HIV-1 Transcription and Virus Production Are Both Accentuated by the Proinflammatory Myeloid-Related Proteins in Human CD4+ T Lymphocytes
Bibliographic record
Abstract
S100A8, S100A9, and S100A12, collectively known as myeloid-related proteins (MRPs), are highly expressed by the myeloid cell lineage and are found in the extracellular milieu during infections and inflammatory conditions. Recent data showed high levels of MRPs in the serum of HIV type 1 (HIV-1)-infected patients which correlated with disease progression and low CD4(+) counts. Therefore, we set out to investigate the effect of MRPs on HIV-1 replication. We observed a 4- to 5-fold induction of virus production in J1.1, a human T lymphoid cell line latently infected with HIV-1, following treatment with MRPs. Using luciferase-based reporter gene assays, we demonstrated that MRPs induce a dose- and time-dependent activation of the HIV-1 long terminal repeat promoter region that could be blocked by specific anti-MRP polyclonal Abs and by physical denaturation of these proteins. The MRP-mediated induction was acting through the HIV-1 enhancer sequence and was dependent upon NF-kappaB activity. These latter results were also confirmed by EMSA experiments conducted in Jurkat cells and freshly isolated PBMCs. In conclusion, we demonstrate that MRPs induce HIV-1 transcriptional activity and viral replication in infected CD4(+) T-lymphocytes at concentrations similar to those found in the serum of HIV-1-infected patients.
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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 | 0.001 |
| 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".