Modeling Cystic Fibrosis Chronic Infection Using Engineered Mucus-like Hydrogels
Bibliographic record
Abstract
The airway mucus of patients with cystic fibrosis has altered properties, which create a microenvironment primed for chronic infections that are difficult to treat. These complex polymicrobial airway infections and corresponding mammalian-microbe interactions are challenging to model in vitro. Here, we report the development of mucus-like hydrogels with varied compositions and viscoelastic properties reflecting differences between healthy and cystic fibrosis airway mucus. Models of cystic fibrosis and healthy airway microenvironments were created by combining the hydrogels with relevant pathogens, human bronchial epithelial cells, and an antibiotic. Notably, pathogen antibiotic resistance was not solely dependent on the altered properties of the mucus-like hydrogels but was also influenced by culture conditions including microbe species, monomicrobial or polymicrobial culture, and the presence of epithelial cells. Additionally, the cystic fibrosis airway model showed the ability to mimic features characteristic of chronic cystic fibrosis airway infections including sustained polymicrobial growth and increased antibiotic tolerance.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".