Differential expression of ISG20 in chronic hepatitis B patients and relation to interferon‐alpha therapy response
Bibliographic record
Abstract
The 20 kDa exonuclease encoded by the interferon-stimulated gene, ISG20, can inhibit the replication of hepatitis B virus (HBV), and may represent a clinically useful prognostic marker for response to interferon-alpha (IFN-α) antiviral therapy. The present study was designed to investigate the differential expression patterns of ISG20 in liver biopsy samples from treatment-naive patients with chronic hepatitis B and non-HBV infected controls and to determine the relation between the differential expression and IFN-α treatment outcome (responders vs. non-responders). HBV infection status was determined by measuring levels of hepatitis B surface antigen (HBsAg) by chemoluminescence immunoassay and of HBV DNA by real-time quantitative (q)PCR. ISG20 protein and mRNA expressions were assessed by immunohistochemistry and qPCR, respectively. Chronic hepatitis B responders showed significantly higher levels of ISG20 protein and mRNA expressions than either the chronic hepatitis B non-responders or the controls. Moreover, increased expression of ISG20 in both the nucleus and cytoplasm was correlated with positive response to IFN-α treatment. Thus, active transcription and translation of ISG20 may represent a marker to identify chronic hepatitis B patients likely to respond to IFN-α therapy. Prognostic clinical strategies based upon this marker may include genomic screening methods and immunohistochemical staining of liver biopsies.
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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 | 0.001 |
| 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".