Alpha/Beta Interferons Potentiate Virus-Induced Apoptosis through Activation of the FADD/Caspase-8 Death Signaling Pathway
Bibliographic record
Abstract
Interferon (IFN) mediates its antiviral effects by inducing a number of responsive genes, including the double-stranded RNA (dsRNA)-dependent protein kinase, PKR. Here we report that inducible overexpression of functional PKR in murine fibroblasts sensitized cells to apoptosis induced by influenza virus, while in contrast, cells expressing a dominant-negative variant of PKR were completely resistant. We determined that the mechanism of influenza virus-induced apoptosis involved death signaling through FADD/caspase-8 activation, while other viruses such as vesicular stomatitis virus (VSV) and Sindbis virus (SNV) did not significantly provoke PKR-mediated apoptosis but did induce cytolysis of fibroblasts via activation of caspase-9. Significantly, treatment with IFN-alpha/beta greatly sensitized the fibroblasts to FADD-dependent apoptosis in response to dsRNA treatment or influenza virus infection but completely protected the cells against VSV and SNV replication in the absence of any cellular destruction. The mechanism by which IFN increases the cells' susceptibility to lysis by dsRNA or certain virus infection is by priming cells to FADD-dependent apoptosis, possibly by regulating the activity of the death-induced signaling complex (DISC). Conversely, IFN is also able to prevent the replication of viruses such as VSV that avoid triggering FADD-mediated DISC activity, by noncytopathic mechanisms, thus preventing destruction of the cell.
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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".