Mechanisms for Macrophage-Mediated HIV-1 Induction
Bibliographic record
Abstract
Viral latency is a long-term pathogenic condition in patients infected with HIV-1. Low but sustained virus replication in chronically infected cells can be activated by stimulation with proinflammatory cytokines such as TNF-alpha, IL-1 beta, or other host factors. However, the precise mechanism by which cellular activation induces latently infected cells to produce virions has remained unclear. In the present report, we present evidence that activation of HIV-1 replication in latently infected U1 or ACH2 cells by human macrophages is mediated by a rapid nuclear localization of NF-kappaB p50/p65 dimer with concomitant increased expression of proinflammatory cytokines. Multiplexed RT-PCR amplification of mRNA isolated from cocultures of macrophages and U1 and ACH2 cells showed significant induction of IL-1beta, IL-6, IL-8, TNF-alpha, and TGF-beta expression within 3 h of coincubation. Fixation of macrophages, U-1, or ACH2 cells with paraformaldehyde before coculture completely abrogated the induction of NF-kappaB subunits and HIV-1 replication, suggesting that cooperative interaction between the two cell types is an essential process for cellular activation. Pretreatment of macrophage-U1 or macrophage-ACH2 cocultures with neutralizing anti-TNF-alpha Ab down-regulated the replication of HIV-1. In addition, pretreatment of macrophage-U1 or macrophage-ACH2 cocultures with the NF-kappaB inhibitor (E)3-[(4-methylphenyl)sulfonyl]-2-propenenitrile (BAY 11-7082) prevented the induction of cytokine expression, indicating a pivotal role of NF-kappaB-mediated signaling in the reactivation of HIV-1 in latently infected cells by macrophages. These results provide a mechanism by which macrophages induce HIV-1 replication in latently infected cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".