Faster DNA Repair of Ultraviolet-Induced Cyclobutane Pyrimidine Dimers and Lower Sensitivity to Apoptosis in Human Corneal Epithelial Cells than in Epidermal Keratinocytes
Bibliographic record
Abstract
Absorption of UV rays by DNA generates the formation of mutagenic cyclobutane pyrimidine dimers (CPD) and pyrimidine (6-4) pyrimidone photoproducts (6-4PP). These damages are the major cause of skin cancer because in turn, they can lead to signature UV mutations. The eye is exposed to UV light, but the cornea is orders of magnitude less prone to UV-induced cancer. In an attempt to shed light on this paradox, we compared cells of the corneal epithelium and the epidermis for UVB-induced DNA damage frequency, repair and cell death sensitivity. We found similar CPD levels but a 4-time faster UVB-induced CPD, but not 6-4PP, repair and lower UV-induced apoptosis sensitivity in corneal epithelial cells than epidermal. We then investigated levels of DDB2, a UV-induced DNA damage recognition protein mostly impacting CPD repair, XPC, essential for the repair of both CPD and 6-4PP and p53 a protein upstream of the genotoxic stress response. We found more DDB2, XPC and p53 in corneal epithelial cells than in epidermal cells. According to our results analyzing the protein stability of DDB2 and XPC, the higher level of DDB2 and XPC in corneal epithelial cells is most likely due to an increased stability of the protein. Taken together, our results show that corneal epithelial cells have a better efficiency to repair UV-induced mutagenic CPD. On the other hand, they are less prone to UV-induced apoptosis, which could be related to the fact that since the repair is more efficient in the HCEC, the need to eliminate highly damaged cells by apoptosis is reduced.
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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".