Immunologic Change over 72 Weeks Following Raltegravir- Versus Efavirenz-Based Therapy in HIV/HCV-Coinfected Individuals in Vietnam
Bibliographic record
Abstract
The impact of HIV antiretroviral therapy (ART) on immune dysregulation associated with hepatitis C virus (HCV)/HIV coinfection is incompletely understood. We serially assessed monocyte activation (neopterin, sCD14, and sCD163) and T cell activation (HLA-DR, CD38) and immune exhaustion [program cell death protein 1 (PD1), TIGIT] in HIV/HCV-coinfected individuals who participated in a randomized trial performed in Vietnam designed to assess the hepatotoxicity of raltegravir (RAL)- versus efavirenz (EFV)-based therapy when used as first-time ART in combination with tenofovir disoproxil fumarate and emtricitabine. Baseline pre-ART values were compared with those from ART-naive HIV-monoinfected and HIV-seronegative individuals. Before ART, HIV/HCV-coinfected individuals had higher levels of neopterin, sCD14, and sCD163, and increased frequencies of CD38 + HLA-DR + , PD1 + , and TIGIT + CD4 and CD8 T cells compared with ART-naive HIV-monoinfected or HIV-seronegative individuals (all p < .01). Most parameters did not normalize despite 72 weeks of ART. In particular sCD163 persisted at high levels. Improvement over 72 weeks in fibrosis as assessed by FibroScan ® correlated with reductions in plasma sCD163 and in the frequencies of T cell activation, single PD1 + , TIGIT + , and dual PD1 + TIGIT + CD8 T cells. A nonsignificant tendency toward more favorable effects on monocyte and T cell immune activation and on T cell exhaustion were seen with RAL-compared with EFV-based therapy. The initiation of ART in HIV/HCV-coinfected individuals is associated with incomplete improvement in monocyte and T cell immune activation and exhaustion, which was associated with some corresponding improvement in liver fibrosis.
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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 | 0.000 | 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".