Inhibition of Chemokine-Glycosaminoglycan Interactions in Donor Tissue Reduces Mouse Allograft Vasculopathy and Transplant Rejection
Bibliographic record
Abstract
BACKGROUND: Binding of chemokines to glycosaminoglycans (GAGs) is classically described as initiating inflammatory cell migration and creating tissue chemokine gradients that direct local leukocyte chemotaxis into damaged or transplanted tissues. While chemokine-receptor binding has been extensively studied during allograft transplantation, effects of glycosaminoglycan (GAG) interactions with chemokines on transplant longevity are less well known. Here we examine the impact of interrupting chemokine-GAG interactions and chemokine-receptor interactions, both locally and systemically, on vascular disease in allografts. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of GAG or CC chemokine receptor 2 (CCR2) deficiency were coupled with the infusion of viral chemokine modulating proteins (CMPs) in mouse aortic allograft transplants (n = 239 mice). Inflammatory cell invasion and neointimal hyperplasia were significantly reduced in N-deacetylase-N-sulfotransferase-1 (Ndst1(f/f)TekCre(+)) heparan sulfate (GAG)-deficient (Ndst1(-/-), p<0.044) and CCR2-deficient (Ccr2(-/-), p<0.04) donor transplants. Donor tissue GAG or CCR2 deficiency markedly reduced inflammation and vasculopathy, whereas recipient deficiencies did not. Treatment with three CMPs was also investigated; Poxviral M-T1 blocks CC chemokine receptor binding, M-T7 blocks C, CC, and CXC GAG binding, and herpesviral M3 binds receptor and GAG binding for all classes. M-T7 reduced intimal hyperplasia in wild type (WT) (Ccr2(+/+), p< or =0.003 and Ccr2(-/-), p</=0.027) aortic allografts, but not in Ndst1(-/-) aortic allografts (p = 0.933). M-T1 and M3 inhibited WT (Ccr2(+/+) and Ndst1(+/+), p< or =0.006) allograft vasculopathy, but did not block vasculopathy in Ccr2(-/-) (p = 0.61). M-T7 treatment alone, even without immunosuppressive drugs, also significantly prolonged survival of renal allograft transplants (p< or =0.001). CONCLUSIONS/SIGNIFICANCE: Interruption of chemokine-GAG interactions, even in the absence of chemokine-receptor blockade, is a highly effective approach to reduction of allograft rejection, reducing vascular inflammation and prolonging allograft survival. Although chemokines direct both local and systemic cell migration, interruption of inherent chemokine responses in the donor tissue unexpectedly had a greater therapeutic impact on allograft vasculopathy.
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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".