Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 197

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Quantification of human urinary exosomes by nanoparticle tracking analysis

Open access
Oosthuyzen, Wilna, Sime, Nicole E. L., Ivy, Jessica R., Turtle, Emma J., Street, Jonathan M., Pound, John, Bath, Louise E., Webb, David J., Gregory, Christopher D., Bailey, Matthew A., Dear, James W.·2013·The Journal of Physiology

Abstract

Exosomes are vesicles that are released from the kidney into the urine. They contain RNA and protein from the cell of origin and can track changes in renal physiology non-invasively. Current methods for the identification and quantification of urinary exosomes are time consuming and only semi-quantitative. In this study, we applied nanoparticle tracking analysis to human urine and identified particles with a range of sizes, including a subpopulation of characteristic exosomal size that labelled positively with antibodies to exosome proteins. Nanoparticle tracking analysis was able to track an increase in exosomal aquaporin 2 concentration following desmopressin treatment of a kidney cell line, a rodent model and a patient with central diabetes insipidus. With appropriate sample storage, nanoparticle tracking analysis has potential as a tool for the rapid characterization and quantification of exosomes in human urine. This new method can be used to develop urinary extracellular vesicles further as a non-invasive tool for investigating human renal physiology. Abstract Exosomes are vesicles that are released from the kidney into urine. They contain protein and RNA from the glomerulus and all sections of the nephron and represent a reservoir for biomarker discovery. Current methods for the identification and quantification of urinary exosomes are time consuming and only semi-quantitative. Nanoparticle tracking analysis (NTA) counts and sizes particles by measuring their Brownian motion in solution. In this study, we applied NTA to human urine and identified particles with a range of sizes. Using antibodies against the exosomal proteins CD24 and aquaporin 2 (AQP2), conjugated to a fluorophore, we could identify a subpopulation of CD24- and AQP2-positive particles of characteristic exosomal size. Extensive pre-NTA processing of urine was not necessary. However, the intra-assay variability in the measurement of exosome concentration was significantly reduced when an ultracentrifugation step preceded NTA. Without any sample processing, NTA tracked exosomal AQP2 upregulation induced by desmopressin stimulation of kidney collecting duct cells. Nanoparticle tracking analysis was also able to track changes in exosomal AQP2 concentration that followed desmopressin treatment of mice and a patient with central diabetes insipidus. When urine was stored at room temperature, 4°C or frozen, nanoparticle concentration was reduced; freezing at −80°C with the addition of protease inhibitors produced the least reduction. In conclusion, with appropriate sample storage, NTA has potential as a tool for the characterization and quantification of extracellular vesicles in human urine.

Overview

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 · 10.1113/jphysiol.2013.264069

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

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

Self-check

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

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

Citations

Cites

Cited by

See all 197

Metadata

Authors
Oosthuyzen, W., Sime, N. E. L., Ivy, J. R., Turtle, E. J., Street, J. M., Pound, J., Bath, L. E., Webb, D. J., Gregory, C. D., Bailey, M. A., & Dear, J. W.
Venue
The Journal of Physiology
Publisher
Wiley
Published
2013-10-29
Volume
591
Issue
23
Pages
5833-5842
ISSN
  • 0022-3751 (ISSN-L)
  • 1469-7793
OpenAlex
W2101484893
Cited by
197
References
1
FWCI
5.11
Type
journal article
Language
en
Open access
green

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.