Role of Fibrinogen-Like Protein 2 Prothrombinase/Fibroleukin in Experimental and Human Allograft Rejection
Bibliographic record
Abstract
Immune coagulation is a major contributor to the pathogenesis of xenograft rejection, viral-induced hepatocellular injury and cytokine-induced fetal loss syndrome. In this study, we investigated the contribution of the novel gene product, fibrinogen-like protein 2 (fgl2) prothrombinase, in mediating immune injury in experimental and human acute allograft rejection. Using a mouse heterotopic cardiac transplant model, mouse fgl2(mfgl2)/fibroleukin mRNA transcripts and protein were highly expressed in macrophages, CD4- and CD8-positive T lymphocytes, and endothelial cells in rejecting cardiac allografts in association with deposits of fibrin. Although mfgl2-deficient mice rejected allografts at similar rates to littermate controls, survival of grafts from mfgl2-deficient mice were prolonged and deposition of intravascular fibrin was diminished. Treatment of wild-type mice with a neutralizing anti-fgl2 Ab ameliorated histological evidence for allorejection and intravascular fibrin deposition, and resulted in an increase in graft survival. To address further the relevance of fgl2 in acute allograft rejection, we examined kidney biopsies from patients who had undergone renal transplantation. Human fgl2 mRNA transcripts and protein were markedly expressed mainly in renal tubule cells, infiltrating lymphoid cells including macrophages, CD8(+) T cells, mature B cells (plasma cells), and endothelial cells. Dual staining showed fibrin deposition was localized mainly to blood vessels, in the glomerulus and interstitium and the lumen of tubules, and occurred in association with human fgl2 expression. These data collectively suggest that fgl2 accounts for the fibrin deposition seen in both experimental and human allograft rejection and provide a rationale for targeting fgl2 as adjunctive therapy to treat allograft rejection.
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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 | 0.000 |
| 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".