Hepatitis C virus load and expression of a unique subset of cellular genes in circulating lymphoid cells differentiate non‐responders from responders to pegylated interferon alpha–ribavirin treatment
Bibliographic record
Abstract
Based on investigations of liver biopsy material, certain cellular genes have been implicated as correlates of success or failure to interferon alpha-ribavirin (IFN/RBV) therapy against hepatitis C. The current study aimed at determining whether expression of host genes thought to be relevant to HCV replication in the liver would be correlated with HCV infection status in peripheral blood mononuclear cells (PBMCs) and also with patient responsiveness to IFN/RBV treatment. Therefore, PBMCs from patients with chronic hepatitis C responding (n = 35) or not (n = 49) to IFN/RBV and from healthy controls (n = 15) were evaluated for HCV RNA load and cellular gene expression. Non-responders had 3- to 10-fold higher basal levels of interleukin (IL)-8, IFN-stimulated gene 15 (ISG15), 2',5'-oligoadenylate synthetase (OAS), and Toll-like receptors (TLR)-4, -5, and -7 compared to responders. Non-responders with similar post-treatment follow-ups as responders persistently expressed 6- to 20-fold greater levels of IL-8, ISG15, and OAS after therapy. Higher expression of IFN-α, IFN-γ, and IFN-λ was found in PBMCs of individuals achieving sustained virological response, either before or after therapy. Pre-treatment HCV RNA loads in PBMCs of non-responders were significantly higher (P = 0.016) than those of responders. In conclusion, the data indicate that immune cells of responders and non-responders to IFN/RBV therapy exhibited significantly different virological and host gene expression profiles. Elevated baseline HCV loads and TLR-4, -5, and -7 levels, and persistently high levels of IL-8, ISG15, and OAS were correlated with IFN non-responsiveness. The results warrant further investigations on the utilization of PBMCs for predicting success or failure to IFN-based therapies.
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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 | 0.001 | 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) | 0.002 | 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".