Inflammatory epithelial cytokines after<i>in vitro</i>respiratory syncytial viral infection are associated with reduced lung function
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) infections in early life predispose children with cystic fibrosis (CF) to more severe lung function decline in later life. The mechanisms explaining the associations between RSV and progression of CF lung disease are not clear. In this study, a human bronchial epithelial cell line and primary human nasal epithelial cells (PNECs) from individuals with CF and healthy control donors were infected with RSV. Real-time PCR, plaque assay, cytokine detection, immunofluorescence and Western blot analyses were performed. RSV is replicated to a higher degree in CF epithelial cells as compared to control cells; however, no defects in innate immune pathways were identified in CF cells. Rather, primary p.Phe508del cystic fibrosis transmembrane conductance regulator PNECs produced more cytokines after RSV infection than control cells. Moreover, interleukin-8 and tumour necrosis factor-α production post RSV negatively correlated with lung function (% predicted forced expiratory volume in 1 s) in the individuals who donated the cells. These data suggest that CF epithelium has a dysfunctional response to RSV allowing for enhanced viral replication and an exaggerated inflammatory response that ultimately may predispose to greater airway inflammation and reduced lung function.
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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 | 0.001 | 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".