Low-Energy Electron-Induced Damage in a Trinucleotide Containing 5-Bromouracil
Bibliographic record
Abstract
The reaction of low-energy electrons (LEEs; 10 eV) with 5'-TpXpT-3' (TXT), where X is uracil (U), thymine (T), and 5-bromouracil (5BrU), was examined by HPLC-UV analysis. The presence of 5BrU increased total damage by >50%. The radiation products of T5BrUT included TUT (40%), free U, T, 5BrU (23%), and fragments (13%). These products may be explained by initial capture of LEEs by the nucleobase to form a transient anion, followed by transfer of the electron within the molecule and cleavage of susceptible bonds by dissociative electron attachment (C-Br, C-N, or C-O bonds). In addition, these products may arise from the uracilyl-5-yl (U-5-yl) radicals that undergo H-atom abstraction from the sugar moiety. Interestingly, several products contained two sites of cleavage (U, pUT, and TUp). The formation of these products was linear with dose, and thus, they arise from the single-electron reactions. To explain these products, we propose that the reaction of LEEs (10 eV) involves the coupling of two dissociative processes in the same molecule (for example, dissociative excitation and dissociative electron attachment). The latter reactions may contribute to the formation of clustered damage, which is the most deleterious damage induced by ionizing radiation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".