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Mathematical Optimization of the Combination of Radiation and Differentiation Therapies for Cancer

Overview of attention for article published in Frontiers in oncology, January 2013
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1 X user

Citations

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Title
Mathematical Optimization of the Combination of Radiation and Differentiation Therapies for Cancer
Published in
Frontiers in oncology, January 2013
DOI 10.3389/fonc.2013.00052
Pubmed ID
Authors

Jeff W. N. Bachman, Thomas Hillen

Abstract

Cancer stem cells (CSC) are considered to be a major driver of cancer progression and successful therapies must control CSCs. However, CSC are often less sensitive to treatment and they might survive radiation and/or chemotherapies. In this paper we combine radiation treatment with differentiation therapy. During differentiation therapy, a differentiation promoting agent is supplied (e.g., TGF-beta) such that CSCs differentiate and become more radiosensitive. Then radiation can be used to control them. We consider three types of cancer: head and neck cancer, brain cancers (primary tumors and metastatic brain cancers), and breast cancer; and we use mathematical modeling to show that combination therapy of the above type can have a large beneficial effect for the patient; increasing treatment success and reducing side effects.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Poland 1 3%
Germany 1 3%
Canada 1 3%
Unknown 25 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 28%
Researcher 4 14%
Student > Doctoral Student 3 10%
Professor > Associate Professor 3 10%
Student > Master 3 10%
Other 7 24%
Unknown 1 3%
Readers by discipline Count As %
Mathematics 9 31%
Medicine and Dentistry 6 21%
Agricultural and Biological Sciences 5 17%
Engineering 3 10%
Physics and Astronomy 2 7%
Other 2 7%
Unknown 2 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 March 2013.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from Frontiers in oncology
#15,918
of 22,416 outputs
Outputs of similar age
#258,420
of 289,004 outputs
Outputs of similar age from Frontiers in oncology
#194
of 328 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% 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 289,004 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 328 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.