Interferon-Alpha-Induced Changes in Metallothionein Expression in Liver Biopsies from Patients with Chronic Hepatitis C
Bibliographic record
Abstract
An association between reactive oxygen species and liver damage has been postulated in the course of hepatitis C virus (HCV) infection. Metallothionein (MT), induced by HCV core protein and interferon (IFN), plays a role in scavenging free radicals. MT expression in liver biopsies obtained from 21 patients with chronic HCV infection before and after IFN-alpha therapy was investigated. Changes in Knodell histological activity index (HAI) scores, MT protein levels (immunohistochemistry), MT-I and MT-II messenger (m)RNA expression levels (in situ hybridization) and proliferating cell nuclear antigen (PCNA) labelling index were determined and compared in serial liver specimens. MT staining was clustered around the portal tracts with inflammatory cells and fibrosis. The pattern of MT protein before IFN-alpha therapy was similar in all patients, but was higher in IFN-sustained responders than in nonresponders after IFN-alpha therapy. HAI scores and PCNA labelling indexes were significantly reduced after IFN-alpha therapy. MT-II mRNA expression correlated positively with PCNA index before therapy and with HAI scores after therapy (P<0.05). No correlation was found between MT-I mRNA and HAI scores or PCNA index. The findings indicate that IFN-alpha-induced hepatic MT may participate in the therapeutic effects of IFN-alpha for HCV. In addition, MT-II mRNA expression may be involved in cell proliferation in the livers of patients with chronic HCV infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".