Airway-On-A-Chip: Designs and Applications for Lung Repair and Disease
Bibliographic record
Abstract
The lungs are affected by illnesses including asthma, chronic obstructive pulmonary disease, and infections such as influenza and SARS-CoV-2. Physiologically relevant models for respiratory conditions will be essential for new drug development. The composition and structure of the lung extracellular matrix (ECM) plays a major role in the function of the lung tissue and cells. Lung-on-chip models have been developed to address some of the limitations of current two-dimensional in vitro models. In this review, we describe various ECM substitutes utilized for modeling the respiratory system. We explore the application of lung-on-chip models to the study of cigarette smoke and electronic cigarette vapor. We discuss the challenges and opportunities related to model characterization with an emphasis on in situ characterization methods, both established and emerging. We discuss how further advancements in the field, through the incorporation of interstitial cells and ECM, have the potential to provide an effective tool for interrogating lung biology and disease, especially the mechanisms that involve the interstitial elements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".