Transgenic Mouse Models—A Seminal Breakthrough in Oncogene Research
Bibliographic record
Abstract
Transgenic mouse models are an integral part of modern cancer research, providing a versatile and powerful means of studying tumor initiation and progression, metastasis, and therapy. The present repertoire of these models is very diverse, with a wide range of strategies used to induce tumorigenesis by expressing dominant-acting oncogenes or disrupting the function of tumor-suppressor genes, often in a highly tissue-specific manner. Much of the current technology used in the creation and characterization of transgenic mouse models of cancer will be discussed in depth elsewhere. However, to gain a complete appreciation and understanding of these complex models, it is important to review the history of the field. Transgenic mouse models of cancer evolved as a new and, compared with the early cell-culture-based techniques, more physiologically relevant approach for studying the properties and transforming capacities of oncogenes. Here, we will describe early transgenic mouse models of cancer based on tissue-specific expression of oncogenes and discuss their impact on the development of this still rapidly growing field.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".