Protective effects of 10 °C preservation on donor lungs with lipopolysaccharide-induced acute lung injury
Bibliographic record
Abstract
OBJECTIVES: Hypothermic lung preservation at 10 °C has been recently shown to enhance quality of healthy donor lungs during ischemia. This study aims to show generalizability of the 10 °C lung preservation using an endotoxin-induced lung injury with specific focus on the benefits of post-transplant lung function and mitochondrial preservation. METHODS: Lipopolysaccharide (3 mg/kg) was injected intratracheally in rats to induce lung injury. Injured lungs were flushed with preservation solution and allocated to 3 groups (n = 6 each): minimum cold storage, 6-hour storage on ice (ice), and 6-hour storage at 10 °C (10 °C). Left lungs were transplanted and reperfused for 2 hours. After storage, lung tissue was used to evaluate the effects of hypothermic storage on the mitochondrial function: mitochondrial membrane potential was assessed by JC-1 staining; mitochondrial oxygen consumption was assessed using high-resolution respirometry. RESULTS: Two hours after reperfusion, the oxygen tension/inspired oxygen fraction ratio from the graft was significantly greater in the 10 °C group than in the Ice group (P = .015), whereas the wet-to-dry weight ratio was significantly lower (P = .041). Levels of interleukin-8 in lung tissues were significantly lower in the 10 °C group than in the Ice group (P = .004). Mechanistically, we noted greater mitochondrial membrane potential and elevated state III respiration in the 10 °C group than in the Ice group (P = .015 and P = .002, respectively), implying higher metabolic activities may be maintained during 10 °C preservation. CONCLUSIONS: Favorable metabolism during 10 °C preservation prevented ischemia-induced mitochondrial damages in injured lungs, leading to better post-transplant outcomes.
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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".