Influenza Virus Receptor Specificity and Cell Tropism in Mouse and Human Airway Epithelial Cells
Bibliographic record
Abstract
Recent human infections caused by the highly pathogenic avian influenza virus H5N1 strains emphasize an urgent need for assessment of factors that allow viral transmission, replication, and intra-airway spread. Important determinants for virus infection are epithelial cell receptors identified as glycans terminated by an alpha2,3-linked sialic acid (SA) that preferentially bind avian strains and glycans terminated by an alpha2,6-linked SA that bind human strains. The mouse is often used as a model for study of influenza viruses, including recent avian strains; however, the selectivity for infection of specific respiratory cell populations is not well described, and any relationship between receptors in the mouse and human lungs is incompletely understood. Here, using in vitro human and mouse airway epithelial cell models and in vivo mouse infection, we found that the alpha2,3-linked SA receptor was expressed in ciliated airway and type II alveolar epithelial cells and was targeted for cell-specific infection in both species. The alpha2,6-linked SA receptor was not expressed in the mouse, a factor that may contribute to the inability of some human strains to efficiently infect the mouse lung. In human airway epithelial cells, alpha2,6-linked SA was expressed and functional in both ciliated and goblet cells, providing expanded cellular tropism. Differences in receptor and cell-specific expression in these species suggest that differentiated human airway epithelial cell cultures may be superior for evaluation of some human strains, while the mouse can provide a model for studying avian strains that preferentially bind only the alpha2,3-linked SA receptor.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".