Evidence map›Paper›PMID 35054584›Full record

ReviewMembranes2021

Improving Isolation of Extracellular Vesicles by Utilizing Nanomaterials.

Haiyang Zhang, Qi Zhang, Yuanyuan Deng, Mengxi Chen, Chenxi Yang

Open access · goldAbstract readReview
In one paragraph

Review in Membranes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Rapid isolation method for extracellular vesicles based on FeFrontiers in bioengineering and biotechnology · 2024
    Article
  7. Review
  8. Article
  9. 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 2 institutions in 1 country.

Haiyang ZhangCollege of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.ORCID 0000-0003-4056-1999
Qi ZhangCollege of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Yuanyuan DengSchool of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Mengxi ChenCollege of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Chenxi YangSchool of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0003-3219-704X
Soochow University · CNSoutheast University · CN

Funding

National Natural Science Foundation of China 21703163
6 · The paper itself

Abstract

Extracellular vesicles (EVs) as the new form of cellular communication have been demonstrated their potential use for disease diagnosis, prognosis and treatment. EVs are vesicles with a lipid bilayer and are present in various biofluids, such as blood, saliva and urine. Therefore, EVs have emerged as one of the most appealing sources for the discovery of clinical biomarkers. However, isolation of the target EVs from different biofluids is required for the use of EVs as diagnostic and therapeutic entities in clinical settings. Owing to their unique properties and versatile functionalities, nanomaterials have been widely investigated for EV isolation with the aim to provide rapid, simple, and efficient EV enrichment. Herein, this review presents the progress of nanomaterial-based isolations for EVs over the past five years (from 2017 to 2021) and discusses the use of nanomaterials for EV isolations based on the underlying mechanism in order to offer insights into the design of nanomaterials for EV isolations.

Indexed as

extracellular vesiclesnanomaterial-based isolationnanomaterials

Identifiers

PMID35054584
PMCPMC8780510
OpenAlexW4206689755

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.