Biomolecular Damage Induced by Ionizing Radiation: The Direct and Indirect Effects of Low-Energy Electrons on DNA
Bibliographic record
Abstract
Many experimental and theoretical advances have recently allowed the study of direct and indirect effects of low-energy electrons (LEEs) on DNA damage. In an effort to explain how LEEs damage the human genome, researchers have focused efforts on LEE interactions with bacterial plasmids, DNA bases, sugar analogs, phosphate groups, and longer DNA moieties. Here, we summarize the current understanding of the fundamental mechanisms involved in LEE-induced damage of DNA and complex biomolecule films. Results obtained by several laboratories on films prepared and analyzed by different methods and irradiated with different electron-beam current densities and fluencies are presented. Despite varied conditions (e.g., film thicknesses and morphologies, intrinsic water content, substrate interactions, and extrinsic atmospheric compositions), comparisons show a striking resemblance in the types of damage produced and their yield functions. The potential of controlling this damage using molecular and nanoparticle targets with high LEE yields in targeted radiation-based cancer therapies is also discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".