Incompatible erythrocyte transfusion with lipopolysaccharide induces acute lung injury in a novel rat model
Bibliographic record
Abstract
Acute transfusion reactions can manifest in many forms including acute hemolytic transfusion reaction, allergic reaction and transfusion-related acute lung injury. We previously developed an acute hemolytic transfusion reaction rat model mediated by transfusion of incompatible human erythrocytes against which rats have preexisting antibodies resulting in classical complement pathway mediated intravascular hemolysis. In this study, the acute hemolytic transfusion reaction model was adapted to yield an acute lung injury phenotype. Adolescent male Wistar rats were primed in the presence or absence of lipopolysaccharide followed by transfusion of incompatible erythrocytes. Blood was collected at various time points during the course of the experiment to determine complement C5a levels and free DNA in isolated plasma. At 4 hours, blood and lung tissue were recovered and assayed for complete blood count and histological acute lung injury, respectively. Compared to sham animals or animals receiving increasing amounts of incompatible erythrocytes (equivalent to a 15-45% transfusion) in the absence of lipopolysaccharide, lungs of animals receiving lipopolysaccharide and a 30% erythrocyte transfusion showed dramatic alveolar wall thickening due to neutrophil infiltration. C5a levels were significantly elevated in these animals indicating that complement activation contributes to lung damage. Additionally, these animals demonstrated a significant increase of free DNA in the blood over time suggestive of neutrophil extracellular trap formation previously associated with transfusion-related acute lung injury in humans and mice. This novel 'two-hit' model utilizing incompatible erythrocyte transfusion in the presence of lipopolysaccharide yields a robust acute lung injury phenotype.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".