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Anti-Cancer Drug Validation: the Contribution of Tissue Engineered Models

Overview of attention for article published in Stem Cell Reviews and Reports, February 2017
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95 Mendeley
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Title
Anti-Cancer Drug Validation: the Contribution of Tissue Engineered Models
Published in
Stem Cell Reviews and Reports, February 2017
DOI 10.1007/s12015-017-9720-x
Pubmed ID
Authors

Mariana R. Carvalho, Daniela Lima, Rui L. Reis, Joaquim M. Oliveira, Vitor M. Correlo

Abstract

Drug toxicity frequently goes concealed until clinical trials stage, which is the most challenging, dangerous and expensive stage of drug development. Both the cultures of cancer cells in traditional 2D assays and animal studies have limitations that cannot ever be unraveled by improvements in drug-testing protocols. A new generation of bioengineered tumors is now emerging in response to these limitations, with potential to transform drug screening by providing predictive models of tumors within their tissue context, for studies of drug safety and efficacy. Considering the NCI60, a panel of 60 cancer cell lines representative of 9 different cancer types: leukemia, lung, colorectal, central nervous system (CNS), melanoma, ovarian, renal, prostate and breast, we propose to review current "state of art" on the 9 cancer types specifically addressing the 3D tissue models that have been developed and used in drug discovery processes as an alternative to complement their study.

X Demographics

X Demographics

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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 18%
Student > Master 14 15%
Student > Ph. D. Student 10 11%
Student > Doctoral Student 8 8%
Student > Bachelor 7 7%
Other 16 17%
Unknown 23 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 19%
Medicine and Dentistry 8 8%
Agricultural and Biological Sciences 7 7%
Engineering 6 6%
Materials Science 4 4%
Other 21 22%
Unknown 31 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 March 2018.
All research outputs
#16,725,651
of 25,382,440 outputs
Outputs from Stem Cell Reviews and Reports
#649
of 1,036 outputs
Outputs of similar age
#199,888
of 324,444 outputs
Outputs of similar age from Stem Cell Reviews and Reports
#8
of 13 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,036 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 324,444 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.