Strategies to Improve and Stabilize Extended Ex Vivo Lung Perfusion
Bibliographic record
Abstract
Despite the success of lung transplantation to treat end-stage lung diseases, organ shortage remains to be a major limitation. The Toronto Ex vivo lung perfusion (EVLP) protocol has improved assessment of donor lungs and provides an unique platform to repair lungs, with the goal of expanding the organ pool and improving long-term outcomes. However, the use of the technique is limited to ~12h, which limits advances in therapeutic strategies. We sought to determine whether a continuous replacement strategy or a modified feed could be used to operate EVLP to preserve lung integrity for extended perfusion time(24h). During EVLP, pig lungs were subjected to Toronto protocol, continuous perfusate replacement, or modified feed. By using a clinically relevant swine model, here we report the use of continuous perfusate replacement during prolonged EVLP preserved lung integrity for 24h. The application of this operation in EVLP will allow for advanced therapeutic interventions currently not feasible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".