Apical-out airway organoids as a platform for studying viral infections and screening for antiviral drugs
Bibliographic record
Abstract
Airway organoids are polarized 3D epithelial structures that recapitulate the organization and many of the key functions of the in vivo tissue. They present an attractive model that can overcome some of the limitations of traditional 2D and Air-Liquid Interface (ALI) models, yet the limited accessibility of the organoids' apical side has hindered their applications in studies focusing on host-pathogen interactions. Here, we describe a scalable, fast and efficient way to generate airway organoids with the apical side externally exposed. These apical-out airway organoids are generated in an Extracellular Matrix (ECM)-free environment from 2D-expanded bronchial epithelial cells and differentiated in suspension to develop uniformly-sized organoid cultures with robust ciliogenesis. Differentiated apical-out airway organoids are susceptible to infection with common respiratory viruses and show varying responses upon treatment with antivirals. In addition to the ease of apical accessibility, these apical-out airway organoids offer an alternative in vitro model to study host-pathogen interactions in higher throughput than the traditional air-liquid interface model.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".