Rhinovirus Load Is High despite Preserved Interferon-β Response in Cystic Fibrosis Bronchial Epithelial Cells
Bibliographic record
Abstract
Lung disease in cystic fibrosis (CF) is often exacerbated following acute upper respiratory tract infections caused by the human rhinovirus (HRV). Pathophysiology of these exacerbations is presently unclear and may involve deficient innate antiviral or exaggerated inflammatory responses in CF airway epithelial cells. Furthermore, responses of CF cells to HRV may be adversely affected by pre-exposure to virulence factors of Pseudomonas (P.) aeruginosa, the microorganism that frequently colonizes CF airways. Here we examined production of antiviral cytokine interferon-β and inflammatory chemokine interleukin-8, expression of the interferon-responsive antiviral gene 2'-5'-oligoadenylate synthetase 1 (OAS1), and intracellular virus RNA load in primary CF (delF508 CFTR) and healthy airway epithelial cells following inoculation with HRV16. Parallel cells were exposed to virulence factors of P. aeruginosa prior to and during HRV16 inoculation. CF cells exhibited production of interferon-β and interleukin-8, and expression of OAS1 at levels comparable to those in healthy cells, yet significantly higher HRV16 RNA load during early hours post-inoculation with HRV16. In line with this, HRV16 RNA load was higher in the CFBE41o- dF cell line overexpessing delF508 CFTR, compared with the isogenic control CFBE41o- WT (wild-type CFTR). Pre-exposure to virulence factors of P. aeruginosa did not affect OAS1 expression or HRV16 RNA load, but potentiated interleukin-8 production. In conclusion, CF cells demonstrate elevated HRV RNA load despite preserved interferon-β and OAS1 responses. High HRV load in CF airway epithelial cells appears to be due to deficiencies manifesting early during HRV infection, and may not be related to interferon-β.
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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".