Low TRBP Levels Support an Innate Human Immunodeficiency Virus Type 1 Resistance in Astrocytes by Enhancing the PKR Antiviral Response
Bibliographic record
Abstract
Acute human immunodeficiency virus type 1 (HIV-1) replication in astrocytes produces minimal new virus particles due, in part, to inefficient translation of viral structural proteins despite high levels of cytoplasmic viral mRNA. We found that a highly reactive double-stranded (ds) RNA-binding protein kinase (PKR) response in astrocytes underlies this inefficient translation of HIV-1 mRNA. The dsRNA elements made during acute replication of HIV-1 in astrocytes triggers PKR activation and the specific inhibition of HIV-1 protein translation. The heightened PKR response results from relatively low levels of the cellular antagonist of PKR, the TAR RNA binding protein (TRBP). Efficient HIV-1 production was restored in astrocytes by inhibiting the innate PKR response to HIV-1 dsRNA with dominant negative PKR mutants, or PKR knockdown by siRNA gene silencing. Increasing the expression of TRBP in astrocytes restored acute virus production to levels comparable to those observed in permissive cells. Therefore, the robust innate PKR antiviral response in astrocytes results from relatively low levels of TRBP expression and contributes to their restricted infection. Our findings highlight TRBP as a novel cellular target for therapeutic interventions to block productive HIV-1 replication in cells that are fully permissive for HIV-1 infection.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".