Restoration of HCV-Specific Immune Responses with Antiviral Therapy: A Case for DAA Treatment in Acute HCV Infection
Bibliographic record
Abstract
Worldwide, 71 million individuals are chronically infected with Hepatitis C Virus (HCV). Chronic HCV infection can lead to potentially fatal outcomes including liver cirrhosis and hepatocellular carcinoma. HCV-specific immune responses play a major role in viral control and may explain why approximately 20% of infections are spontaneously cleared before the establishment of chronicity. Chronic infection, associated with prolonged antigen exposure, leads to immune exhaustion of HCV-specific T cells. These exhausted T cells are unable to control the viral infection. Before the introduction of direct acting antivirals (DAAs), interferon (IFN)-based therapies demonstrated successful clearance of viral infection in approximately 50% of treated patients. New effective and well-tolerated DAAs lead to a sustained virological response (SVR) in more than 95% of patients regardless of viral genotype. Researchers have investigated whether treatment, and the subsequent elimination of HCV antigen, can reverse this HCV-induced exhausted phenotype. Here we review literature exploring the restoration of HCV-specific immune responses following antiviral therapy, both IFN and DAA-based regimens. IFN treatment during acute HCV infection results in greater immune restoration than IFN treatment of chronically infected patients. Immune restoration data following DAA treatment in chronically HCV infected patients shows varied results but suggests that DAA treatment may lead to partial restoration that could be improved with earlier administration. Future research should investigate immune restoration following DAA therapies administered during acute 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".