Evidence map›Paper›PMID 34277609›Full record

ReviewFrontiers in cell and developmental biology2021

Nanoparticles for Stem Cell Tracking and the Potential Treatment of Cardiovascular Diseases.

Huihua Huang, Xuejun Du, Zhiguo He, Zifeng Yan, Wei Han

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Molecular and cellular imaging of the eye.Biomedical optics express · 2024
    Review
  7. Review
  8. CellularInternational journal of molecular sciences · 2023
    Article
  9. Article
  10. Article
  11. 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

5 authors at 2 institutions in 1 country.

Huihua HuangEmergency Department, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China.
Xuejun DuEmergency Department, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China.
Zhiguo HeAdvanced Materials Institute, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China.
Zifeng YanAdvanced Materials Institute, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China.
Wei HanEmergency Department, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China.
Shenzhen University · CNNano and Advanced Materials Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stem cell-based therapies have been shown potential in regenerative medicine. In these cells, mesenchymal stem cells (MSCs) have the ability of self-renewal and being differentiated into different types of cells, such as cardiovascular cells. Moreover, MSCs have low immunogenicity and immunomodulatory properties, and can protect the myocardium, which are ideal qualities for cardiovascular repair. Transplanting mesenchymal stem cells has demonstrated improved outcomes for treating cardiovascular diseases in preclinical trials. However, there still are some challenges, such as their low rate of migration to the ischemic myocardium, low tissue retention, and low survival rate after the transplantation. To solve these problems, an ideal method should be developed to precisely and quantitatively monitor the viability of the transplanted cells

Indexed as

cardiovascular diseasesimaging techniquemesenchymal stem cellnanoparticlesstem cell therapy

Identifiers

PMID34277609
PMCPMC8283769
OpenAlexW3177392006

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.