Hyperthermal (1–100eV) nitrogen ion scattering damage to D-ribose and 2-deoxy-D-ribose films
Bibliographic record
Abstract
Highly charged heavy ion traversal of a biological medium can produce energetic secondary fragment ions. These fragment ions can in turn cause collisional and reactive scattering damage to DNA. Here we report hyperthermal (1-100 eV) scattering of one such fragment ion (N(+)) from biologically relevant sugar molecules D-ribose and 2-deoxy-D-ribose condensed on polycrystalline Pt substrate. The results indicate that N(+) ion scattering at kinetic energies down to 10 eV induces effective decomposition of both sugar molecules and leads to the desorption of abundant cation and anion fragments. Use of isotope-labeled molecules (5-(13)C D-ribose and 1-D D-ribose) partly reveals some site specificity of the fragment origin. Several scattering reactions are also observed. Both ionic and neutral nitrogen atoms abstract carbon from the molecules to form CN(-) anion at energies down to approximately 5 eV. N(+) ions also abstract hydrogen from hydroxyl groups of the molecules to form NH(-) and NH(2) (-) anions. A fraction of OO(-) fragments abstract hydrogen to form OH(-). The formation of H(3)O(+) ions also involves hydrogen abstraction as well as intramolecular proton transfer. These findings suggest a variety of severe damaging pathways to DNA molecules which occur on the picosecond time scale following heavy ion irradiation of a cell, and prior to the late diffusion-limited homogeneous chemical processes.
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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".