Multiple levels of PKR inhibition during HIV‐1 replication
Why this work is in the frame
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Bibliographic record
Abstract
Recent therapeutic approaches against HIV-1 include IFN in combination therapy for patients with coinfections or as an alternative strategy against the virus. These treatment options require a better understanding of the weak efficacy of the IFN-stimulated genes, such as the protein kinase RNA-activated (PKR), which results in viral progression. Activated PKR has a strong antiviral activity on HIV-1 expression and production in cell culture. However, PKR is not activated upon HIV-1 infection when the virus reaches high levels of replication, due to viral and cellular controls. PKR is activated by low levels of the HIV-1 trans-activation response (TAR) RNA element, but is inhibited by high levels of this double-stranded RNA. The viral Tat protein also counteracts PKR activation by several mechanisms. In addition, HIV-1 replicates only in cells that have a high level of the TAR RNA binding protein (TRBP), a strong inhibitor of PKR activation. Furthermore, increased levels of adenosine deaminase acting on RNA (ADAR1) are observed when HIV-1 replicates at high levels and the protein binds to PKR and inhibits its activation. Finally, the PKR activator (PACT) also binds to PKR during HIV-1 replication with no subsequent kinase activation. The combination of all the inhibiting pathways that prevent PKR phosphorylation contributes to a high HIV-1 production in permissive cells. Enhancing PKR activation by counteracting its inhibitory partners could establish an increased innate immune antiviral pathway against HIV-1 and could enhance the efficacy of the IFN treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 it