Caspase Inhibition Improves Ischemia-Reperfusion Injury After Lung Transplantation
Bibliographic record
Abstract
Ischemia-reperfusion injury is associated with cell death in many organ systems. The role of programmed cell death (PCD) pathways and the ultimate clinical relevance of PCD in the context of lung transplantation (LTx) are unknown. In randomized and blinded studies, rat single LTx was performed in the presence of caspase inhibitors after 'short' (6 h) and 'long' (18 h) periods of cold ischemic storage. Lung function, electron microscopic morphology, caspase 3, 8 and 9 activities and TUNEL assays were evaluated. Endothelial cells and lymphocytes were observed undergoing apoptotic cell death with electron microscopy. Caspase activities were significantly up-regulated immediately after the initial flush and increased further during short periods of cold ischemic storage. A significant amount of apoptotic cell death was observed after LTx and reperfusion. Caspase inhibition virtually eliminated apoptotic cell death and led to improved lung function after LTx and reperfusion. Activation of caspases during cold ischemia contributes significantly to cell death in LTx. Suppression of caspase activity appears to decrease apoptosis and improve lung function. Clearly, this needs to be investigated further with more experiments to validate the potential role of caspase inhibition as a therapeutic modality in ischemia-reperfusion-induced lung injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".