Contrasting effect of the latency-reversing agents bryostatin-1 and JQ1 on astrocyte-mediated neuroinflammation and brain neutrophil invasion
Bibliographic record
Abstract
BACKGROUND: Despite effectiveness of the combined antiretroviral therapy, HIV-1 persists in long-lived latently infected cells. Consequently, new therapeutic approaches aimed at eliminating this latent reservoir are currently being developed. A "shock and kill" strategy using latency-reversing agents (LRA) to reactivate HIV-1 has been proposed. However, the impact of LRA on the central nervous system (CNS) remains elusive. METHODS: We used human fetal astrocytes and investigated the effects of several LRA on their functional and secretory activities. Astrocytes were infected with VSV-G-pseudotyped HIV-1 before treatment with various blood-brain barrier (BBB)-permeable LRA at subcytotoxic doses, which allow HIV-1 reactivation based on previous in vitro and clinical studies. Cells and supernatants were then used to evaluate effects of infection and LRA on (i) viability and metabolic activity of astrocytes using a colorimetric MTS assay; (ii) chemokines and proinflammatory cytokines secretion and gene expression by astrocytes using ELISA and RT-qPCR, respectively; (iii) expression of complement component 3 (C3), a proxy for astrogliosis, by RT-qPCR; (iv) glutamate uptake capacity by a fluorometric assay; and (v) modulation of neutrophil transmigration across an in vitro BBB model. RESULTS: We demonstrate that bryostatin-1 induces secretion of chemokines CCL2 and IL-8 and proinflammatory cytokines IL-6 and GM-CSF, whereas their production is repressed by JQ1. Bryostatin-1 also increases expression of complement component 3 and perturbs astrocyte glutamate homeostasis. Lastly, bryostatin-1 enhances transmigration of neutrophils across an in vitro blood-brain barrier model and induces formation of neutrophil extracellular traps. CONCLUSIONS: These observations highlight the need to carefully assess the potential harmful effect to the CNS when selecting LRA for HIV-1 reactivation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 teacher head, 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".