Faculty Opinions recommendation of Role of double-stranded RNA pattern recognition receptors in rhinovirus-induced airway epithelial cell responses.
Bibliographic record
Abstract
Rhinovirus (RV), a single-stranded RNA virus of the picornavirus family, is a major cause of the common cold as well as asthma and chronic obstructive pulmonary disease exacerbations.Viral double-stranded RNA produced during replication may be recognized by the host pattern recognition receptors Toll-like receptor (TLR)-3, retinoic acid inducible gene (RIG)-I and melanoma-differentiation-associated gene (MDA)-5.No study has yet identified the receptor required for sensing RV double-stranded (ds)-RNA.To examine this, BEAS-2B human bronchial epithelial cells were infected with intact RV-1B or replication-deficient UV-irradiated virus, and interferon (IFN) and IFN-stimulated gene expression determined by quantitative PCR.The separate requirements of RIG-I, MDA5 and IFN response factor (IRF)-3 were determined using their respective siRNAs.The requirement of TLR3 was determined using siRNA against the TLR3 adaptor molecule TRIF.Intact RV-1B, but not UV-irradiated RV, induced IRF3 phosphorylation and dimerization, as well as mRNA expression of IFN-β̤ , IFN-λ̣ 1, IFN-λ2/3, IRF7, RIG-I, MDA5, IP-10/CXCL10, IL-8/CXCL8 and GM-CSF.siRNA against IRF3, MDA5 and TRIF, but not RIG-I, decreased RV1B-induced expression of IFN-β̤ IFN-λ̣ 1, IFN-λ2/3, IRF7, RIG-I, MDA5 and IP-10/CXCL10, but had no effect on IL-8/CXCL8 and GM-CSF.siRNAs against MDA5 and TRIF also reduced IRF3 dimerization.Finally, in primary cells, transfection with MDA5 siRNA significantly reduced IFN expression, as it did in BEAS-2B cells.These results suggest that TLR3 and MDA5, but not RIG-I, are required for maximal sensing of RV dsRNA, and that TLR3 and MDA5 signal through a common downstream signaling intermediate, IRF3.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.409 | 0.243 |
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".