DNA damage by radiation as a function of electron energy and interaction at the atomic level with Monte Carlo simulation
Bibliographic record
Abstract
In radiotherapy, X-ray or heavy ion beams target tumors to cause damage to their cell DNA. This damage is mainly induced by secondary low energy electrons. In this paper, we report the DNA molecular breaks at the atomic level as a function of electron energy and types of electron interactions using of Monte Carlo simulation. The number of DNA single and double strand breaks are compared to those from experimental results based on electron energies. In recent years, DNA atomistic models were introduced but still the simulations consider energy deposition in volumes of DNA or water equivalent material. We simulated a model of atomistic B-DNA in vacuum, forming 1122 base pairs of 30 nm in length. Each atom has been represented by a sphere whose radius equals the radius of van der Waals. We repeatedly simulated 10 million electrons for each energy from 4 eV to 500 eV and counted each interaction type with its position x, y, z in the volume of DNA. Based on the number and types of interactions at the atomic level, the number of DNA single and double strand breaks were calculated. We found that the dissociative electron attachment has the dominant effect on DNA strand breaks at energies below 10 eV compared to excitation and ionization. In addition, it is straightforward with our simulation to discriminate the strand and base breaks as a function of radiation interaction type and energy. In conclusion, the knowledge of DNA damage at the atomic level helps design direct internal therapeutic agents of cancer treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".