Formation and repair of oxidatively generated damage in cellular DNA
Bibliographic record
Abstract
In this review article, emphasis is placed on the critical survey of available data concerning modified nucleobase and 2-deoxyribose products that have been identified in cellular DNA following exposure to a wide variety of oxidizing species and agents including, hydroxyl radical, one-electron oxidants, singlet oxygen, hypochlorous acid and ten-eleven translocation enzymes. In addition, information is provided about the generation of secondary oxidation products of 8-oxo-7,8-dihydroguanine and nucleobase addition products with reactive aldehydes arising from the decomposition of lipid peroxides. It is worth noting that the different classes of oxidatively generated DNA damage that consist of single lesions, intra- and interstrand cross-links were unambiguously assigned and quantitatively detected on the basis of accurate measurements involving in most cases high performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry. The reported data clearly show that the frequency of DNA lesions generated upon severe oxidizing conditions, including exposure to ionizing radiation is low, at best a few modifications per 106 normal bases. Application of accurate analytical measurement methods has also allowed the determination of repair kinetics of several well-defined lesions in cellular DNA that however concerns so far only a restricted number of cases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".