Physiologic and Biologic Characteristics of Three Experimental Models of Acute Lung Injury in Rats
Bibliographic record
Abstract
BACKGROUND: Strategies to attenuate ventilator-associated lung injury have been tested in various experimental methods of acute lung injury (ALI). Conclusions are often drawn from physiologic and biologic effects, but the influence of the model on these results is not known. Our aim in this study was to characterize frequently used models of experimental ALI. METHODS: Twenty Sprague Dawley rats were anesthetized and their lungs mechanically ventilated for 5 hours. Three models of ALI (surfactant washout, acid aspiration, and high tidal volume ventilation) were investigated with regard to hemodynamics, respiratory mechanics, gas exchange, lung pathology, and inflammatory reactions. Animals without ALI served as controls. RESULTS: Five animals in each group were analyzed. Dynamic compliance and Pao(2)/fraction of inspired oxygen ratio decreased by at least 50% in all groups after 1 hour. Whereas compliance remained decreased in all models, oxygenation returned to baseline values in the lavage group after 5 hours. Diffuse alveolar damage was worse in the high tidal volume model and was not different between the control and lavage animals. Interleukin-6 was increased in bronchoalveolar lavage fluid in the aspiration and high tidal volume models. CONCLUSIONS: Although comparable physiologic effects meeting acute respiratory distress syndrome criteria were achieved in all models, the biologic responses varied among lung injury models. The acid aspiration model created both respiratory and inflammatory responses typically seen in ALI; these data suggest that it may be the most clinically applicable model to study the intermediate-term effects of ventilator-associated lung injury in rats.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".