A local drug delivery system prolongs graft survival by dampening T cell infiltration and neutrophil extracellular trap formation in vascularized composite allografts.
Bibliographic record
Abstract
INTRODUCTION The standard treatment for preventing rejection in vascularized composite allotransplantation (VCA) currently relies on systemic immunosuppression, which exposes the host to well-known side effects. Locally administered immunosuppression strategies have shown promising results to bypass this hurdle. Nevertheless, their progress has been slow, partially attributed to a limited understanding of the essential mechanisms underlying graft rejection. Recent discoveries highlight the crucial involvement of innate immune components, such as neutrophil extracellular traps (NETs), in organ transplantation. Here we aimed to prolong graft survival through a tacrolimus-based drug delivery system and to understand the role of NETs in VCA graft rejection. METHODS To prevent off-target toxicity and promote graft survival, we tested a locally administered tacrolimus-loaded on-demand drug delivery system (TGMS-TAC) in a multiple MHC-mismatched porcine VCA model. Off-target toxicity was assessed in tissue and blood. Graft rejection was evaluated macroscopically while the complement system, T cells, neutrophils and NETs were analyzed in graft tissues by immunofluorescence and/or western blot. Plasmatic levels of inflammatory cytokines were measured using a Luminex magnetic-bead porcine panel, and NETs were measured in plasma and tissue using DNA-MPO ELISA. Lastly, to evaluate the effect of tacrolimus on NET formation, NETs were induced in-vitro in porcine and human peripheral neutrophils following incubation with tacrolimus. RESULTS Repeated intra-graft administrations of TGMS-TAC minimized systemic toxicity and prolonged graft survival. Nevertheless, signs of rejection were observed at endpoint. Systemically, there were no increases in cytokine levels, complement anaphylatoxins, T-cell subpopulations, or neutrophils during rejection. Yet, tissue analysis showed local infiltration of T cells and neutrophils, together with neutrophil extracellular traps (NETs) in rejected grafts. Interestingly, intra-graft administration of tacrolimus contributed to a reduction in both T-cellular infiltration and NETs. In fact, in-vitro NETosis assessment showed a 62-84% reduction in NETs after stimulated neutrophils were treated with tacrolimus. CONCLUSION Our data indicate that the proposed local delivery of immunosuppression avoids off-target toxicity while prolonging graft survival in a multiple MHC-mismatch VCA model. Furthermore, NETs are found to play a role in graft rejection and could therefore be a potential innovative therapeutic target.
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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 | 0.001 | 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 | 0.003 |
| 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".