HIV protease inhibitors disrupt astrocytic glutamate transporter function and neurobehavioral performance
Bibliographic record
Abstract
OBJECTIVE: The neurotoxic actions of the HIV protease inhibitors, amprenavir (APV) and lopinavir (LPV) were investigated. DESIGN: With combination antiretroviral therapy (cART), HIV-infected persons exhibit neurocognitive impairments, raising the possibility that cART might exert adverse central nervous system (CNS) effects. We examined the effects of LPV and APV using in-vitro and in-vivo assays of CNS function. METHODS: Gene expression, cell viability and amino-acid levels were measured in human astrocytes, following exposure to APV or LPV. Neurobehavioral performance, amino-acid levels and neuropathology were examined in HIV-1 Vpr transgenic mice after treatment with APV or LPV. RESULTS: Excitatory amino-acid transporter-2 (EAAT2) expression was reduced in astrocytes treated with LPV or APV, especially LPV (P < 0.05), which was accompanied by reduced intracellular L-glutamate levels in LPV-treated cells (P < 0.05). Treatment of astrocytes with APV or LPV reduced the expression of proliferating cell nuclear antigen (PCNA) and Ki-67 (P < 0.05) although cell survival was unaffected. Exposure of LPV to astrocytes augmented glutamate-evoked transient rises in [Cai] (P < 0.05). Vpr mice treated with LPV showed lower concentrations of L-glutamate, L-aspartate and L-serine in cortex compared with vehicle-treated mice (P < 0.05). Total errors in T-maze assessment were increased in LPV and APV-treated animals (P < 0.05). EAAT2 expression was reduced in the brains of protease inhibitor-treated animals, which was associated with gliosis (P < 0.05). CONCLUSION: These results indicated that contemporary protease inhibitors disrupt astrocyte functions at therapeutic concentrations with enhanced sensitivity to glutamate, which can lead to neurobehavioral impairments. ART neurotoxicity should be considered in future therapeutic regimens for 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 | 0.000 | 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) | 0.001 | 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".