Evidence map›Paper›PMID 34104390›Full record

ArticleJournal of tissue engineering

Spectroscopic profiling variations in extracellular vesicle biochemistry in a model of myogenesis.

Owen G Davies, Stephen Powell, Jonathan Js Rickard, Michael Clancy, Pola Goldberg Oppenheimer

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of tissue engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 3 institutions in 1 country.

Owen G DaviesSchool of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.ORCID https://orcid.org/0000-0003-0808-8695
Stephen PowellPhysical Sciences for Health Doctoral Training Centre, University of Birmingham, Birmingham, UK.
Jonathan Js RickardDepartment of Physics, Cavendish Laboratories, University of Cambridge, Cambridge, UK.
Michael ClancySchool of Chemical Engineering, University of Birmingham, Birmingham, UK.
Pola Goldberg OppenheimerSchool of Chemical Engineering, University of Birmingham, Birmingham, UK.
University of Birmingham · GBLoughborough University · GBUniversity of Cambridge · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Extracellular vesicles (EVs) hold value as accessible biomarkers for understanding cellular differentiation and related pathologies. Herein, EV biomarkers in models of skeletal muscle dormancy and differentiation have been comparatively profiled using Raman spectroscopy (RS). Significant variations in the biochemical fingerprint of EVs were detected, with an elevation in peaks associated with lipid and protein signatures during early myogenic differentiation (day 2). Principal component analysis revealed a clear separation between the spectra of EVs derived from myogenic and senescent cell types, with non-overlapping interquartile ranges and population median. Observations aligned with nanoparticle tracking data, highlighting a significant early reduction in EV concentration in senescent myoblast cultures as well as notable variations in EV morphology and diameter. As differentiation progressed physical and biochemical differences in the properties of EVs became less pronounced. This study demonstrates the applicability of RS as a high-resolution analytical method for profiling biochemical changes in EVs during early myogenesis.

Indexed as

analyticaldifferentiationRaman spectroscopyskeletal muscleVesicle

Identifiers

PMID34104390
PMCPMC8172953
OpenAlexW3166111859

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.