Mitogen‐regulated protein/proliferin mRNA induction following single applications of tumor promoters to murine skin
Bibliographic record
Abstract
Mitogen-regulated protein/proliferin (mrp/plf) gene family transcripts rise in abundance as a response to diverse chemical and physical agents that promote morphological transformation in the murine C3H/10T1/2 cultured cell model of multi-step carcinogenesis. To determine if proliferin genes respond to tumor promoters in vivo, RNA was extracted from the whole skin of SENCAR mice after single applications of 2 or 20 microg 12-O-tetradecanoylphorbol-13-acetate (TPA); 3.2 or 32 nmole), 20 or 40 mg benzoyl peroxide (BPO; 83, 165 micromole), or acetone vehicle alone (2.72 mmole). RNA samples were prepared from treated skin areas, 2-48 h after painting. Mrp/plf-mRNA was not detected in Northern blot hybridizations, but large increases in mRNAs for ornithine decarboxylase gene and mRNA (odc), v-jun oncogene-related transcription factor gene and mRNA (junB), egr1 (early growth response protein gene and mRNA) were measured relative to beta 2 microglobulin gene and mRNA (b2m) mRNA in response to TPA. BPO induced small relative changes in these mRNAs. Reverse transcriptase (RT)-polymerase chain reactions (PCR) detected fully-processed MRP/plf-mRNA 16-48 h after TPA treatments in five of six animals, and in three of six BPO-treated animals. The MRP/plf-mRNA species expressed in the skin were predominantly plf1 and mrp3 as determined by gene-specific restriction enzyme sites within the RT-PCR products. Expression was either undetectable or found at low levels in acetone-painted controls and was not detected during the anagen phase of the normal hair growth cycle in unpainted animals. These results demonstrate that mrp/plf-mRNA is differentially expressed in murine skin in response to mechanistically distinct tumor promoters and has potential utility as a short-term biomarker for tumor promoting effects in chemical carcinogenesis.
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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) | 0.002 | 0.001 |
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".