Circulating LPS and (1→3)-β-D-Glucan: A Folie à Deux Contributing to HIV-Associated Immune Activation
Bibliographic record
Abstract
Immune activation is the driving force behind the occurrence of AIDS and non-AIDS events, and is only partially reduced by antiretroviral therapy (ART). Soon after HIV infection, intestinal CD4+ T cells are depleted leading to epithelial gut damage and subsequent translocation of microbes and/or their products into systemic circulation. Bacteria and fungi are the two most abundant populations of the gut microbiome. Circulating lipopolysaccharide (LPS) and (1→3)-β-D-Glucan (βDG), major components of bacterial and fungal cell walls respectively, are measured as markers of microbial translocation in the context of compromised gut barriers. While LPS is a well-known inducer of innate immune activation, βDG is emerging as a significant source of monocyte and NK cell activation that contributes to immune dysfunction. Herein, we critically evaluated recent literature to untangle the respective roles of LPS and βDG in HIV-associated immune dysfunction. Furthermore, we appraised the relevance of LPS and βDG as biomarkers of disease progression and immune activation on ART. Understanding the consequences of elevated LPS and βDG on immune activation will provide insight into novel therapeutic strategies against the occurrence of AIDS and non-AIDS events.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".