Simian Immunodeficiency Virus-Induced Alterations in Monocyte Production of Tumor Necrosis Factor Alpha Contribute to Reduced Immune Activation in Sooty Mangabeys
Bibliographic record
Abstract
Human immunodeficiency virus type 1 (HIV-1) infection is characterized by persistent viral replication in the context of CD4(+) T cell depletion and elevated immune activation associated with disease progression. In contrast, simian immunodeficiency virus (SIV) infection of African-origin sooty mangabeys (SM) generally does not result in simian AIDS despite high viral loads and therefore affords a unique model in which to study the immunologic contributions to a nonpathogenic lentiviral disease outcome. A key feature of these natural SIV infections is the maintenance of low levels of immune activation during chronic infection. Our goal was to delineate the contribution of monocytes to maintaining low levels of immune activation in SIV-infected SM. Utilizing an ex vivo whole-blood assay, proinflammatory cytokine production was quantified in monocytes in response to multiple Toll-like receptor (TLR) ligands and a specific, significant reduction in the tumor necrosis factor alpha (TNF-α) response to lipopolysaccharide (LPS) was observed in SIV-infected SM. In contrast, monocytes from hosts of pathogenic infections (HIV-infected humans and SIV-infected Asian macaques) maintained a robust TNF-α response. In SIV-infected SM, monocyte TNF-α responses to low levels of LPS could be augmented by the presence of plasma from uninfected control animals. The impact of LPS-induced TNF-α production on immune activation was demonstrated in vitro, as TNF-α blocking antibodies inhibited downstream CD8(+) T cell activation in a dose-dependent manner. These data demonstrate an association between nonpathogenic SIV infection of SM and a reduced monocyte TNF-α response to LPS, and they identify a role for monocytes in contributing to the suppressed chronic immune activation observed in these natural hosts.
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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) | 0.000 | 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 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".