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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 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
1 news outlet
twitter
20 X users
patent
2 patents
facebook
2 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
204 Dimensions

Readers on

mendeley
239 Mendeley
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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

Timothy E. G. Krueger, Daniel L. J. Thorek, Samuel R. Denmeade, John T. Isaacs, W. Nathaniel Brennen

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 239 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 239 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 14%
Student > Ph. D. Student 33 14%
Student > Master 22 9%
Student > Bachelor 20 8%
Student > Doctoral Student 14 6%
Other 22 9%
Unknown 94 39%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 12%
Medicine and Dentistry 27 11%
Agricultural and Biological Sciences 15 6%
Engineering 14 6%
Pharmacology, Toxicology and Pharmaceutical Science 12 5%
Other 36 15%
Unknown 107 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 20 June 2023.
All research outputs
#1,409,034
of 25,013,816 outputs
Outputs from Stem Cells Translational Medicine
#177
of 1,588 outputs
Outputs of similar age
#29,340
of 336,512 outputs
Outputs of similar age from Stem Cells Translational Medicine
#4
of 34 outputs
Altmetric has tracked 25,013,816 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,588 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.2. This one has done well, scoring higher than 88% 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 336,512 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 91% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.