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Concise Review: Mesenchymal Stem Cell-Based Drug Delivery: The Good, the Bad, the Ugly, and the Promise

Overview of attention for article published in Stem Cells Translational Medicine, August 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
twitter
19 X users
patent
5 patents
facebook
2 Facebook pages
reddit
3 Redditors

Readers on

mendeley
273 Mendeley
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Article details
Title
Concise Review: Mesenchymal Stem Cell-Based Drug Delivery: The Good, the Bad, the Ugly, and the Promise
Published in
Stem Cells Translational Medicine, August 2018
DOI 10.1002/sctm.18-0024
Pubmed ID
Authors
Abstract

The development of mesenchymal stem cells (MSCs) as cell-based drug delivery vectors for numerous clinical indications, including cancer, has significant promise. However, a considerable challenge for effective translation of these approaches is the limited tumor tropism and broad biodistribution observed using conventional MSCs, which raises concerns for toxicity to nontarget peripheral tissues (i.e., the bad). Consequently, there are a variety of synthetic engineering platforms in active development to improve tumor-selective targeting via increased homing efficiency and/or specificity of drug activation, some of which are already being evaluated clinically (i.e., the good). Unfortunately, the lack of robust quantification and widespread adoption of standardized methodologies with high sensitivity and resolution has made accurate comparisons across studies difficult, which has significantly impeded progress (i.e., the ugly). Herein, we provide a concise review of active and passive MSC homing mechanisms and biodistribution postinfusion; in addition to in vivo cell tracking methodologies and strategies to enhance tumor targeting with a focus on MSC-based drug delivery strategies for cancer therapy. Stem Cells Translational Medicine 2018;1-13.

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 273 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 273 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 36 13%
Student > Ph. D. Student 35 13%
Student > Bachelor 25 9%
Student > Master 25 9%
Student > Doctoral Student 14 5%
Other 23 8%
Unknown 115 42%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 12%
Medicine and Dentistry 30 11%
Agricultural and Biological Sciences 17 6%
Engineering 14 5%
Pharmacology, Toxicology and Pharmaceutical Science 13 5%
Other 40 15%
Unknown 126 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 February 2026.
All research outputs
#1,569,729
of 32,046,026 outputs
Outputs from Stem Cells Translational Medicine
#178
of 1,708 outputs
Outputs of similar age
#25,609
of 359,846 outputs
Outputs of similar age from Stem Cells Translational Medicine
#4
of 33 outputs
Altmetric has tracked 32,046,026 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,708 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.7. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 359,846 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.