Influenza virus antagonizes self sensing by RIG-I to enhance viral replication
Bibliographic record
Abstract
Innate immune sensors must finely distinguish pathogens from the host to mount a response only during infection. RIG-I is cytoplasmic sensor that surveils for foreign RNAs. When activated, RIG-I triggers a broad antiviral response that is a major regulator of RNA virus infection. Here were show that RIG-I not only bound viral RNAs, but was activated by host RNAs to amplify the antiviral state. These were primarily non-coding RNAs transcribed by RNA polymerase III. They were benign under normal conditions but became immunogenic during influenza virus infection where they signaled via RIG-I to suppress viral replication. This same class of RNAs was bound by influenza virus nucleoprotein (NP), which normally functions to encapsidate the viral genome. NP interacted with RIG-I and antagonized sensing of self RNAs to counter innate immune responses. Overall, these results demonstrate that self sensing is strategically deployed by the cell to amplify the antiviral response and reveal a newly identified viral countermeasure that disrupts RIG-I activation by host RNAs.
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) | 0.000 | 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".