A164 RAPID INTRAHEPATIC AND PERIPHERAL BLOOD HCV RNA DECLINE AND HCV-SPECIFIC IMMUNE RESPONSE INCREASE DURING IFN-FREE DAA THERAPY IN HCV TREATMENT-NAÏVE PATIENTS
Bibliographic record
Abstract
Interferon (IFN)-free HCV direct-acting antiviral (DAA) treatment regimens lead to rapid HCV RNA decline and high rates of sustained virologic response (SVR). This study examined the impact of IFN-free DAA treatment on HCV-specific T cell responses and immunophenotypic effects in peripheral blood and in the liver of patients. Nine treatment-naïve patients with HCV genotype 1 and fibrosis stage 0–2 (defined by FibroSure ≤0.48 and APRI score ≤1) were treated for 6 weeks with sofosbuvir (nucleotide polymerase inhibitor), simeprevir (NS3/4A protease inhibitor) and daclatasvir (NS5A inhibitor). Peripheral blood mononuclear cells (PBMC) and fine needle aspiration liver biopsies (FNAB) were collected at baseline, day 2, week 1, end of treatment (EOT) and post-treatment follow-up week 24. HCV RNA was quantitatively measured at all time points in plasma using the Roche Cobas Taqman HCV assay v2.0 (lower limit of quantification [LLOQ]=15 IU/mL) and in blood and liver samples using the Abbott RealTime HCV assay (LLOQ=12 IU/mL). HCV-specific immune responses were evaluated by Enzyme-Linked ImmunoSpot (ELISPOT) assay with pools of overlapping peptides spanning the HCV genome. Cell quantities available from FNAB samples for assessment of HCV-specific T cell responses were low. PBMC and intrahepatic T cell phenotype and exhaustion were evaluated by flow cytometry with markers for CD3, CD4, CD8, CD127, Tim-3 and PD-1. Plasma HCV RNA rapidly declined and was <15 IU/mL undetectable in all 9 patients at EOT. All 9 patients achieved SVR12 and SVR24. HCV RNA also declined in liver tissue but was still detected in all 9 patients at EOT (low-level detectable in all 9 patients,
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".