Stimulation of the RIG-I/MAVS Pathway by Polyinosinic:Polycytidylic Acid Upregulates IFN-β in Airway Epithelial Cells with Minimal Costimulation of IL-8
Bibliographic record
Abstract
Pharmacological stimulation of the antiviral cytokine IFN-β in the airways may help to counter deleterious virus-induced exacerbations in chronic inflammatory lung diseases (asthma, chronic obstructive pulmonary disease, or cystic fibrosis). Polyinosinic-polycytidylic acid [poly(I:C)] is a known inducer of IFN-β but also costimulates an inflammatory response. The latter response is undesirable given the pre-existing airway inflammation in these diseases. The objective of our study was to identify conditions for poly(I:C) to selectively upregulate IFN-β in airway epithelial cells without a concomitant inflammatory response. The inflammatory response was gauged by production of the chemokine IL-8. Using cell lines and primary airway epithelial cells (both submerged and well-differentiated), we observed that pure poly(I:C) stimulated IFN-β mainly through the TLR3/TRIF pathway and IL-8 through an unidentified pathway. The magnitude of the IL-8 response stimulated by pure poly(I:C) matched or even exceeded that of IFN-β. Furthermore, this IL-8 response could not be pharmacologically downregulated without affecting IFN-β. In contrast, we show that stimulation of the RIG-I/MAVS pathway, such as when poly(I:C) is delivered intracellularly in a complex with liposomes or via nucleofection, selectively stimulates IFN-β with low IL-8 costimulation. The magnitude of IFN-β stimulation by liposome-encapsulated poly(I:C) is markedly diminished in well-differentiated cells. In conclusion, it is feasible to augment IFN-β production in airway epithelial cells without excessive costimulation of IL-8 if the RIG-I/MAVS pathway is stimulated, such as via liposomal delivery of poly(I:C). Better cytoplasmic delivery vehicles are needed to efficiently stimulate this pathway in well-differentiated cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".