Exploring alveolar recruitability using positive end-expiratory pressure in mice overexpressing TGF-β1: a structure–function analysis
Bibliographic record
Abstract
Abstract Pre-injured lungs are prone to injury progression in response to mechanical ventilation. Heterogeneous ventilation due to (micro)atelectases imparts injurious strains on open alveoli (known as volutrauma). Hence, recruitment of (micro)atelectases by positive end-expiratory pressure (PEEP) is necessary to interrupt this vicious circle of injury but needs to be balanced against acinar overdistension. In this study, the lung-protective potential of alveolar recruitment was investigated and balanced against overdistension in pre-injured lungs. Mice, treated with empty vector (AdCl) or adenoviral active TGF-β1 (AdTGF-β1) were subjected to lung mechanical measurements during descending PEEP ventilation from 12 to 0 cmH2O. At each PEEP level, recruitability tests consisting of two recruitment maneuvers followed by repetitive forced oscillation perturbations to determine tissue elastance (H) and damping (G) were performed. Finally, lungs were fixed by vascular perfusion at end-expiratory airway opening pressures (Pao) of 20, 10, 5 and 2 cmH2O after a recruitment maneuver, and processed for design-based stereology to quantify derecruitment and distension. H and G were significantly elevated in AdTGF-β1 compared to AdCl across PEEP levels. H was minimized at PEEP = 5–8 cmH2O and increased at lower and higher PEEP in both groups. These findings correlated with increasing septal wall folding (= derecruitment) and reduced density of alveolar number and surface area (= distension), respectively. In AdTGF-β1 exposed mice, 27% of alveoli remained derecruited at Pao = 20 cmH2O. A further decrease in Pao down to 2 cmH2O showed derecruitment of an additional 1.1 million alveoli (48%), which was linked with an increase in alveolar size heterogeneity at Pao = 2–5 cmH2O. In AdCl, decreased Pao resulted in septal folding with virtually no alveolar collapse. In essence, in healthy mice alveoli do not derecruit at low PEEP ventilation. The potential of alveolar recruitability in AdTGF-β1 exposed mice is high. H is optimized at PEEP 5–8 cmH2O. Lower PEEP folds and larger PEEP stretches septa which results in higher H and is more pronounced in AdTGF-β1 than in AdCl. The increased alveolar size heterogeneity at Pao = 5 cmH2O argues for the use of PEEP = 8 cmH2O for lung protective mechanical ventilation in this animal 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".