Pten Deficiency in Melanocytes Results in Resistance to Hair Graying and Susceptibility to Carcinogen-Induced Melanomagenesis
Bibliographic record
Abstract
Phosphate and tensin homologue deleted on chromosome 10 (PTEN) is a tumor suppressor gene inactivated in numerous sporadic cancers, including melanomas. To analyze Pten functions in melanocytes, we used the Cre-loxP system to delete Pten specifically in murine pigment-producing cells and generated DctCrePten(flox/flox) mice. Half of DctCrePten(flox/flox) mice died shortly after birth with enlargements of the cerebral cortex and hippocampus. Melanocytes were increased in the dermis of perinatal DctCrePten(flox/flox) mice. When the mutants were subjected to repeated depilations, melanocyte stem cells in the bulge of the hair follicle resisted exhaustion and the mice were protected against hair graying. Although spontaneous melanomas did not form in DctCrePten(flox/flox) mice, large nevi and melanomas developed after carcinogen exposure. DctCrePten(flox/flox) melanocytes were increased in size and exhibited heightened activation of Akt and extracellular signal-regulated kinases, increased expression of Bcl-2, and decreased expression of p27(Kip1). Our results show that Pten is important for the maintenance of melanocyte stem cells and the suppression of melanomagenesis.
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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 | 0.000 |
| 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".