Negative Pressure Ventilation Ex‐Situ Lung Perfusion Preserves Porcine and Human Lungs for 36‐Hours
Bibliographic record
Abstract
INTRODUCTION: Preclinically, 24-hour continuous Ex-Situ Lung Perfusion (ESLP) is the longest duration achieved in large animal models and rejected human lungs. Here, we present our 36-hour Negative Pressure Ventilation (NPV)-ESLP protocol applied to porcine and rejected human lungs. METHODS: Five sets of donor domestic pig lungs (45-55 kg) underwent 36-hour NPV-ESLP. Two sets of clinically rejected human lungs were preserved on 36-hour NPV-ESLP. Graft function was assessed via physiologic parameters, edema formation, and cytokine profiles. RESULTS: Porcine and human lung function was stable with mean partial pressure of oxygen divided by the fraction of inspired oxygen (PaO2/FiO2; PF) ratios throughout preservation of 473±11.79 and 554.7±13.26, respectively (mean±standard error of the mean). In porcine lungs, mean compliance (Cdyn) during ESLP was 33.96±2.18, pulmonary artery pressure (PAP) 13.03±0.53, and pulmonary vascular resistance (PVR) 481.20 ±21.86. In human lungs, mean Cdyn was 82.68±3.54, PAP 6.00±0.33, and PVR 184.00±9.71. Average percentage weight-gain was 34.47±13.22 in porcine lungs and 116.3±6.65 in rejected human lungs. CONCLUSION: NPV-ESLP can preserve porcine lungs and human lungs for 36-hours with acceptable physiologic function. Greater weight-gain in the human lungs is likely due to prolonged ischemic time prior to ESLP and use of an acellular perfusate. Continuous 36-hour NPV-ESLP could support therapies for endothelial protection and mitigate fluid accumulation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".