Targeted production of proprotein convertase PC1 enhances mammary development and tumorigenesis in transgenic miceThis article is one of a selection of papers published in a special issue celebrating the 125th anniversary of the Faculty of Medicine at the University of Manitoba.
Bibliographic record
Abstract
Elevated production of proprotein convertases (PCs), proteolytic enzymes that posttranslationally modify the biological activities of diverse groups of cellular proteins, is a common occurrence in human breast carcinomas. A transgenic mouse model was developed to gain insight into the significance of PC production in breast development and neoplasia. Mammary epithelium-specific and early expression of PC1 was targeted by the use of the mouse mammary tumor virus promoter/enhancer. Whole-mount examinations revealed that the mammary glands of 83-day-old virgin PC1 transgenic mice exhibited an accelerated lobuloalveolar development compared with that of age-matched wild-type mice (p < 0.001). This phenotypic change was accompanied by extensive alterations in gene expression assessed by gene expression microarray analyses. Pathway analysis of PC1-induced alterations in gene expression has revealed possible mechanism of action of PC1 in the mammary gland. PC1 expression alone, however, did not promote spontaneous mammary tumorigenesis in the transgenic mice. PC1 transgene expression resulted in a significantly higher incidence (p = 0.008) and accelerated growth (p = 0.023) of 7,12-dimethylbenz[a]anthracene (DMBA)-induced mammary adenocarcinomas. The present study therefore shows that PC1 expression can promote normal and neoplastic mammary development and growth and suggests that proprotein convertases may be important etiological factors in human breast neoplasia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".