Toll-like receptor expression and responsiveness are increased in viraemic HIV-1 infection
Bibliographic record
Abstract
OBJECTIVES: Toll-like receptors (TLR) are important in pathogen recognition and may play a role in HIV disease. We evaluated the effect of chronic untreated and treated HIV-1 infection on systemic TLR expression and TLR signalling. METHODS: Two hundred HIV-infected and uninfected women from a Kenya cohort participated in the studies. TLR1 to TLR10 messenger RNA expression was determined by quantitative reverse transcriptase polymerase chain reaction in peripheral blood mononuclear cells (PBMC). TLR ligand responsiveness was determined in or using ex-vivo PBMC by cytokine production in culture supernatants. RESULTS: Chronic, untreated HIV-1 infection was significantly associated with increased mRNA expression of TLR6, TLR7, and TLR8 and when analysis was limited to those with advanced disease (CD4 cell count < 200 cells/ml) TLR2, TLR3, and TLR4 were additionally elevated. TLR expression correlated with the plasma HIV-RNA load, which was significant for TLR6 and TLR7. In vitro HIV single-stranded RNA alone could enhance TLR mRNA expression. PBMC of HIV-infected subjects also demonstrated profoundly increased proinflammatory responsiveness to TLR ligands, suggesting sensitization of TLR signalling in HIV. Finally, viral suppression by HAART was associated with a normalization of TLR levels. CONCLUSION: Together, these data indicate that chronic viraemic HIV-1 is associated with increased TLR expression and responsiveness, which may perpetuate innate immune dysfunction and activation that underlies HIV pathogenesis, and thus reveal potential new targets for therapy.
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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 | 0.001 |
| 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) | 0.003 | 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".