Reduction of CCR5 with low-dose rapamycin enhances the antiviral activity of vicriviroc against both sensitive and drug-resistant HIV-1
Bibliographic record
Abstract
Vicriviroc (VCV) is a chemokine (C-C motif) receptor 5 (CCR5) antagonist with potent anti-HIV activity that currently is being evaluated in phase III clinical trials. In the present study, donor CCR5 density (CCR5 receptors/CD4 lymphocytes) inversely correlated with VCV antiviral activity (Spearman's correlation test; r = 0.746, P = 0.0034). Low doses of the transplant drug rapamycin (RAPA) reduced CCR5 density and enhanced VCV antiviral activity. In drug interaction studies, the RAPA/VCV combination had considerable antiviral synergy (combination indexes of 0.1-0.04) in both multicycle and single-cycle infection of lymphocytes. The synergy between RAPA and VCV translated into dose reduction indexes of 8- to 41-fold reductions for RAPA and 19- to 658-fold reductions for VCV. RAPA enhanced VCV antiviral activity against both B and non-B clade isolates, potently suppressing clade G viruses with reported reduced sensitivities to VCV and to the licensed CCR5 antagonist maraviroc. Importantly, RAPA reduction of CCR5 density in lymphocytes sensitized VCV-resistant strains to VCV, inhibiting virus production by approximately 90%. We further demonstrated the role of CCR5 density on VCV activity against resistant virus in donor lymphocytes and in cell lines expressing varying CCR5 densities. Together, these results suggest that low doses of RAPA may increase the durability of VCV-containing regimens in patients by enhancing VCV viral suppression, by allowing the use of lower doses of VCV with reduced potential for toxicity, and by controlling emerging VCV-resistant variants.
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 | 0.000 |
| 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".