Hepatitis C virus: The role of molecular mimicry in response to interferon treatment
Bibliographic record
Abstract
Chronic hepatitis C virus (HCV) infection is one of the major causes of chronic liver disease worldwide. In order for HCV to persist, the virus must escape immune recognition or inhibit the host immune response. The NS5A protein contains the interferon sensitivity-determining region (ISDR) and is able to repress dsRNA-dependent protein kinase (PKR) thus influencing the response to interferon (IFN) therapy. Patients who respond to IFN therapy have stronger antibody reactivity against the NS5A compared to IFN non-responders. Therefore, given the possible role for the ISDR in IFN resistance and differential antibody reactivity, it is possible that variation in ISDR may be involved in viral immune escape and development of persistent HCV infection employing aspects of host mimicry. In this study, pre-treatment samples obtained from HCV infected patients were used to investigate the effect of different NS5A ISDR variants on the IFN antiviral response and their involvement in immune evasion. The NS5A was identified as a homologue of the variable region of immunoglobulins (Ig). The IFN resistant genotypes had higher levels of similarity to Ig compared to IFN sensitive genotypes. Expression of NS5A-6003 (HCV genotype 1b) and NS5A-6074 (HCV genotype 2a) was able to rescue vesicular stomatitis virus (VSV) from IFN inhibition and restore luciferase activity. A correlation between Ig-like NS5A structure and also antibody response with the outcome of IFN treatment was observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".