Reduced antiretroviral drug efficacy and concentration in HIV-infected microglia contributes to viral persistence in brain
Bibliographic record
Abstract
BACKGROUND: In patients with HIV/AIDS receiving antiretroviral therapy (ART), HIV-1 persistence in brain tissue is a vital and unanswered question. HIV-1 infects and replicates in resident microglia and trafficking macrophages within the brain although the impact of individual ART drugs on viral infection within these brain myeloid cells is unknown. Herein, the effects of contemporary ART drugs were investigated using in vitro and in vivo models of HIV-1 brain infection. RESULTS: values for specific ART drugs in HIV-infected human microglia were significantly higher compared to bone marrow-derived macrophages and peripheral blood mononuclear cells. Intracellular ART drug concentrations in microglia were significantly lower than in human lymphocytes. In vivo brain concentrations of ART drugs in mice were 10 to 100-fold less in brain tissues compared with plasma and liver levels. In brain tissues from untreated HIV-infected BLT mice, HIV-encoded RNA, DNA and p24 were present in human leukocytes while ART eradicated viral RNA and DNA in both brain and plasma. Interruption of ART resulted in detectable viral RNA and DNA and increased human CD68 expression in brains of HIV-infected BLT mice. In aviremic HIV/AIDS patients receiving effective ART, brain tissues that were collected within hours of last ART dosing showed HIV-encoded RNA and DNA with associated neuroinflammatory responses. CONCLUSIONS: ART drugs show variable concentrations and efficacies in brain myeloid cells and tissues in drug-specific manner. Despite low drug concentrations in brain, experimental ART suppressed HIV-1 infection in brain although HIV/AIDS patients receiving effective ART had detectable HIV-1 in brain. These findings suggest that viral suppression in brain is feasible but new approaches to enhancing ART efficacy and concentrations in brain are required for sustained HIV-1 eradication from brain.
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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 | 0.001 | 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".