Atelectasis Causes Alveolar Injury in Nonatelectatic Lung Regions
Bibliographic record
Abstract
RATIONALE: Many authors have suggested that the mechanism by which atelectasis contributes to injury is through the repetitive opening and closing of distal airways in lung regions that are atelectatic. However, neither the topographic nor mechanistic relationships between atelectasis and distribution of lung injury are known. OBJECTIVES: To investigate how atelectasis contributes to ventilator-induced lung injury. METHODS: Surfactant depletion was performed in anesthetized rats that were then allocated to noninjurious or injurious ventilation for 90 min. MEASUREMENTS: Lung injury was quantified by gas exchange, compliance, histology, wet-to-dry weight, and cytokine expression, and its distribution by histology, stereology, cytokine mRNA expression, in situ hybridization, and immunohistochemistry. Functional residual capacity, percent atelectasis, and injury-induced lung water accumulation were measured using gravimetric and volumetric techniques. MAIN RESULTS: Atelectasis occurred in the dependent lung regions. Injurious ventilation was associated with alveolar and distal airway injury, while noninjurious ventilation was not. With injurious ventilation, alveolar injury (i.e., histology, myeloperoxidase protein expression, quantification, and localization of cytokine mRNA expression) was maximal in nondependent regions, whereas distal airway injury was equivalent in atelectatic and nonatelectatic regions. CONCLUSIONS: These data support the notion that lung injury associated with atelectasis involves trauma to the distal airways. We provide topographic and biochemical evidence that such distal airway injury is not localized solely to atelectatic areas, but is instead generalized in both atelectatic and nonatelectatic lung regions. In contrast, alveolar injury associated with atelectasis does not occur in those areas that are atelectatic but occurs instead in remote nonatelectatic alveoli.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".