RAIDD Mediates TLR3 and IRF7 Driven Type I Interferon Production
Bibliographic record
Abstract
BACKGROUND/AIMS: Viral infections represent a global health problem with the need for new viral therapies and better understanding of the immune response during infection. The most immediate and potent anti-viral defense mechanism is the production of type I interferon (IFN-I) which are activated rapidly following recognition of viral infection by host pathogen recognition receptors (PRR). The mechanisms of innate cellular signaling downstream of PRR activation remain to be fully understood. In the present study, we demonstrate that CASP2 and RIPK1 domain-containing adaptor with death domain (CRADD/RAIDD) is a critical component in type I IFN production. METHODS: The role of RAIDD during IFN-I production was investigated using western blot, shRNA mediated lentiviral knockdown, immunoprecipitation and IFN-I driven dual luciferase assay. RESULTS: Immunoprecipitation analysis revealed the molecular interaction of RAIDD with interferon regulatory factor 7 (IRF7) and its phosphorylating kinase IKKε. Using an IFN-4α driven dual luciferase analysis in RAIDD deficient cells, type I IFN activation by IKKε and IRF7 was dramatically reduced. Furthermore, deletion of either the caspase recruitment domain (CARD) or death domain (DD) of RAIDD inhibited IKKε and IRF7 mediated interferon-4α activation. CONCLUSION: We have identified that the adaptor molecule RAIDD coordinates IKKε and IRF7 interaction to ensure efficient expression of type I interferon.
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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 | 0.001 |
| 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) | 0.003 | 0.002 |
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".