P-270WARM VERSUS COLD DONOR LUNG ISCHAEMIC PRESERVATIONS ACTIVATE DISTINCT MECHANISMS DURING DEVELOPMENT OF POST-TRANSPLANT PULMONARY DYSFUNCTION
Bibliographic record
Abstract
Objectives: Ischaemia-reperfusion injury related to lung transplantation (LTx) is a major contributor to early postoperative morbidity and mortality. Severe lung injury is seen when using donor lungs after prolonged hypothermic preservation or donation after cardiac death. We hypothesized that different injury mechanisms will be associated with increased cold and warm ischaemic times (CIT and WIT). Methods: Donor lung injury was induced with (i) 18 h CIT after harvest, and (ii) 3 h WIT before retrieval. Twelve hour CIT was used as a low-injury control. Left single LTx was performed using a separate ventilation technique. After 2 h of reperfusion, pulmonary vein blood gases were analysed, and the grafts and plasma were harvested for multi-cytokine and M65 assays. Results: Pulmonary oxygenation was significantly worse in both 18 hCIT and WIT groups, with higher peak airway pressures during the reperfusion, compared to the control. Interleukin (IL)-1α, IL-1β, IL-18, IL-6, VEGF, and chemokines CCL2, CCL3, CXCL1, and CXCL2 were up-regulated in all groups when comparing end-reperfusion time points to pre-transplant. Notably, graft tissue levels of these analytes were significantly lower in the WIT group compared to the CIT groups. Conversely, systemic plasma levels of all analytes were elevated in the WIT group. Levels of plasma M65 were not detectable in the 12 h CIT group, but were significantly elevated in both 18 h CIT and WIT groups. Conclusions: Compared to 12 h CIT, pulmonary physiology deteriorated to a similar degree in both the 18 h CIT and 3 h WIT groups. However, the inflammatory response was more severe locally in grafts after 18 h CIT, whereas the systemic response and cell death signal (M65) were more severe in the WIT group. The distinct inflammatory responses indicate that the type of donor lung injury should be carefully considered when developing specific therapeutic strategies to reduce lung injury. Disclosure: No significant relationships.
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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) | 0.003 | 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".