Rapid inflammasome activation in microglia contributes to brain disease in HIV/AIDS
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus type 1(HIV-1) infects and activates innate immune cells in the brain resulting in inflammation and neuronal death with accompanying neurological deficits. Induction of inflammasomes causes cleavage and release of IL-1β and IL-18, representing pathogenic processes that underlie inflammatory diseases although their contribution HIV-associated brain disease is unknown. RESULTS: Investigation of inflammasome-associated genes revealed that IL-1β, IL-18 and caspase-1 were induced in brains of HIV-infected persons and detected in brain microglial cells. HIV-1 infection induced pro-IL-1β in human microglia at 4 hr post-infection with peak IL-1β release at 24 hr, which was accompanied by intracellular ASC translocation and caspase-1 activation. HIV-dependent release of IL-1β from a human macrophage cell line, THP-1, was inhibited by NLRP3 deficiency and high extracellular [K+]. Exposure of microglia to HIV-1 gp120 caused IL-1β production and similarly, HIV-1 envelope pseudotyped viral particles induced IL-1β release, unlike VSV-G pseudotyped particles. Infection of cultured feline macrophages by the related lentivirus, feline immunodeficiency virus (FIV), also resulted in the prompt induction of IL-1β. In vivo FIV infection activated multiple inflammasome-associated genes in microglia, which was accompanied by neuronal loss in cerebral cortex and neurological deficits. Multivariate analyses of data from FIV-infected and uninfected animals disclosed that IL-1β, NLRP3 and caspase-1 expression in cerebral cortex represented key molecular determinants of neurological deficits. CONCLUSIONS: NLRP3 inflammasome activation was an early and integral aspect of lentivirus infection of microglia, which was associated with lentivirus-induced brain disease. Inflammasome activation in the brain might represent a potential target for therapeutic interventions in HIV/AIDS.
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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 | 0.001 | 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 | 0.000 |
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".