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Should we use cells, biomaterials, or tissue engineering for cartilage regeneration?

Overview of attention for article published in Stem Cell Research & Therapy, April 2016
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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16 X users
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6 patents

Citations

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137 Dimensions

Readers on

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282 Mendeley
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Title
Should we use cells, biomaterials, or tissue engineering for cartilage regeneration?
Published in
Stem Cell Research & Therapy, April 2016
DOI 10.1186/s13287-016-0314-3
Pubmed ID
Authors

Jonathan C. Bernhard, Gordana Vunjak-Novakovic

Abstract

For a long time, cartilage has been a major focus of the whole field of tissue engineering, both because of the constantly growing need for more effective options for joint repair and the expectation that this apparently simple tissue will be easy to engineer. After several decades, cartilage regeneration has proven to be anything but easy. With gratifying progress in our understanding of the factors governing cartilage development and function, and cell therapy being successfully used for several decades, there is still a lot to do. We lack reliable methods to generate durable articular cartilage that would resemble the original tissue lost to injury or disease. The question posed here is whether the answer would come from the methods using cells, biomaterials, or tissue engineering. We present a concise review of some of the most meritorious efforts in each area, and propose that the solution will most likely emerge from the ongoing attempts to recapitulate certain aspects of native cartilage development. While an ideal recipe for cartilage regeneration is yet to be formulated, we believe that it will contain cell, biomaterial, and tissue engineering approaches, blended into an effective method for seamless repair of articular cartilage.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 282 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Spain 1 <1%
United States 1 <1%
Switzerland 1 <1%
Unknown 278 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 61 22%
Student > Master 44 16%
Student > Bachelor 40 14%
Researcher 25 9%
Student > Doctoral Student 15 5%
Other 35 12%
Unknown 62 22%
Readers by discipline Count As %
Engineering 46 16%
Biochemistry, Genetics and Molecular Biology 42 15%
Medicine and Dentistry 35 12%
Agricultural and Biological Sciences 25 9%
Materials Science 20 7%
Other 37 13%
Unknown 77 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 December 2023.
All research outputs
#1,842,488
of 25,093,754 outputs
Outputs from Stem Cell Research & Therapy
#97
of 2,725 outputs
Outputs of similar age
#29,685
of 305,328 outputs
Outputs of similar age from Stem Cell Research & Therapy
#2
of 34 outputs
Altmetric has tracked 25,093,754 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,725 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 96% 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 305,328 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 90% 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 97% of its contemporaries.