Urokinase Receptor Is Necessary for Bacterial Defense against Pneumonia-Derived Septic Melioidosis by Facilitating Phagocytosis
Bibliographic record
Abstract
Urokinase receptor (urokinase-type plasminogen activator receptor [uPAR], CD87), a GPI-anchored protein, is considered to play an important role in inflammation and fibrinolysis. The Gram-negative bacterium Burkholderia pseudomallei is able to survive and replicate within leukocytes and causes melioidosis, an important cause of pneumonia-derived community-acquired sepsis in Southeast Asia. In this study, we investigated the expression and function of uPAR both in patients with septic melioidosis and in a murine model of experimental melioidosis. uPAR mRNA and surface expression was increased in patients with septic melioidosis in/on both peripheral blood monocytes and granulocytes as well as in the pulmonary compartment during experimental pneumonia-derived melioidosis in mice. uPAR-deficient mice intranasally infected with B. pseudomallei showed an enhanced growth and dissemination of B. pseudomallei when compared with wild-type mice, corresponding with increased pulmonary and hepatic inflammation. uPAR knockout mice demonstrated significantly reduced neutrophil migration toward the pulmonary compartment after inoculation with B. pseudomallei. Further in vitro experiments showed that uPAR-deficient macrophages and granulocytes display a markedly impaired phagocytosis of B. pseudomallei. Additional studies showed that uPAR deficiency did not influence hemostatic and fibrinolytic responses during severe melioidosis. These data suggest that uPAR is crucially involved in the host defense against sepsis caused by B. pseudomallei by facilitating the migration of neutrophils toward the primary site of infection and subsequently facilitating the phagocytosis of B. pseudomallei.
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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 | 0.001 |
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".