Cited by 334Extracellular vesicles in diseasePlatelet Disorders and TreatmentsCaveolin-1 and cellular processes

Isolation and characterization of platelet-derived extracellular vesicles

Open access
Aatonen, Maria T., Öhman, Tiina, Nyman, Tuula A., Laitinen, Saara, Grönholm, Mikaela, Siljander, Pia R.‐M.·2014·Journal of Extracellular Vesicles

Abstract

BACKGROUND: Platelet-derived extracellular vesicles (EVs) participate, for example, in haemostasis, immunity and development. Most studies of platelet EVs have targeted microparticles, whereas exosomes and EV characterization under various conditions have been less analyzed. Studies have been hampered by the difficulty in obtaining EVs free from contaminating cells and platelet remnants. Therefore, we optimized an EV isolation protocol and compared the quantity and protein content of EVs induced by different agonists. METHODS: Platelets isolated with iodixanol gradient were activated by thrombin and collagen, lipopolysaccharide (LPS) or Ca(2+) ionophore. Microparticles and exosomes were isolated by differential centrifugations. EVs were quantitated by nanoparticle tracking analysis (NTA) and total protein. Size distributions were determined by NTA and electron microscopy. Proteomics was used to characterize the differentially induced EVs. RESULTS: The main EV populations were 100-250 nm and over 90% were <500 nm irrespective of the activation. However, activation pathways differentially regulated the quantity and the quality of EVs, which also formed constitutively. Thrombogenic activation was the most potent physiological EV-generator. LPS was a weak inducer of EVs, which had a selective protein content from the thrombogenic EVs. Ca(2+) ionophore generated a large population of protein-poor and unselectively packed EVs. By proteomic analysis, EVs were highly heterogeneous after the different activations and between the vesicle subpopulations. CONCLUSIONS: Although platelets constitutively release EVs, vesiculation can be increased, and the activation pathway determines the number and the cargo of the formed EVs. These activation-dependent variations render the use of protein content in sample normalization invalid. Since most platelet EVs are 100-250 nm, only a fraction has been analyzed by previously used methods, for example, flow cytometry. As the EV subpopulations could not be distinguished and large vesicle populations may be lost by differential centrifugation, novel methods are required for the isolation and the differentiation of all EVs.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3402/jev.v3.24692

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The anti-mitochondrial autoantibody repertoire and their antigenic targets remain mostly uncharacterized.

    “Despite the extensive literature regarding antibodies targeting the cardiolipin (also known as the mitochondrial antigen M1) in SLE, the anti-mitochondrial autoantibody repertoire and their antigenic targets remains mostly uncharacterized (12, 34–37).”

    From Autoantibodies in Systemic Lupus Erythematosus Target Mitochondrial RNA (2019) · cites this paper as [37]

    The Results section discusses the protein cargo of platelet-derived extracellular vesicles, not the characterization of anti-mitochondrial autoantibodies or their antigenic targets. Searches for those terms, cardiolipin, and SLE found no passage addressing the attributed claim; no page number was provided for the indexed passages. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Aatonen, M. T., Öhman, T., Nyman, T. A., Laitinen, S., Grönholm, M., & Siljander, P. R. ‐.
Affiliations
  • University of Helsinki (FI)
  • Finnish Red Cross (FI)
Corresponding author
Siljander, Pia R.‐M.
Venue
Journal of Extracellular Vesicles
Publisher
Wiley
Published
2014-01
Volume
3
Issue
1
ISSN
2001-3078 (ISSN-L)
OpenAlex
W1991525001
Cited by
333
References
55
Citations by year
2026: 20 · 2025: 25 · 2024: 40 · 2023: 27 · 2022: 40 · 2021: 28 · 2020: 20 · 2019: 35 · 2018: 16 · 2017: 25 · 2016: 41 · 2015: 15 · 2014: 1
FWCI
11.20
Type
journal article
Language
en
Open access
Locations
  • Journal of Extracellular Vesicles (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Magnus Ehrnroothin Säätiö
  • Otto A. Malm Lahjoitusrahasto
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
  • Health Sciences › Medicine › Hematology › Platelet Disorders and Treatments
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Caveolin-1 and cellular processes
Keywords
platelet-derived extracellular vesicles, exosomes, microparticles, EV isolation, platelet activation, thrombin, collagen, lipopolysaccharide, calcium ionophore, vesicle size distribution, EV proteome, vesicle heterogeneity, sample normalization

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review