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Comparison of membrane affinity-based method with size-exclusion chromatography for isolation of exosome-like vesicles from human plasma

Overview of attention for article published in Journal of Translational Medicine, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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8 tweeters
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2 patents

Citations

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158 Dimensions

Readers on

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259 Mendeley
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Title
Comparison of membrane affinity-based method with size-exclusion chromatography for isolation of exosome-like vesicles from human plasma
Published in
Journal of Translational Medicine, January 2018
DOI 10.1186/s12967-017-1374-6
Pubmed ID
Authors

Ruzena Stranska, Laurens Gysbrechts, Jens Wouters, Pieter Vermeersch, Katarzyna Bloch, Daan Dierickx, Graciela Andrei, Robert Snoeck

Abstract

Plasma extracellular vesicles (EVs), especially exosome-like vesicles (ELVs), are being increasingly explored as a source of potential noninvasive disease biomarkers. The discovery of blood-based biomarkers associated with ELVs requires methods that isolate high yields of these EVs without significant contamination with highly abundant plasma proteins and lipoproteins. The rising interest in blood-based EV-associated biomarkers has led to the rapid development of novel EV isolation methods. However, the field suffers from a lack of standardization and often, new techniques are used without critical evaluation. Size exclusion chromatography (SEC) has become the method of choice for rapid isolation of relatively pure EVs from plasma, yet it has technical limitations for certain downstream applications. The recently released exoEasy kit (Qiagen) is a new membrane affinity spin column method for the isolation of highly pure EVs from biofluids with the potential to overcome most of the limitations of SEC. By using multiple complementary techniques we assessed the performance of the exoEasy kit in isolating ELVs from 2 ml of human plasma and compared it with the SEC qEV column (Izon Science). Our data show that exoEasy kit isolates a heterogenous mixture of particles with a larger median diameter, broader size range and a higher yield than the SEC qEV column. The exclusive presence of small RNAs in the particles and the total RNA yield were comparable to the SEC qEV column. Despite being less prone to low density lipoprotein contamination than the SEC qEV column, the overall purity of exoEasy kit EV preparations was suboptimal. The low particle-protein ratio, significant amount of albumin, very low levels of exosome-associated proteins and propensity to triglyceride-rich lipoprotein contamination suggest isolation of mainly non-ELVs and co-isolation of plasma proteins and certain lipoproteins by the exoEasy kit. We demonstrate that performance of exoEasy kit for the isolation of ELVs for biomarker discovery is inferior to the SEC qEV column. This comprehensive evaluation of a novel EV isolation method contributes to the acceleration of the discovery of EV-associated biomarkers and the development of EV-based diagnostics.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 259 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 259 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 56 22%
Researcher 40 15%
Student > Bachelor 31 12%
Student > Master 27 10%
Student > Doctoral Student 17 7%
Other 31 12%
Unknown 57 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 67 26%
Agricultural and Biological Sciences 34 13%
Medicine and Dentistry 28 11%
Chemistry 11 4%
Immunology and Microbiology 11 4%
Other 40 15%
Unknown 68 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2020.
All research outputs
#2,743,392
of 17,366,233 outputs
Outputs from Journal of Translational Medicine
#414
of 3,205 outputs
Outputs of similar age
#82,873
of 416,258 outputs
Outputs of similar age from Journal of Translational Medicine
#30
of 262 outputs
Altmetric has tracked 17,366,233 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,205 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 416,258 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 262 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.