Plasma Extracellular Vesicles Enhance HIV-1 Infection of Activated CD4+ T Cells and Promote the Activation of Latently Infected J-Lat10.6 Cells via miR-139-5p Transfer
Bibliographic record
Abstract
HIV latency is a challenge to the success of antiretroviral therapy (ART). Hence patients may benefit from interventions that efficiently reactivate the latent virus to be eliminated by ARTs. Here we show that plasma extracellular vesicles (pEVs) can enhance HIV infection of activated CD4 + T cells and reactivate the virus in latently infected J-Lat 10.6 cells. Evaluation of the extravesicular miRNA cargo by a PCR array revealed that pEVs from HIV patients express miR-139-5p. Furthermore, we found that increased levels of miR-139-5p in J-Lat 10.6 cells incubated with pEVs corresponded with reduced expression of the transcription factor, FOXO1. pEV treatment also corresponded with increased miR-139-5p expression in stimulated PD1+ Jurkat cells, but with concomitant upregulation of FOXO1, Fos, Jun, PD-1 and PD-L1. However, J-Lat 10.6 cells incubated with miR-139-5p inhibitor-transfected pEVs from HIV ART-naïve and on-ART patients expressed reduced levels of miR-139-5p than cells treated with pEVs from healthy controls (HC). Collectively, our results indicate that pEV miR-139-5p belongs to a network of miRNAs that can promote cell activation, including latent HIV-infected cells by regulating the expression of FOXO1 and the PD1/PD-L1 promoters, Fos and Jun.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".