Targeted delivery of ribavirin improves outcome of murine viral fulminant hepatitis via enhanced anti-viral activity
Bibliographic record
Abstract
Side effects of interferon-ribavirin combination therapy limit the sustained viral response achievable in hepatitis C virus (HCV) patients. Coupling ribavirin to macromolecular carriers that target the drug to the liver would reduce systemic complications. The aim of this study was to evaluate the efficacy of a hemoglobin-ribavirin conjugate (HRC 203) in murine hepatitis virus strain 3 (MHV-3) induced viral hepatitis. HRC 203 had greater anti-viral activity on both isolated hepatocytes and macrophages, whereas both ribavirin and HRC 203 inhibited production of the pro-inflammatory cytokines interferon gamma (IFN-gamma) and tumor necrosis factor alpha (TNF-alpha) by macrophages. In vivo, untreated MHV-3-infected mice all developed clinical and biochemical signs of acute viral hepatitis and died by day 4 post infection. Livers recovered from untreated infected mice showed greater than 90% necrosis. In contrast, survival was enhanced in both ribavirin- and HRC 203-treated mice with a marked reduction in biochemical [ALT(max) 964 +/- 128 IU/L (ribavirin); 848 +/- 212 IU/L (HRC 203)] and histological evidence of hepatic necrosis (<10% in ribavirin/HRC 203 vs. 90% in untreated controls). Clinically, HRC 203-treated mice behaved normally, in contrast to ribavirin-treated mice, which developed lethargy and abnormal fur texture. In conclusion, targeted delivery of ribavirin to the liver alters the course of MHV-3 infection as demonstrated by prolonged survival, improved behavior, and reduced signs of histologically evident disease, as well as inhibition of viral replication and production of inflammatory cytokines in vitro.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".