Evidence map›Paper›PMID 31447954›Full record

ReviewScience and technology of advanced materials2019

Latest advances in extracellular vesicles: from bench to bedside.

Tomofumi Yamamoto, Nobuyoshi Kosaka, Takahiro Ochiya

Abstract readReview
In one paragraph

Review in Science and technology of advanced materials, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

  1. Trial
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  5. Biodistribution studies ofApplied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine · 2025
    Article
  6. Review
  7. Review
  8. HIG-2 promotes glioma stemness and radioresistance mediated by IGFBP2-rich microparticles in hypoxia.Apoptosis : an international journal on programmed cell death · 2025
    Article
  9. Review
  10. Article
  11. Review
  12. Therapeutic and diagnostic applications of exosomes in colorectal cancer.Medical oncology (Northwood, London, England) · 2024
    Review
  13. Review
  14. Article
  15. Article
  16. Review
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  18. 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

3 authors.

Tomofumi YamamotoDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan.
Nobuyoshi KosakaDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan.
Takahiro OchiyaDivision of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) are small membraned vesicles and approximately 50-150 nm in diameter. Almost all of the type of cells releases the EVs and circulates in the body fluids. EVs contain multiple functional components, such as mRNAs, microRNAs (miRNAs), DNAs, and proteins, which can be transferred to the recipient cells, resulting in phenotypic changes. Recently, EV research has focused on their potential as a drug delivery vehicle and in targeted therapy against specific molecules. Moreover, some surface proteins are specific to particular diseases, and therefore, EVs also have promise as biomarkers. In this concise review, we summarize the latest research focused on EVs, which have the potential to become a promising drug delivery method, biomarker, and new therapeutic target for improving the outcomes of cancer patients.

Indexed as

30 Bio-inspired and biomedical materials600 Othersbiomarkerdrug delivery systemEV-based therapyexosomesExtracellular vesicles

Identifiers

PMID31447954
PMCPMC6691912

What OpenQuestion holds

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LicenceCC BY
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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.