Ex vivo perfusion induces a time- and perfusate-dependent molecular repair response in explanted porcine lungs
Bibliographic record
Abstract
Ex vivo lung perfusion (EVLP) shows promise in ameliorating pretransplant acute lung injury (ALI) and expanding the donor organ pool, but the mechanisms of ex vivo repair remain poorly understood. We aimed to assess the utility of gene expression for characterizing ALI during EVLP. One hundred sixty-nine porcine lung samples were collected in vivo (n = 25), after 0 (n = 11) and 12 (n = 11) hours of cold static preservation (CSP), and after 0 (n = 57), 6 (n = 8), and 12 (n = 57) hours of EVLP, utilizing various ventilation and perfusate strategies. The expression of 53 previously described ALI-related genes was measured and correlated with function and histology. Twenty-eight genes were significantly upregulated and 6 genes downregulated after 12 hours of EVLP. Aggregate gene sets demonstrated differential expression with EVLP (P < .001) but not CSP. Upregulated 28-gene set expression peaked after 6 hours of EVLP, whereas downregulated 6-gene set expression continued to decline after 12 hours. Cellular perfusates demonstrated a greater reduction in downregulated 6-gene set expression vs acellular perfusate (P < .038). Gene set expression correlated with relevant functional and histologic parameters, including P/F ratio (P < .001) and interstitial inflammation (P < .005). Further studies with posttransplant results are warranted to evaluate the clinical significance of this novel molecular approach for assessing organ quality during EVLP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".