RSV and HMPV Infections in 3D Tissue Cultures: Mechanisms Involved in Virus-Host and Virus-Virus Interactions
Bibliographic record
Abstract
Respiratory viral infections constitute a global public health concern. Among prevalent respiratory viruses, two pneumoviruses can be life-threatening in high-risk populations. In young children, they constitute the first cause of hospitalization due to severe lower respiratory tract diseases. A better understanding of their pathogenesis is still needed as there are no approved efficient anti-viral nor vaccine against pneumoviruses. We studied Respiratory Syncytial virus (RSV) and human Metapneumovirus (HMPV) in single and dual infections in three-dimensional cultures, a highly relevant model to study viral respiratory infections of the airway epithelium. Our investigation showed that HMPV is less pathogenic than RSV in this model. Compared to RSV, HMPV replicated less efficiently, induced a lower immune response, did not block cilia beating, and was more sensitive to IFNs. In dual infections, RSV-infected epithelia were less permissive to HMPV. By neutralizing IFNs in co-infection assays, we partially prevented HMPV inhibition by RSV and significantly increased the number of co-infected cells in the tissue. This suggests that interference in dual infection would be at least partly mediated by the host immune response. In summary, this work provides new insight regarding virus-host and virus-virus interactions of pneumoviruses in the airway epithelium. This could be helpful for the proper handling of at-risk patients.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".