Rhinovirus replication and innate immunity in highly differentiated human airway epithelial cells
Bibliographic record
Abstract
BACKGROUND: Human rhinovirus (HRV) infections are the primary cause of the common cold and are a major trigger for exacerbations of lower airway diseases, such as asthma and chronic obstructive pulmonary diseases. Although human bronchial epithelial cells (HBE) are the natural host for HRV infections, much of our understanding of how HRV replicates and induces host antiviral responses is based on studies using non-airway cell lines (e.g. HeLa cells). The current study examines the replication cycle of HRV, and host cell responses, in highly differentiated cultures of HBE. METHODS: ) of purified HRV-16, and responses were monitored up to 144 h after infection. Viral genomic RNA and negative strand RNA template levels were monitored, along with levels of type I and II interferons and selected antivirals. RESULTS: Regardless of initial infectious dose, relatively constant levels of both genomic and negative strand RNA are generated during replication, with negative strand copy numbers being10,000-fold lower than those of genomic strands. Infections were limited to a small percentage of ciliated cells and did not result in any overt signs of epithelial death. Importantly, regardless of infectious dose, HRV-16 infections were cleared by HBE in the absence of immune cells. Levels of type I and type III interferons (IFNs) varied with initial infectious dose, implying that factors other than levels of double-stranded RNA regulate IFN induction, but the time-course of HRV-16 clearance HBE was the same regardless of levels of IFNs produced. Patterns of antiviral viperin and ISG15 expression suggest they may be generated in an IFN-independent manner during HRV-16 infections. CONCLUSIONS: These data challenge a number of aspects of dogma generated from studies in HeLa cells and emphasize the importance of appropriate cell context when studying HRV infections.
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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 | 0.001 |
| 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".