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| Content Provider | PubMed Central |
|---|---|
| Author | Bernal, M. A. Dealmeida, C. E. Incerti, S. Champion, C. Ivanchenko, V. Francis, Z. |
| Copyright Year | 2015 |
| Abstract | Purpose. To study the influence of DNA configuration on the direct damage yield. No indirect effect has been accounted for. Methods. The GEANT4-DNA code was used to simulate the interactions of protons and alpha particles with geometrical models of the A-, B-, and Z-DNA configurations. The direct total, single, and double strand break yields and site-hit probabilities were determined. Certain features of the energy deposition process were also studied. Results. A slight increase of the site-hit probability as a function of the incident particle linear energy transfer was found for each DNA configuration. Each DNA form presents a well-defined site-hit probability, independently of the particle linear energy transfer. Approximately 70% of the inelastic collisions and ~60% of the absorbed dose are due to secondary electrons. These fractions are slightly higher for protons than for alpha particles at the same incident energy. Conclusions. The total direct strand break yield for a given DNA form depends weakly on DNA conformation topology. This yield is practically determined by the target volume of the DNA configuration. However, the double strand break yield increases with the packing ratio of the DNA double helix; thus, it depends on the DNA conformation. |
| Related Links | http://dx.doi.org/10.1155/2015/417501 |
| Starting Page | 417501 |
| File Format | |
| ISSN | 17486718 |
| e-ISSN | 17486718 |
| Journal | Computational and Mathematical Methods in Medicine |
| Volume Number | 2015 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2015-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology Modeling and Simulation |
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