Concurrent administration of IFNα14 and cART in TKO-BLT mice enhances suppression of HIV-1 viremia but does not eliminate the latent reservoir
Bibliographic record
Abstract
Abstract Combination antiretroviral therapy (cART) prevents HIV-1 replication but does not eliminate the latent reservoir and cure the infection. Type I interferons (IFN) mediate antiviral effects through different mechanisms than cART. We previously showed that IFNα14 is the most potent IFNα subtype against HIV-1 and that it can significantly reduce the HIV-1 proviral reservoir. This study sought to determine whether combining cART with IFNα14 therapy would produce greater reductions in HIV-1 viral and proviral loads than ART alone. Immunodeficient Rag2−/−γc−/−CD47−/− C57BL/6 mice were humanized by the BLT method, infected with HIV-1JR-CSF and the in vivo efficacy of cART was compared with combined cART/IFNα14 therapy. Infection was allowed to establish for 6 weeks prior to 4 weeks of treatment with oral cART either with or without IFNα14. Plasma viral RNA and splenic CD4+ T cell viral DNA levels were measured immediately after treatment and after 2 weeks of therapy interruption. Augmentation of cART with IFNα14 resulted in significantly enhanced suppression of HIV-1 plasma viremia. However, no significant reduction in total viral DNA was detectable. Furthermore, virus rebounded after treatment interruption to similar levels in both groups. Thus, augmentation of cART with IFNα14 resulted in a more pronounced reduction of HIV viremia levels over cART alone, but the effect was not potent enough to be detected at the viral DNA level or to prevent virus rebound following therapy interruption in immune system-humanized mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".