Nef and TNFα are Coplayers that Favor HIV-1 Replication in Monocytic Cells and Primary Macrophages
Bibliographic record
Abstract
The human immunodeficiency virus (HIV) Nef protein is myristoylated and plays a critical role in AIDS pathogenesis by enhancing viral replication, survival of the virus within infected cells and by facilitating its spread in vivo. We observed that, in the promonocytic cell line U937, myristoylated exogenous Nef protein activates NF-kappaB and AP-1, whereas unmyristoylated exogenous Nef protein does not. Using methyl-beta-cyclodextrin (MbetaC) treatment, we observed that the activation of NF-kappaB and AP-1 by exogenous Nef protein is mediated primarily via lipid rafts both in U937 cells and in primary human macrophages. In agreement with this observation, exogenous Nef protein colocalized with GM1 ganglioside, a major component of lipid rafts, in U937 cells as detected by confocal microscopy. Since tumor necrosis factor alpha (TNFalpha) activates NF-kappaB and AP-1, we investigated the role of exogenous Nef protein in TNFalpha-stimulated U937 cells and primary macrophages. We observed that exogenous Nef and TNFalpha synergistically activate NF-kappaB and AP-1 in U937 cells and primary macrophages resulting in enhanced stimulation of the HIV-1 long terminal repeat (LTR), and subsequently in enhanced viral replication in both chronically infected promonocytic U1 cells and acutely HIV-1-infected primary macrophages. Both enhanced LTR stimulation and viral replication following treatment with exogenous Nef and TNFalpha were mediated via lipid rafts. Therefore, our results indicate that exogenous Nef protein and enhanced TNFalpha production detected in HIV-infected subjects could synergize to fuel the progression of the disease via lipid raft-dependent stimulation of the HIV-1 provirus present in such cellular reservoirs as mononuclear phagocytes.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".