Peripheral blood monocyte-derived chemokine blockade prevents murine transfusion-related acute lung injury (TRALI)
Bibliographic record
Abstract
Transfusion-related acute lung injury (TRALI) is the leading cause of transfusion-related mortality and can occur with any type of transfusion. TRALI is thought to be primarily mediated by donor antibodies activating recipient neutrophils resulting in pulmonary endothelial damage. Nonetheless, details regarding the interactions between donor antibodies and recipient factors are unknown. A murine antibody-mediated TRALI model was used to elucidate the roles of the F(ab')2 and Fc regions of a TRALI-inducing immunoglobulin G anti-major histocompatibility complex (MHC) class I antibody (34.1.2s). Compared with intact antibody, F(ab')2 fragments significantly increased serum levels of the neutrophil chemoattractant macrophage inflammatory protein 2 (MIP-2); however, pulmonary neutrophil levels were only moderately increased, and no pulmonary edema or mortality occurred. Fc fragments did not modulate any of these parameters. TRALI induction by intact antibody was completely abrogated by in vivo peripheral blood monocyte depletion by gadolinium chloride (GdCl3) or chemokine blockade with a MIP-2 receptor antagonist but was restored upon repletion with purified monocytes. The results suggest a two-step process for antibody-mediated TRALI induction: the first step involves antibody binding its cognate antigen on blood monocytes, which generates MIP-2 chemokine production that is correlated with pulmonary neutrophil recruitment; the second step occurs when antibody-coated monocytes increase Fc-dependent lung damage.
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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) | 0.000 | 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) | 0.001 | 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".