant advances in reperfusion therapies, their limited time window and associated risks underscore the necessity for novel treatment strategies. Stem cell-derived extracellular vesicles (EVs) have emerged as a promising therapeutic approach due to their ability to modulate the post-stroke microenvironment and facilitate neuroprotection and neurorestoration. This review synthesizes current research on the therapeutic potential of stem cell-derived EVs in AIS, focusing on their origin, biogenesis, mechanisms of action, and strategies for enhancing their targeting capacity and therapeutic efficacy. Additionally, we explore innovative combination therapies and discuss both the challenges and prospects of EV-based treatments. Our findings reveal that stem cell-derived EVs exhibit diverse therapeutic effects in AIS, such as promoting neuronal survival, diminishing neuroinflammation, protecting the blood-brain barrier, and enhancing angiogenesis and neurogenesis. Various strategies, including targeting modifications and cargo modifications, have been developed to improve the efficacy of EVs. Combining EVs with other treatments, such as reperfusion therapy, stem cell transplantation, nanomedicine, and gut microbiome modulation, holds great promise for improving stroke outcomes. However, challenges such as the heterogeneity of EVs and the need for standardized protocols for EV production and quality control remain to be addressed. Stem cell-derived EVs represent a novel therapeutic avenue for AIS, offering the potential to address the limitations of current treatments. Further research is needed to optimize EV-based therapies and translate their benefits to clinical practice, with an emphasis on ensuring safety, overcoming regulatory hurdles, and enhancing the specificity and efficacy of EV delivery to target tissues.

Indexed as

Extracellular VesiclesStem CellsStrokeAnimalsHumansStem Cell TransplantationExtracellular vesiclesNeuroprotectionStem cell-derivedStrokeTherapeutic approach

Identifiers

PMID39039539
PMCPMC11265156

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.