Reparixin, a CXCR1/2 inhibitor in islet allotransplantation
Bibliographic record
Abstract
Quality of life in Type 1 diabetic patients may be improved with islet transplantation, but lifelong immunosuppression is required to prevent rejection. Allo-immune response is a key player in graft dysfunction and although the adaptive immune response is well characterized, the effect of the innate immune reaction after transplantation is only recently becoming appreciated. In this study, we address how the innate response affects long-term outcomes in a murine islet allotransplant model. CTLA-4 Ig treatment is known to significantly prolong kidney subcapsular islet allograft survival and enhance glucose tolerance. The combination of CTLA-4 Ig with reparixin, which blocks against inflammatory neutrophil infiltration, yielded no long-term graft survival in an intrahepatic allotransplant model but had similar long-term graft survival in the kidney subcapsular model. Seven days after transplant, serum blood IFN-γ levels were significantly lower in the CTLA-4 Ig with reparixin treatment group compared to controls. IL-12p70 cytokine levels were increased with combination treatment, a positive modulation of the inflammatory response to the allograft. Furthermore, KC GRO, also known as CXCL1, was decreased in serum 7 d after transplant. Histologically, we found that immune cell infiltrate, CD4+ and CD8+ T cell populations along with both CXCR1+ and CXCR2+ cell populations were decreased within the CTLA-4 Ig and reparixin islet transplant graft. Overall these data provide insight into the down regulation of T-cell recruitment by CTLA-4 Ig and decreased neutrophil activation and recruitment with reparixin after long-term islet graft survival.
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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".