<i>N</i>-Acetylcysteine Protects Melanocytes against Oxidative Stress/Damage and Delays Onset of Ultraviolet-Induced Melanoma in Mice
Bibliographic record
Abstract
PURPOSE: UV radiation is the major environmental risk factor for melanoma and a potent inducer of oxidative stress, which is implicated in the pathogenesis of several malignancies. We evaluated whether the thiol antioxidant N-acetylcysteine (NAC) could protect melanocytes from UV-induced oxidative stress/damage in vitro and from UV-induced melanoma in vivo. EXPERIMENTAL DESIGN: In vitro experiments used the mouse melanocyte line melan-a. For in vivo experiments, mice transgenic for hepatocyte growth factor and survivin, shown previously to develop melanoma following a single neonatal dose of UV irradiation, were given NAC (7 mg/mL; mother's drinking water) transplacentally and through nursing until 2 weeks after birth. RESULTS: NAC (1-10 mmol/L) protected melan-a cells from several UV-induced oxidative sequelae, including production of intracellular peroxide, formation of the signature oxidative DNA lesion 8-oxoguanine, and depletion of free reduced thiols (primarily glutathione). Delivery of NAC reduced thiol depletion and blocked formation of 8-oxoguanine in mouse skin following neonatal UV treatment. Mean onset of UV-induced melanocytic tumors was significantly delayed in NAC-treated compared with control mice (21 versus 14 weeks; P = 0.0003). CONCLUSIONS: Our data highlight the potential importance of oxidative stress in the pathogenesis of melanoma and suggest that NAC may be useful as a chemopreventive agent.
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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 | 0.001 |
| 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".