Transfer of Intracellular HIV Nef to Endothelium Causes Endothelial Dysfunction
Bibliographic record
Abstract
With effective antiretroviral therapy (ART), cardiovascular diseases (CVD) are emerging as a major cause of morbidity and death in the aging HIV-infected population. To address whether HIV-Nef, a viral protein produced in infected cells even when virus production is halted by ART, can lead to endothelial activation and dysfunction, we tested Nef protein transfer to and activity in endothelial cells. We demonstrated that Nef is essential for major endothelial cell activating effects of HIV-infected Jurkat cells when in direct contact with the endothelium. In addition, we found that Nef protein in endothelial cells is sufficient to cause apoptosis, ROS generation and release of monocyte attractant protein-1 (MCP-1). The Nef protein-dependent endothelial activating effects can be best explained by our observation that Nef protein rapidly transfers from either HIV-infected or Nef-transfected Jurkat cells to endothelial cells between these two cell types. These results are of in vivo relevance as we demonstrated that Nef protein induces GFP transfer from T cells to endothelium in CD4.Nef.GFP transgenic mice and Nef is present in chimeric SIV-infected macaques. Analyzing the signal transduction effects of Nef in endothelial cells, we found that Nef-induced apoptosis is mediated through ROS-dependent mechanisms, while MCP-1 production is NF-kB dependent. Together, these data indicate that inhibition of Nef-associated pathways may be promising new therapeutic targets for reducing the risk for cardiovascular disease in the HIV-infected population.
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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 | 0.001 | 0.001 |
| 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".