Cell type-specific differences in redox regulation and proliferation after low UVA doses
Bibliographic record
Abstract
Ultraviolet A (UVA) radiation is harmful for living organisms but in low doses may stimulate cell proliferation. Our aim was to examine the relationships between exposure to different low UVA doses, cellular proliferation, and changes in cellular reactive oxygen species levels. In human colon cancer (HCT116) and melanoma (Me45) cells exposed to UVA doses comparable to environmental, the highest doses (30-50 kJ/m2) reduced clonogenic potential but some lower doses (1 and 10 kJ/m2) induced proliferation. This effect was cell type and dose specific. In both cell lines the levels of reactive oxygen species and nitric oxide fluctuated with dynamics which were influenced differently by UVA; in Me45 cells decreased proliferation accompanied the changes in the dynamics of H2O2 while in HCT116 cells those of superoxide. Genes coding for proteins engaged in redox systems were expressed differently in each cell line; transcripts for thioredoxin, peroxiredoxin and glutathione peroxidase showed higher expression in HCT116 cells whereas those for glutathione transferases and copper chaperone were more abundant in Me45 cells. We conclude that these two cell types utilize different pathways for regulating their redox status. Many mechanisms engaged in maintaining cellular redox balance have been described. Here we show that the different cellular responses to a stimulus such as a specific dose of UVA may be consequences of the use of different redox control pathways. Assays of superoxide and hydrogen peroxide level changes after exposure to UVA may clarify mechanisms of cellular redox regulation and help in understanding responses to stressing factors.
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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".