Development of a Neonatal Piglet Acute Lung Injury Model Recreating the Early Environment of Preterm Infant Lungs
Bibliographic record
Abstract
Premature birth is a major cause of pediatric morbidity and mortality. Bronchopulmonary dysplasia (BPD) is a severe consequence of extreme prematurity, leading to lung growth alterations and long-lasting developmental effects. The pathogenesis of BPD is multi-factorial, including mechanical ventilation, hyperoxia, and inflammation as the main drivers of its development. Currently, there is no treatment for BPD. In this study, a feasible and reproducible new neonatal piglet model of acute lung injury (ALI), mimicking the clinical stimuli faced by the human preterm lung, is presented. The multi-hit ALI neonatal piglet model - combining surfactant depletion, hyperoxia, high pressure-ventilation, and intratracheal lipopolysaccharide (LPS) administration results in impaired oxygenation, perturbed lung function, inflammation with neutrophil infiltration, and histological lung injury. Its main advantages are using the harmful stimuli known to drive BPD pathogenesis and its low maintenance. It generates high-fidelity ALI, meeting the American Thoracic Society ALI criteria. Large animal models, such as this piglet model, are critical to understanding early pathogenic factors, identifying therapeutic targets, and facilitating clinical translation to patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".