Polygenic control of hepatocarcinogenesis in Copenhagen × F344 rats
Bibliographic record
Abstract
Cop and CFF1 rats exhibit resistance to hepatocarcinogenesis, associated with high rates of remodeling of neoplastic lesions. We have mapped hepatocarcinogenesis susceptibility, resistance and remodeling loci affecting the number, volume and volume fraction of neoplastic nodules induced by the "resistant hepatocyte" model in male CFF2 rats. Three loci in significant linkage with the number or volume of nonremodeling lesions were identified on chromosomes 1, 4 and 18. Suggestive linkage with number or volume fraction of total, nonremodeling or remodeling lesions was found for 7 loci on chromosomes 1, 2, 13, 14 and 15. All of these loci showed significant allele-specific effects on the phenotypic traits. We also detected by analysis of variance 19 2-way interactions inducing phenotypic effects not predictable on the basis of the sum of separate effects. These novel epistatic loci were in significant linkage with the number and/or volume of total, nonremodeling or remodeling nodules. These data indicate that susceptibility to hepatocarcinogenesis in Cop rats is controlled by a complex array of genes with several gene-gene interactions and that different genetic mechanisms control remodeling and nonremodeling liver nodules. Frequent deregulation in human liver cancer of genes positioned in chromosomal segments syntenic to rat susceptibility/resistance loci suggests some similarities between the genetic mechanisms involved in hepatocarcinogenesis in rats and humans.
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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 | 0.000 | 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".