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Engineering in-vitro stem cell-based vascularized bone models for drug screening and predictive toxicology

Overview of attention for article published in Stem Cell Research & Therapy, April 2018
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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4 X users

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Title
Engineering in-vitro stem cell-based vascularized bone models for drug screening and predictive toxicology
Published in
Stem Cell Research & Therapy, April 2018
DOI 10.1186/s13287-018-0847-8
Pubmed ID
Authors

Alessandro Pirosa, Riccardo Gottardi, Peter G. Alexander, Rocky S. Tuan

Abstract

The production of veritable in-vitro models of bone tissue is essential to understand the biology of bone and its surrounding environment, to analyze the pathogenesis of bone diseases (e.g., osteoporosis, osteoarthritis, osteomyelitis, etc.), to develop effective therapeutic drug screening, and to test potential therapeutic strategies. Dysregulated interactions between vasculature and bone cells are often related to the aforementioned pathologies, underscoring the need for a bone model that contains engineered vasculature. Due to ethical restraints and limited prediction power of animal models, human stem cell-based tissue engineering has gained increasing relevance as a candidate approach to overcome the limitations of animals and to serve as preclinical models for drug testing. Since bone is a highly vascularized tissue, the concomitant development of vasculature and mineralized matrix requires a synergistic interaction between osteogenic and endothelial precursors. A number of experimental approaches have been used to achieve this goal, such as the combination of angiogenic factors and three-dimensional scaffolds, prevascularization strategies, and coculture systems. In this review, we present an overview of the current models and approaches to generate in-vitro stem cell-based vascularized bone, with emphasis on the main challenges of vasculature engineering. These challenges are related to the choice of biomaterials, scaffold fabrication techniques, and cells, as well as the type of culturing conditions required, and specifically the application of dynamic culture systems using bioreactors.

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The data shown below were collected from the profiles of 4 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 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 215 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 16%
Student > Master 33 15%
Student > Bachelor 31 14%
Researcher 27 13%
Student > Doctoral Student 12 6%
Other 18 8%
Unknown 60 28%
Readers by discipline Count As %
Engineering 34 16%
Biochemistry, Genetics and Molecular Biology 30 14%
Medicine and Dentistry 26 12%
Materials Science 14 7%
Agricultural and Biological Sciences 10 5%
Other 28 13%
Unknown 73 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 April 2018.
All research outputs
#7,239,292
of 23,043,346 outputs
Outputs from Stem Cell Research & Therapy
#713
of 2,431 outputs
Outputs of similar age
#125,431
of 326,937 outputs
Outputs of similar age from Stem Cell Research & Therapy
#26
of 70 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,431 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 70% 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 326,937 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.