Direct observation of ultrafast-electron-transfer reactions unravels high effectiveness of reductive DNA damage
Bibliographic record
Abstract
Both water and electron-transfer reactions play important roles in chemistry, physics, biology, and the environment. Oxidative DNA damage is a well-known mechanism, whereas the relative role of reductive DNA damage is unknown. The prehydrated electron (e(pre)-), a novel species of electrons in water, is a fascinating species due to its fundamental importance in chemistry, biology, and the environment. e(pre)- is an ideal agent to observe reductive DNA damage. Here, we report both the first in situ femtosecond time-resolved laser spectroscopy measurements of ultrafast-electron-transfer (UET) reactions of e(pre)- with various scavengers (KNO(3), isopropanol, and dimethyl sulfoxide) and the first gel electrophoresis measurements of DNA strand breaks induced by e(pre)- and OH(•) radicals co-produced by two-UV-photon photolysis of water. We strikingly found that the yield of reductive DNA strand breaks induced by each e(pre)- is twice the yield of oxidative DNA strand breaks induced by each OH(•) radical. Our results not only unravel the long-standing mystery about the relative role of radicals in inducing DNA damage under ionizing radiation, but also challenge the conventional notion that oxidative damage is the main pathway for DNA damage. The results also show the potential of femtomedicine as a new transdisciplinary frontier and the broad significance of UET reactions of e(pre)- in many processes in chemistry, physics, biology, and the environment.
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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 | 0.001 |
| Open science | 0.000 | 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".