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Novel Biological Approaches for Testing the Contributions of Single DSBs and DSB Clusters to the Biological Effects of High LET Radiation

Overview of attention for article published in Frontiers in oncology, June 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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Title
Novel Biological Approaches for Testing the Contributions of Single DSBs and DSB Clusters to the Biological Effects of High LET Radiation
Published in
Frontiers in oncology, June 2016
DOI 10.3389/fonc.2016.00163
Pubmed ID
Authors

Veronika Mladenova, Emil Mladenov, George Iliakis

Abstract

The adverse biological effects of ionizing radiation (IR) are commonly attributed to the generation of DNA double-strand breaks (DSBs). IR-induced DSBs are generated by clusters of ionizations, bear damaged terminal nucleotides, and frequently comprise base damages and single-strand breaks in the vicinity generating a unique DNA damage-clustering effect that increases DSB "complexity." The number of ionizations in clusters of different radiation modalities increases with increasing linear energy transfer (LET), and is thought to determine the long-known LET-dependence of the relative biological effectiveness (RBE). Multiple ionizations may also lead to the formation of DSB clusters, comprising two or more DSBs that destabilize chromatin further and compromise overall processing. DSB complexity and DSB-cluster formation are increasingly considered in the development of mathematical models of radiation action, which are then "tested" by fitting available experimental data. Despite a plethora of such mathematical models the ultimate goal, i.e., the "a priori" prediction of the radiation effect, has not yet been achieved. The difficulty partly arises from unsurmountable difficulties in testing the fundamental assumptions of such mathematical models in defined biological model systems capable of providing conclusive answers. Recently, revolutionary advances in methods allowing the generation of enzymatic DSBs at random or in well-defined locations in the genome, generate unique testing opportunities for several key assumptions frequently fed into mathematical modeling - including the role of DSB clusters in the overall effect. Here, we review the problematic of DSB-cluster formation in radiation action and present novel biological technologies that promise to revolutionize the way we address the biological consequences of such lesions. We describe new ways of exploiting the I-SceI endonuclease to generate DSB-clusters at random locations in the genome and describe the possible utility of Zn-finger nucleases and of TALENs in generating DSBs at defined genomic locations. Finally, we describe ways to harness the revolution of CRISPR/Cas9 technology to advance our understanding of the biological effects of DSBs. Collectively, these approaches promise to improve the focus of mathematical modeling of radiation action by providing testing opportunities for key assumptions on the underlying biology. They are also likely to further strengthen interactions between experimental radiation biologists and mathematical modelers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 20%
Student > Bachelor 6 14%
Student > Ph. D. Student 5 11%
Student > Master 5 11%
Student > Doctoral Student 3 7%
Other 4 9%
Unknown 12 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 43%
Agricultural and Biological Sciences 8 18%
Medicine and Dentistry 2 5%
Physics and Astronomy 1 2%
Immunology and Microbiology 1 2%
Other 0 0%
Unknown 13 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 May 2017.
All research outputs
#4,547,684
of 25,374,647 outputs
Outputs from Frontiers in oncology
#1,514
of 22,416 outputs
Outputs of similar age
#74,202
of 367,033 outputs
Outputs of similar age from Frontiers in oncology
#8
of 61 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 93% 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 367,033 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.