The Murine Double-Stranded RNA-Dependent Protein Kinase PKR Is Required for Resistance to Vesicular Stomatitis Virus
Bibliographic record
Abstract
Interferon (IFN)-induced antiviral responses are mediated through a variety of proteins, including the double-stranded RNA-dependent protein kinase PKR. Here we show that fibroblasts derived from PKR(-/-) mice are more permissive for vesicular stomatitis virus (VSV) infection than are wild-type fibroblasts and demonstrate a deficiency in alpha/beta-IFN-mediated protection. We further show that mice lacking PKR are extremely susceptible to intranasal VSV infection, succumbing within days after instillation with as few as 50 infectious viral particles. Again, alpha/beta-IFN was unable to rescue PKR(-/-) mice from VSV infection. Surprisingly, intranasally infected PKR(-/-) mice died not from pathology of the central nervous system but rather from acute infection of the respiratory tract, demonstrating high virus titers in the lungs compared to similarly infected wild-type animals. These results confirm the role of PKR as the major component of IFN-mediated resistance to VSV infection. Since previous reports have shown PKR to be nonessential for survival in animals challenged with encephalomyocarditis virus, influenza virus, and vaccinia virus (N. Abraham et al., J. Biol. Chem. 274:5953-5962, 1999; Y. Yang et al., EMBO J. 14:6095-6106, 1995), our findings serve to highlight the premise that host dependence on the various mediators of IFN-induced antiviral defenses is pathogen specific.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.001 | 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".