Insulin‐like growth factor binding protein‐1 over‐expression in transgenic mice inhibits hepatic preneoplasia
Bibliographic record
Abstract
Insulin-like growth factor binding protein-1 (IGFBP-1) is synthesized in the liver and regulates the mitogenic effects of the insulin-like growth factors (IGFs). The evidence that IGFBP-1 plays a role in hepatocarcinogenesis, however, is equivocal. We have, therefore, investigated the development of preneoplastic hepatic lesions in transgenic mice in which the human IGFBP-1 gene is under the control of the mouse metallothionein promoter. The lesions were induced by treating 15-d-old male mice with a single intraperitoneal injection of 5 mg/kg diethylnitrosamine (DENA). Lesions were scored when the mice were 28 wk of age. Quantitative microscopy of liver sections revealed that significantly fewer transgenic mice treated with zinc to activate the transgene had focal lesions compared to either transgenic mice not treated with zinc or wild-type mice treated with zinc (36.4% versus 85.7% and 83.3%, respectively, P < 0.05 in each case). Zinc-treated transgenic mice also had significantly fewer lesions per liver (11.5 +/- 5.0 versus 74.7 +/- 18.4 and 59.4 +/- 15.6, respectively, P < 0.01 in each case) and a smaller percentage of liver volume occupied by lesions (0.2 +/- 0.1 versus 1.4 +/- 0.3 and 1.1 +/- 0.4 respectively, P < 0.05 in each case). Immunohistochemical staining showed that both IGF-I and IGF-II were overexpressed in most of the lesions. These results show that expression of the IGFBP-1 transgene leads to a marked inhibition of hepatic preneoplasia, possibly by decreasing the mitogenic activity of IGF-I and/or IGF-II. This study adds new evidence to the notion that the IGF axis plays an important role in liver cancer development.
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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 | 0.000 | 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".