The effect of <i>c‐myc</i> on stem cell fate influences skin tumor phenotype
Bibliographic record
Abstract
Nonmelanoma skin cancers (NMSCs) consist of a variety of tumor types including basal cell carcinoma, squamous cell carcinoma, a variety of hair follicle tumors, and sebaceous gland tumors. Genetic alterations that alter the fate of multipotent stem cells are believed to influence NMSC phenotype. We previously generated a transgenic mouse line which constitutively expressed c-myc under the control of the K14 promoter (K14.MYC2). These mice exhibited an increase in size and number of sebaceous glands, suggesting that c-myc diverted multipotential stem cells to a sebaceous lineage. Our goal in the current study was to determine if alterations in the commitment of multipotent stem cells to different cell fates would influence tumor phenotype. To this end, we exposed K14.MYC2 mice to a chemical carcinogenesis protocol and discovered that these mice were predisposed to develop sebaceous adenomas. Our data demonstrate that genetic alterations that alter the fate of multipotent stem cells during embryonic development can markedly influence the phenotype of NMSC that develop following exposure to carcinogens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".