Generation of a Mouse Expressing a Conditional Knockout of the Hepatocyte Growth Factor Gene: Demonstration of Impaired Liver Regeneration
Bibliographic record
Abstract
Hepatocyte growth/scatter factor (HGF/SF) is a pleiotropic cytokine originally identified as a potent mitogen for rat hepatocytes. Two HGF/SF knockout mouse models have been reported, both of which exhibit developmental abnormalities causing embryonic lethality. To circumvent this limitation, we created a mouse conditionally deficient in liver expression of HGF/SF to specifically investigate the role of this mitogen in the process of adult liver regeneration. Gene targeting technology was used to generate a mouse with loxP sites flanking exon 5 of the HGF/SF gene (ex5-flox). In the absence of cre recombinase activity, mice homozygous for ex5-flox were indistinguishable from wild-type littermates. To ablate HGF/SF gene expression in vitro, primary hepatocytes established from homozygous HGF(ex5-flox) mice were infected with a recombinant adenoviral vector coding for cre recombinase (AdCre1). PCR analyses of genomic DNA demonstrated greater than 90% ablation of the ex5-floxed gene sequence. In vivo, HGF(ex.5-flox) mice were administered AdCre1 vector and the ablation of the HGF gene confirmed by Southern blot analysis. To induce liver regeneration, mice were injected with the hepatotoxin carbon tetrachloride. The regenerative capacity of hepatocytes in mice administered cre recombinase was shown to be significantly reduced when compared with mice injected with an adenovirus expressing LacZ. A similar reduction in hepatocyte regeneration was observed in HGF(ex.5.flox) mice carrying the cre transgene under the control of the interferon-inducible (pI:pC) Mx1 promoter, as an alternative strategy to ablate the HGF/SF gene in liver. Our results confirm the mitogenic role of HGF/SF in liver regeneration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".