Evidence map›Paper›PMID 37088150›Full record

ArticleMolecular & cellular proteomics : MCP2023

Ultrasensitive Protein Detection Technologies for Extracellular Vesicle Measurements.

Adnan Shami-Shah, Maia Norman, David R Walt

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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  14. Clinical Proteomics: A Promise Becoming Reality.Molecular & cellular proteomics : MCP · 2024
    Article
  15. Review
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

3 authors.

Adnan Shami-ShahDepartment of Pathology, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Maia NormanDepartment of Pathology, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA; Department of Neuroscience, Tufts University, School of Medicine, Boston, Massachusetts, USA.
David R WaltDepartment of Pathology, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA. Electronic address: dwalt@bwh.harvard.edu.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Extracellular vesicles (EVs) are nanoscopic, heterogenous, lipid-rich particles that carry a multitude of cargo biomolecules including proteins, nucleic acids, and metabolites. Although historically EVs were regarded as cellular debris with no intrinsic value, growing understanding of EV biogenesis has led to the realization that EVs facilitate intercellular communication and are sources of liquid biomarkers. EVs can be isolated and analyzed from a wide variety of accessible biofluids for biomarker discovery and diagnostic applications. There is a diversity of EVs from different biological compartments (e.g., cells and tissues), and some of these EVs are present at extremely low concentrations. Consequently, a challenge in the field is to find appropriate markers that enable selective isolation of these rare EVs. Many conventional protein detection technologies have limited sensitivity to detect low abundance biomarkers in EVs, limiting their use in EV research. Advances in ultrasensitive detection technologies are needed to harness the potential of EVs for clinical application. This Perspective highlights current EV research focusing on ultrasensitive detection technologies, their limitations, and areas of potential growth in the future.

Indexed as

Extracellular VesiclesProteinsBiomarkersBiomarkersProteinsbiofluidsbiomarkersextracellular vesiclesproteinsultrasensitive technology

Identifiers

PMID37088150
PMCPMC10326690

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.