Rhinovirus Induces Basolateral Release of IL-17C in Highly Differentiated Airway Epithelial Cells
Bibliographic record
Abstract
Human rhinovirus (HRV) is a major trigger of acute exacerbations of both asthma and chronic obstructive pulmonary disease. The airway epithelium is the primary site of HRV infection, and responds by releasing proinflammatory and antimicrobial cytokines. Epithelial cells release IL-17C in response to exposure to bacterial, viral, and fungal pathogens. We previously demonstrated a role for HRV in IL-17C production from undifferentiated epithelial cells, and showed that IL-17C could play a role in neutrophil recruitment. To extend these observations, highly differentiated human bronchial epithelial cells (HBE) were infected apically with HRV to assess the effect of dose, time, viral replication, and strain on the IL-17C response. Cellular lysates, and basolateral and apical secretions were analyzed for IL-17C and CXCL1 protein release following HRV or IL-17C stimulation. Upon HRV infection, IL-17C protein was exclusively released basolaterally in a dose-, time-, and viral replication-dependent manner. Several strains of rhinovirus were capable of inducing IL-17C release. Enriched columnar epithelial cell populations contained significantly higher viral titer, and expressed significantly more IL-17C mRNA than enriched basal cell populations. In addition, the kinetic profile of IL-17C release following HRV treatment closely mimics viral shedding kinetics, further implicating the role of rhinovirus replication in IL-17C production. Basolateral treatment of HBEs with IL-17C resulted in a dose-dependent increase in basolateral CXCL1 production. In summary, replicating rhinovirus drives basolateral IL-17C protein release from both apical and basal epithelial cells, which may then act in an autocrine/paracrine manner to promote basolateral CXCL1 protein release.
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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 | 0.001 |
| 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) | 0.001 | 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".