Wavelength‐ and Tissue‐dependent Variations in the Mutagenicity of Cyclobutane Pyrimidine Dimers in Mouse Skin
Bibliographic record
Abstract
The cyclobutane pyrimidine dimer (CPD) is a main mutagenic photolesion in DNA produced by UVR. We previously studied the wavelength-dependent kinetics of mutation induction efficiency using monochromatic UVR sources and transgenic mice developed for mutation assay and established the action spectra of UVR mutagenicity in the mouse epidermis and dermis. Here, we further established the action spectra of CPD and pyrimidine(6-4)pyrimidone photoproduct formation in the same tissues and in naked DNA using the same sources and mouse strain. Quantitative ELISA helped us estimate the photolesion formation efficiencies on a molecule-per-nucleotide basis. Using these action spectra, we confirmed that the UVR mutation mostly depends on CPD formation. Moreover, the mutagenicity of a CPD molecule (CPD mutagenicity) was found to vary by wavelength, peaking at approximately 313 nm in both the epidermis and dermis with similar wavelength-dependent patterns. Thus, the CPD formation efficiency is a main determinant of UVR mutagenicity in mouse skin, whereas a wavelength-dependent variation in the qualitative characteristics of CPD molecules also affects the mutagenic consequences of UVR insults. In addition, the CPD mutagenicity was always higher in the epidermis than in the dermis, suggesting different cellular responses to UVR between the two tissues irrespective of the wavelength.
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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 | 0.001 | 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 | 0.001 |
| 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".