Accelerated CCl4-Induced Liver Fibrosis in Hjv-/- Mice, Associated with an Oxidative Burst and Precocious Profibrogenic Gene Expression
Bibliographic record
Abstract
Hereditary hemochromatosis is commonly associated with liver fibrosis. Likewise, hepatic iron overload secondary to chronic liver diseases aggravates liver injury. To uncover underlying molecular mechanisms, hemochromatotic hemojuvelin knockout (Hjv-/-) mice and wild type (wt) controls were intoxicated with CCl(4). Hjv-/- mice developed earlier (by 2-4 weeks) and more acute liver damage, reflected in dramatic levels of serum transaminases and ferritin and the development of severe coagulative necrosis and fibrosis. These responses were associated with an oxidative burst and early upregulation of mRNAs encoding α1-(I)-collagen, the profibrogenic cytokines TGF-β1, endothelin-1 and PDGF and, notably, the iron-regulatory hormone hepcidin. Hence, CCl4-induced liver fibrogenesis was exacerbated and progressed precociously in Hjv-/- animals. Even though livers of naïve Hjv-/- mice were devoid of apparent pathology, they exhibited oxidative stress and immunoreactivity towards α-SMA antibodies, a marker of hepatic stellate cells activation. Furthermore, they expressed significantly higher (2-3 fold vs. wt, p<0.05) levels of α1-(I)-collagen, TGF-β1, endothelin-1 and PDGF mRNAs, indicative of early fibrogenesis. Our data suggest that hepatic iron overload in parenchymal cells promotes oxidative stress and triggers premature profibrogenic gene expression, contributing to accelerated onset and precipitous progression of liver fibrogenesis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".