Bond Breaks of Nucleotides by Dissociative Electron Transfer of Nonequilibrium Prehydrated Electrons: A New Molecular Mechanism for Reductive DNA Damage
Bibliographic record
Abstract
DNA damage is a central mechanism in the pathogenesis and treatment of human diseases, notably cancer. Little is known about reductive DNA damage in causing genetic mutations during oncogenesis and killing cancer cells during radiotherapy. The prehydrated electron (e(-)(pre)) has the highest yield among all the radicals generated in cells during ionizing radiation and has subpicosecond lifetimes (10(-13) s) and energies below 0 eV, but its role in DNA damage is unknown. In this work, our real-time measurements by femtosecond time-resolved laser spectroscopy have revealed that while adenine and cytosine can effectively trap an e(-)(pre) to form stable anions, thymidine and especially guanine are highly susceptible to dissociative electron transfer of e(-)(pre), leading to bond dissociation in DNA. Our finding demonstrates a dissociative electron transfer pathway for reductive DNA damage that might be related to various diseases such as cancer and stroke. Moreover, this finding challenges the conventional notion that damage to the genome is mainly induced by the oxidizing OH* radical and might eventually lead to improved radiotherapy of cancer and radioprotection of humans.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".