Reduced host cell reactivation of oxidatively damaged DNA in ageing human fibroblasts
Bibliographic record
Abstract
Many reports have linked oxidative damage to DNA and the associated avoidance and/or repair processes to carcinogenesis, ageing and neurodegeneration. Cancer incidence increases with age and there is evidence that oxidative stress plays a role in human ageing and neurodegeneration. Several reports have suggested that the accumulation of unrepaired DNA lesions plays a causal role in mammalian ageing. Since base excision repair (BER) is the main pathway for the repair of oxidative DNA lesions, the relationship of BER to human ageing and carcinogenesis is of considerable interest. The aim of the present study was to examine the relationship between donor age and increasing time of cells in tissue culture and the repair of oxidative DNA damage in primary human skin fibroblasts. Methylene blue (MB) acts as a photosensitizer and after excitation by visible light (VL) produces reactive oxygen species that result in oxidative damage to DNA. MB+VL produce predominantly 8-hydroxyguanine as well as other single base modifications in DNA that are repaired by BER. We used host cell reactivation (HCR) of a non-replicating recombinant human adenovirus, Ad5CMVlacZ, which expresses the β-galactosidase (β-gal) reporter gene, to measure BER of MB+VL-damaged DNA. HCR of β-gal activity for the MB+VL-treated reporter gene was examined in 10 fibroblast strains from normal donors of ages 2 to 82. The effect of cell passage number on HCR was also examined in human skin fibroblasts from 2 normal donors. We found a significant reduction in HCR with increasing cell passage number, indicating that BER decreases with increasing time of cells grown in tissue culture. We also found a significant correlation of donor age with HCR of the MB+VL-treated reporter gene for high passage number, but not for low passage number fibroblasts. The present study provides evidence that a decrease in BER of oxidatively damaged DNA may play a role in carcinogenesis, ageing and neurodegeneration.
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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) | 0.002 | 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".