Comparisons between the Direct and Indirect Effect of 1.5 keV X-rays and 0–30 eV Electrons on DNA: Base Lesions, Stand Breaks, Cross-Links, and Cluster Damages
Bibliographic record
Abstract
The interaction of low energy electrons (LEEs; 1–30 eV) with genomic material can induce multiple types of damage that may cause the loss of genetic information, mutations, genome instability, and cell death. For all damages measurable by electrophoresis, we provide the first complete set of G -values (yield of a specific product per energy deposited) induced in plasmid DNA by the direct and indirect effects of LEEs ( G LEE ) and 1.5 keV X-rays ( G X ) under identical conditions. Low energy photoelectrons are produced via X-rays incident on a tantalum (Ta) substrate covered with DNA and placed in a chamber filled with nitrogen at atmospheric pressure, under four different humidity levels, ranging from dry conditions to full hydration (Γ = 2.5 to Γ = 33, where Γ is the number of water molecules/nucleotide). Damage yields are measured as a function of X-ray fluence and humidity. G LEE values are between 2 and 27 times larger than those for X-rays. At Γ = 2.5 and 33, G LEE values for double strand breaks are 27 and 16 times larger than G X, respectively. The indirect effect contributes ∼50% to the total damage. These G -values allow quantification of potentially lethal lesions composed of strand breaks and/or base damages in the presence of varying amounts of water, i.e., closer to cellular conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".