Osteopontin mediates murine transfusion-related acute lung injury via stimulation of pulmonary neutrophil accumulation
Bibliographic record
Abstract
Transfusion-related acute lung injury (TRALI) is one of the leading causes of transfusion-related fatalities and is characterized by the onset of acute respiratory distress within 6 hours upon blood transfusion. Specific therapies are unavailable. Preexisting inflammation is a risk factor for TRALI and neutrophils (polymorphonuclear neutrophils [PMNs]) are considered to be the major pathogenic cells. Osteopontin (OPN) is a multifunctional protein expressed at sites of inflammation and, for example, is involved in pulmonary disorders, can regulate cellular migration, and can function as a PMN chemoattractant. We investigated whether OPN is involved in TRALI induction by promoting PMN recruitment to the lungs. Using a previously established murine TRALI model, we found that in contrast to wild-type (WT) mice, OPN knockout (KO) mice were resistant to antibody-mediated PMN-dependent TRALI induction. Administration of purified OPN to the OPN KO mice, however, restored the TRALI response and pulmonary PMN accumulation. Alternatively, blockade of OPN in WT mice using an anti-OPN antibody prevented the onset of TRALI induction. Using pulmonary immunohistochemistry, OPN could be specifically detected in the lungs of mice that suffered from TRALI. The OPN-mediated TRALI response seemed dependent on macrophages, likely the cellular source of OPN and OPN polymerization, and independent from the OPN receptor CD44, interleukin 6 (IL-6), and other PMN chemoattractants including macrophage inflammatory protein-2 (MIP-2). These data indicate that OPN is critically required for induction of antibody-mediated murine TRALI through localization to the lungs and stimulation of pulmonary PMN recruitment. This suggests that anti-OPN antibody therapy may be a potential therapeutic strategy to explore in TRALI patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".