Evidence map›Paper›PMID 30290236›Full record

ArticleBiochimica et biophysica acta. Molecular cell research2018

Rapid and accurate analysis of stem cell-derived extracellular vesicles with super resolution microscopy and live imaging.

Zubair Nizamudeen, Robert Markus, Rhys Lodge, Christopher Parmenter, Mark Platt, Lisa Chakrabarti, Virginie Sottile

Open access · hybridAbstract read
In one paragraph

Article in Biochimica et biophysica acta. Molecular cell research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
3.4field-weighted citation impact, top 6% of its field
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

66 citing papers in PubMed, 128 citations in OpenAlex.

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6 more citing papers are in PubMed but not listed here.

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

7 authors at 2 institutions in 1 country.

Zubair NizamudeenWolfson STEM Centre, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, UK.
Robert MarkusSchool of Life Sciences, University of Nottingham, UK.
Rhys LodgeSchool of Chemistry, University of Nottingham, UK.
Christopher ParmenterNanoscale and Microscale Research Centre, University of Nottingham, UK.
Mark PlattDepartment of Chemistry, Loughborough University, UK.
Lisa ChakrabartiSchool of Veterinary Science, University of Nottingham, UK.
Virginie SottileWolfson STEM Centre, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, UK. Electronic address: virginie.sottile@nottingham.ac.uk.
University of Nottingham · GBLoughborough University · GB

Funding

Biotechnology and Biological Sciences Research Council BB/L013827/1
6 · The paper itself

Abstract

Extracellular vesicles (EVs) have prevalent roles in cancer biology and regenerative medicine. Conventional techniques for characterising EVs including electron microscopy (EM), nanoparticle tracking analysis (NTA) and tuneable resistive pulse sensing (TRPS), have been reported to produce high variability in particle count (EM) and poor sensitivity in detecting EVs below 50 nm in size (NTA and TRPS), making accurate and unbiased EV analysis technically challenging. This study introduces direct stochastic optical reconstruction microscopy (d-STORM) as an efficient and reliable characterisation approach for stem cell-derived EVs. Using a photo-switchable lipid dye, d-STORM imaging enabled rapid detection of EVs down to 20-30 nm in size with higher sensitivity and lower variability compared to EM, NTA and TRPS techniques. Imaging of EV uptake by live stem cells in culture further confirmed the potential of this approach for downstream cell biology applications and for the analysis of vesicle-based cell-cell communication.

Indexed as

AnimalsCell-Derived MicroparticlesCells, CulturedMiceMicroscopy, ConfocalNanotechnologyParticle SizeStem CellsExtracellular vesicleStem cellSuper-resolution microscopy

Identifiers

PMID30290236
PMCPMC6203808
OpenAlexW2895208182

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.